Relevant bibliographies by topics / Linear Multi-Target

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers
  5. Reports

Academic literature on the topic 'Linear Multi-Target'

Author: Grafiati
Published: 4 June 2021
Last updated: 2 February 2022

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Journal articles on the topic "Linear Multi-Target"

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Radosavljevic, Zvonko, Song Lyul, and Branko Kovacevic. "Linear multi-target IPF algorithm for automatic tracking." Scientific Technical Review 66, no. 1 (2016): 3–10. http://dx.doi.org/10.5937/str1601003r.

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Clark, Daniel E. "Multi-Sensor Network Information for Linear-Gaussian Multi-Target Tracking Systems." IEEE Transactions on Signal Processing 69 (2021): 4312–25. http://dx.doi.org/10.1109/tsp.2021.3096044.

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Khunsmuth, K., and T. Mouktonglang. "Discrete multi-target linear-quadratic control problem and quadratic programming." Applied Mathematical Sciences 7 (2013): 4037–48. http://dx.doi.org/10.12988/ams.2013.35279.

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Courrieu, Pierre. "On the convergence of rank-one multi-target linear regression." Statistics 55, no. 1 (January 2, 2021): 68–89. http://dx.doi.org/10.1080/02331888.2021.1891236.

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Liu, Rang, Hongqi Fan, Tiancheng Li, and Huaitie Xiao. "A Computationally Efficient Labeled Multi-Bernoulli Smoother for Multi-Target Tracking." Sensors 19, no. 19 (September 28, 2019): 4226. http://dx.doi.org/10.3390/s19194226.

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A forward–backward labeled multi-Bernoulli (LMB) smoother is proposed for multi-target tracking. The proposed smoother consists of two components corresponding to forward LMB filtering and backward LMB smoothing, respectively. The former is the standard LMB filter and the latter is proved to be closed under LMB prior. It is also shown that the proposed LMB smoother can improve both the cardinality estimation and the state estimation, and the major computational complexity is linear with the number of targets. Implementation based on the Sequential Monte Carlo method in a representative scenario has demonstrated the effectiveness and computational efficiency of the proposed smoother in comparison to existing approaches.
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Yao, Yu, Junhui Zhao, and Lenan Wu. "Doppler Data Association Scheme for Multi-Target Tracking in an Active Sonar System." Sensors 19, no. 9 (April 29, 2019): 2003. http://dx.doi.org/10.3390/s19092003.

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In many wireless sensors, the target kinematic states include location and Doppler information that can be observed from a time series of range and velocity measurements. In this work, we present a tracking strategy for comprising target velocity components as part of the measurement supplement procedure and evaluate the advantages of the proposed scheme. Data association capability can be considered as the key performance for multi-target tracking in an active sonar system. Then, we proposed an enhanced Doppler data association (DDA) scheme which exploits target range and target velocity components for linear multi-target tracking. If the target velocity measurements are not incorporated into target kinematic state tracking, the linear filter bank for the combination of target velocity components can be implemented. Finally, a significant enhancement in the multi-target tracking capability provided by the proposed DDA scheme with the linear multi-target combined probabilistic data association method is demonstrated in a sonar underwater scenario.
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YANG, Liying. "Solution of Mixed Integer Linear Programming for Multi-target Pursuit Problem." Chinese Journal of Mechanical Engineering 44, no. 10 (2008): 51. http://dx.doi.org/10.3901/jme.2008.10.051.

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Faybusovich, L., and T. Mouktonglang. "Multi-target linear-quadratic control problem and second-order cone programming." Systems & Control Letters 52, no. 1 (May 2004): 17–23. http://dx.doi.org/10.1016/j.sysconle.2003.10.003.

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LI Jing, 李晶, 袁峰 YUAN Feng, and 胡英辉 HU Ying-hui. "Attitude measurement of space objects based on multi-linear CCD and multi-point cooperation target." Optics and Precision Engineering 21, no. 6 (2013): 1635–41. http://dx.doi.org/10.3788/ope.20132106.1635.

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Lee, Chang Joo, Jung Min Pak, Choon Ki Ahn, Kyung Min Min, Peng Shi, and Myo Taeg Lim. "Multi-target FIR tracking algorithm for Markov jump linear systems based on true-target decision-making." Neurocomputing 168 (November 2015): 298–307. http://dx.doi.org/10.1016/j.neucom.2015.05.096.

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Dissertations / Theses on the topic "Linear Multi-Target"

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Xu, Cong. "Multi-objective optimization approaches to efficiency assessment and target setting for bank branches." Thesis, University of Manchester, 2018. https://www.research.manchester.ac.uk/portal/en/theses/multiobjective-optimization-approaches-to-efficiency-assessment-and-target-setting-for-bank-branches(eef70a4a-359d-40ed-9b6c-3eeb98fe477a).html.

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This thesis focuses on combining data envelopment analysis (DEA) and multi-objective linear programming (MOLP) methods to set targets by referencing peers' performances and decision-makers' (DMs) preferences. A large number of past papers have proven the importance of a company having a target; however, obtaining a feasible but challenging target has always been a difficult topic for companies. Since DEA was proposed in 1978, it has become one of the most popular performance assessment tools. The performance possibility set and efficient frontier established by DEA provide solid and scientific reference information for managers to evaluate an individual's efficiency. Based on the successful experience of DEA in performance assessment, many scholars have mentioned that DEA can be used to set appropriate targets as well; however, traditional DEA models do not include DMs' preference information that is crucial to a target-setting process. Therefore, several MOLP methods have been introduced to include DMs' preferences in the target-setting process based on the DEA efficient frontier and performance possibility set. The trade-off-based method is one of the most popular interactive methods that have been incorporated with DEA. However, there are several gaps in the current research: (1) the trade-off-based method could take so many interactions that no DMs could finish the interactive process; (2) DMs might find it very difficult to provide the preference information required by MOLP models; and (3) DMs cannot have an intuitive view in terms of the efficient frontier. Regarding the gaps above, this thesis proposes three new trade-off-based interactive target-setting models based on the DEA performance possibility set and efficient frontier to improve DMs' experience when setting targets. The three models can work independently or can be combined during the decision-making process. The piecewise linear model uses a piecewise linear assumption to simulate DMs' real utility function. It gradually narrows down the region that could contain DMs' most-preferred solution (MPS) until it reaches an acceptable range. This model could help DMs who have limited time for interaction but want to have a global view of the entire efficient frontier. This model has also been proven very helpful when DMs are not sensitive to close efficient solutions. The prioritized trade-off model provides a new way for a DM to know about the efficient frontier, which allows the DM to explore the efficient frontier following the preferred direction with a series of trade-off tables and trade-off figures as visual aids. The stepwise trade-off model focuses on situations where the number of objectives (outputs/inputs for the DEA model) is quite large and DMs cannot provide all indifference trade-offs between all the objectives simultaneously. To release the DMs' burden, the stepwise model starts from two objectives and gradually includes new objectives in the decision-making process, with the assumption that the indifference trade-offs between previous objectives are fixed, until all objectives are included. All three models have been validated through numerical examples and case studies of a Chinese state-owned bank to help DMs to explore their MPS in the DEA production possibility set.
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Arthofer, Christoph. "Multi-atlas segmentation using clustering, local non-linear manifold embeddings and target-specific templates." Thesis, University of Nottingham, 2018. http://eprints.nottingham.ac.uk/50070/.

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Multi-atlas segmentation (MAS) has become an established technique for the automated delineation of anatomical structures. The often manually annotated labels from each of multiple pre-segmented images (atlases) are typically transferred to a target through the spatial mapping of corresponding structures of interest. The mapping can be estimated by pairwise registration between each atlas and the target or by creating an intermediate population template for spatial normalisation of atlases and targets. The former is done at runtime which is computationally expensive but provides high accuracy. In the latter approach the template can be constructed from the atlases offline requiring only one registration to the target at runtime. Although this is computationally more efficient, the composition of deformation fields can lead to decreased accuracy. Our goal was to develop a MAS method which was both efficient and accurate. In our approach we create a target-specific template (TST) which has a high similarity to the target and serves as intermediate step to increase registration accuracy. The TST is constructed from the atlas images that are most similar to the target. These images are determined in low-dimensional manifold spaces on the basis of deformation fields in local regions of interest. We also introduce a clustering approach to divide atlas labels into meaningful sub-regions of interest and increase local specificity for TST construction and label fusion. Our approach was tested on a variety of MR brain datasets and applied to an in-house dataset. We achieve state-of-the-art accuracy while being computationally much more efficient than competing methods. This efficiency opens the door to the use of larger sets of atlases which could lead to further improvement in segmentation accuracy.
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Korkmaz, Yusuf. "Tracking Of Multiple Ground Targets In Clutter With Interacting Multiple Model Estimator." Master's thesis, METU, 2013. http://etd.lib.metu.edu.tr/upload/12615727/index.pdf.

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In this thesis study, single target tracking algorithms including IMM-PDA and IMM-IPDA algorithms
Optimal approaches in multitarget tracking including IMM-JPDA, IMM-IJPDA and IMM-JIPDA algorithms and an example of Linear Multi-target approaches in multitarget tracking including IMM-LMIPDA algorithm have been studied and implemented in MATLAB for comparison. Simulations were carried out in various realistic test scenarios including single target tracking, tracking of multiple targets moving in convoy fashion, two targets merging in a junction, two targets merging-departing in junctions and multitarget tracking under isolated tracks situations. RMSE performance, track loss and computational load evaluations were done for these algorithms under the test scenarios dealing with these situations. Benchmarkings are presented relying on these outcomes.
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Woodbury, Nathan Scott. "Representation and Reconstruction of Linear, Time-Invariant Networks." BYU ScholarsArchive, 2019. https://scholarsarchive.byu.edu/etd/7402.

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Network reconstruction is the process of recovering a unique structured representation of some dynamic system using input-output data and some additional knowledge about the structure of the system. Many network reconstruction algorithms have been proposed in recent years, most dealing with the reconstruction of strictly proper networks (i.e., networks that require delays in all dynamics between measured variables). However, no reconstruction technique presently exists capable of recovering both the structure and dynamics of networks where links are proper (delays in dynamics are not required) and not necessarily strictly proper.The ultimate objective of this dissertation is to develop algorithms capable of reconstructing proper networks, and this objective will be addressed in three parts. The first part lays the foundation for the theory of mathematical representations of proper networks, including an exposition on when such networks are well-posed (i.e., physically realizable). The second part studies the notions of abstractions of a network, which are other networks that preserve certain properties of the original network but contain less structural information. As such, abstractions require less a priori information to reconstruct from data than the original network, which allows previously-unsolvable problems to become solvable. The third part addresses our original objective and presents reconstruction algorithms to recover proper networks in both the time domain and in the frequency domain.
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Karvir, Hrishikesh. "Design and Validation of a Sensor Integration and Feature Fusion Test-Bed for Image-Based Pattern Recognition Applications." Wright State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=wright1291753291.

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Pace, Michele. "Stochastic models and methods for multi-object tracking." Phd thesis, Université Sciences et Technologies - Bordeaux I, 2011. http://tel.archives-ouvertes.fr/tel-00651396.

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La poursuite multi-cibles a pour objet le suivi d'un ensemble de cibles mobiles à partir de données obtenues séquentiellement. Ce problème est particulièrement complexe du fait du nombre inconnu et variable de cibles, de la présence de bruit de mesure, de fausses alarmes, d'incertitude de détection et d'incertitude dans l'association de données. Les filtres PHD (Probability Hypothesis Density) constituent une nouvelle gamme de filtres adaptés à cette problématique. Ces techniques se distinguent des méthodes classiques (MHT, JPDAF, particulaire) par la modélisation de l'ensemble des cibles comme un ensemble fini aléatoire et par l'utilisation des moments de sa densité de probabilité. Dans la première partie, on s'intéresse principalement à la problématique de l'application des filtres PHD pour le filtrage multi-cibles maritime et aérien dans des scénarios réalistes et à l'étude des propriétés numériques de ces algorithmes. Dans la seconde partie, nous nous intéressons à l'étude théorique des processus de branchement liés aux équations du filtrage multi-cibles avec l'analyse des propriétés de stabilité et le comportement en temps long des semi-groupes d'intensités de branchements spatiaux. Ensuite, nous analysons les propriétés de stabilité exponentielle d'une classe d'équations à valeurs mesures que l'on rencontre dans le filtrage non-linéaire multi-cibles. Cette analyse s'applique notamment aux méthodes de type Monte Carlo séquentielles et aux algorithmes particulaires dans le cadre des filtres de Bernoulli et des filtres PHD.
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Vestin, Albin, and Gustav Strandberg. "Evaluation of Target Tracking Using Multiple Sensors and Non-Causal Algorithms." Thesis, Linköpings universitet, Reglerteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-160020.

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Today, the main research field for the automotive industry is to find solutions for active safety. In order to perceive the surrounding environment, tracking nearby traffic objects plays an important role. Validation of the tracking performance is often done in staged traffic scenarios, where additional sensors, mounted on the vehicles, are used to obtain their true positions and velocities. The difficulty of evaluating the tracking performance complicates its development. An alternative approach studied in this thesis, is to record sequences and use non-causal algorithms, such as smoothing, instead of filtering to estimate the true target states. With this method, validation data for online, causal, target tracking algorithms can be obtained for all traffic scenarios without the need of extra sensors. We investigate how non-causal algorithms affects the target tracking performance using multiple sensors and dynamic models of different complexity. This is done to evaluate real-time methods against estimates obtained from non-causal filtering. Two different measurement units, a monocular camera and a LIDAR sensor, and two dynamic models are evaluated and compared using both causal and non-causal methods. The system is tested in two single object scenarios where ground truth is available and in three multi object scenarios without ground truth. Results from the two single object scenarios shows that tracking using only a monocular camera performs poorly since it is unable to measure the distance to objects. Here, a complementary LIDAR sensor improves the tracking performance significantly. The dynamic models are shown to have a small impact on the tracking performance, while the non-causal application gives a distinct improvement when tracking objects at large distances. Since the sequence can be reversed, the non-causal estimates are propagated from more certain states when the target is closer to the ego vehicle. For multiple object tracking, we find that correct associations between measurements and tracks are crucial for improving the tracking performance with non-causal algorithms.
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Van, der Walt Anetta. "Mathematical modelling of blood spatter with optimization and other numerical methods / Anetta van der Walt." Thesis, 2014. http://hdl.handle.net/10394/12266.

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The current methods used by forensic experts to analyse blood spatter neglects the influence of gravitation and drag on the trajectory of the droplet. This research attempts to suggest a more accurate method to determine the trajectory of a blood droplet using multi-target tracking. The multi-target tracking problem can be rewritten as a linear programming problem and solved by means of optimization and numerical methods. A literature survey is presented on relevant articles on blood spatter analysis and multi-target tracking. In contrast to a more advanced approach that assumes a background in probability, mathematical modelling and forensic science, this dissertation aims to give a comprehensive mathematical exposition of particle tracking. The tracking of multi-targets, through multi-target tracking, is investigated. The dynamic programming methods to solve the multi-target tracking are coded in the MATLAB programming language. Results are obtained for different scenarios and option inputs. Research strategies include studying documents, articles, journal entries and books.
MSc (Applied Mathematics), North-West University, Potchefstroom Campus, 2014
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Book chapters on the topic "Linear Multi-Target"

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Tsoumakas, Grigorios, Eleftherios Spyromitros-Xioufis, Aikaterini Vrekou, and Ioannis Vlahavas. "Multi-target Regression via Random Linear Target Combinations." In Machine Learning and Knowledge Discovery in Databases, 225–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-44845-8_15.

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Wang, Jinfeng, Jiayan Tang, Linqi He, Zirong Ji, Zhenyu He, Cheng Yang, Rongliang Huang, and Wenzhong Wang. "Research on Optimization of Multi-target Logistics Distribution Based on Hybrid Integer Linear Programming Model." In Communications in Computer and Information Science, 194–208. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5577-0_15.

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Parra, Arenas, M. Mar, Rodriguez Uria, and M. Victoria. "A Formulation of a Fuzzy Linear Goal Programming Problem with Fuzzy Constraints and Fuzzy Target Values." In Multi-Objective Programming and Goal Programming, 270–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-642-87561-8_18.

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Ali, Jauhar, Mahender Anumalla, Varunseelan Murugaiyan, and Zhikang Li. "Green Super Rice (GSR) Traits: Breeding and Genetics for Multiple Biotic and Abiotic Stress Tolerance in Rice." In Rice Improvement, 59–97. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66530-2_3.

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AbstractThe frequent fluctuations in global climate variability (GCV), decreases in farmland and irrigation water, soil degradation and erosion, and increasing fertilizer costs are the significant factors in declining rice productivity, mainly in Asia and Africa. Under GCV scenarios, it is a challenging task to meet the rice food demand of the growing population. Identifying green traits (tolerance of biotic and abiotic stresses, nutrient-use efficiency, and nutritional grain quality) and stacking them in high-yielding elite genetic backgrounds is one promising approach to increase rice productivity. To this end, the Green Super Rice (GSR) breeding strategy helps to pool multi-stress-tolerance traits by stringent selection processes and to develop superior GSR cultivars within a short span of 4–5 years. In the crossing and selection process of GSR breeding, selective introgression lines (SILs) derived from sets of early backcross BC1F2 bulk populations through both target traits and non-target traits were selected. Genotyping of SILs with high-density SNP markers leads to the identification of a large number of SNP markers linked with the target green traits. The identified SILs with superior trait combinations were used for designed QTL pyramiding to combine different target green traits. The GSR breeding strategy also focused on nutrient- and water-use efficiency besides environment-friendly green features primarily to increase grain yield and income returns for resource-poor farmers. In this chapter, we have highlighted the GSR breeding strategy and QTL introgression of green traits in rice. This breeding strategy has successfully dissected many complex traits and also released several multi-stress-tolerant varieties with high grain yield and productivity in the target regions of Asia and Africa.
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Zhou, Han, Zeyu Sun, Sheriff Sadiqbatcha, and Sheldon X. D. Tan. "EM Lifetime Constrained Optimization for Multi-Segment Power Grid Networks." In Dependable Embedded Systems, 365–83. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-52017-5_15.

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AbstractThis chapter provides techniques for power grid network sizing while considering electromigration reliability. Starting with power grid network and electromigration (EM) fundamentals. Specifically the concerns here are EM immortality and aging effects used as EM constraints when formulating the optimization problems. The chapter first shows that the new power/ground (P/G) optimization problem, subject to the voltage IR drop and new EM constraints, can still be formulated as an efficient sequence of linear programming (SLP) problem, where the optimization is carried out in two linear programming phases in each iteration. The new optimization will ensure that none of the wires fails if all the constraints are satisfied. However, requiring all the wires to be EM immortal can be over-constrained. To mitigate this problem, the improvement is to consider the aging effects of interconnect wires in P/G networks. The idea is to allow some short-lifetime wires to fail and optimize the rest of the wires while considering the additional resistance caused by the failed wire segments. In this way, the resulting P/G networks can be optimized such that the target lifetime of the whole P/G networks can be ensured and will become more robust and aging-aware over the expected lifetime of the chip.
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Amitab, Khwairakpam, Debdatta Kandar, and Arnab K. Maji. "Speckle Noise Filtering Using Back-Propagation Multi-Layer Perceptron Network in Synthetic Aperture Radar Image." In Research Advances in the Integration of Big Data and Smart Computing, 280–301. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-8737-0.ch016.

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Synthetic Aperture Radar (SAR) are imaging Radar, it uses electromagnetic radiation to illuminate the scanned surface and produce high resolution images in all-weather condition, day and night. Interference of signals causes noise and degrades the quality of the image, it causes serious difficulty in analyzing the images. Speckle is multiplicative noise that inherently exist in SAR images. Artificial Neural Network (ANN) have the capability of learning and is gaining popularity in SAR image processing. Multi-Layer Perceptron (MLP) is a feed forward artificial neural network model that consists of an input layer, several hidden layers, and an output layer. We have simulated MLP with two hidden layer in Matlab. Speckle noises were added to the target SAR image and applied MLP for speckle noise reduction. It is found that speckle noise in SAR images can be reduced by using MLP. We have considered Log-sigmoid, Tan-Sigmoid and Linear Transfer Function for the hidden layers. The MLP network are trained using Gradient descent with momentum back propagation, Resilient back propagation and Levenberg-Marquardt back propagation and comparatively evaluated the performance.
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Amitab, Khwairakpam, Debdatta Kandar, and Arnab K. Maji. "Speckle Noise Filtering Using Back-Propagation Multi-Layer Perceptron Network in Synthetic Aperture Radar Image." In Deep Learning and Neural Networks, 489–510. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-0414-7.ch028.

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Synthetic Aperture Radar (SAR) are imaging Radar, it uses electromagnetic radiation to illuminate the scanned surface and produce high resolution images in all-weather condition, day and night. Interference of signals causes noise and degrades the quality of the image, it causes serious difficulty in analyzing the images. Speckle is multiplicative noise that inherently exist in SAR images. Artificial Neural Network (ANN) have the capability of learning and is gaining popularity in SAR image processing. Multi-Layer Perceptron (MLP) is a feed forward artificial neural network model that consists of an input layer, several hidden layers, and an output layer. We have simulated MLP with two hidden layer in Matlab. Speckle noises were added to the target SAR image and applied MLP for speckle noise reduction. It is found that speckle noise in SAR images can be reduced by using MLP. We have considered Log-sigmoid, Tan-Sigmoid and Linear Transfer Function for the hidden layers. The MLP network are trained using Gradient descent with momentum back propagation, Resilient back propagation and Levenberg-Marquardt back propagation and comparatively evaluated the performance.
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Saranya N. and Saravana Selvam. "A Detailed Study on Classification Algorithms in Big Data." In Big Data Analytics for Sustainable Computing, 30–46. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-5225-9750-6.ch002.

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After an era of managing data collection difficulties, these days the issue has turned into the problem of how to process these vast amounts of information. Scientists, as well as researchers, think that today, probably the most essential topic in computing science is Big Data. Big Data is used to clarify the huge volume of data that could exist in any structure. This makes it difficult for standard controlling approaches for mining the best possible data through such large data sets. Classification in Big Data is a procedure of summing up data sets dependent on various examples. There are distinctive classification frameworks which help us to classify data collections. A few methods that discussed in the chapter are Multi-Layer Perception Linear Regression, C4.5, CART, J48, SVM, ID3, Random Forest, and KNN. The target of this chapter is to provide a comprehensive evaluation of classification methods that are in effect commonly utilized.
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K. Nairy, Rajesha, Nagesh N. Bhat, K. B. Anjaria, Usha Yadav, Rajesh Chaurasia, Kapil Shirsath, Utkarsha Desai, S. K. Gupta, B. K. Sapra, and Narayana Yerol. "Relative Biological Effectiveness Studies Using 3 MeV Proton Beam from Folded Tandem Ion Accelerator: An Experimental and Theoretical Approach." In Recent Techniques and Applications in Ionizing Radiation Research. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.94243.

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Proton being the easiest light ion to accelerate and achieve desired beam profile, has been pursued as a popular particulate radiation for therapy applications. In the present study, Saccharomyces cerevisiae D7 strain was used to estimate the RBE values of the 3 MeV proton beam, and an attempt was made to derive mathematical formula for calculating RBE value with respect to the dose. Dosimetry studies were carried out using Fricke dosimetry and Semiconductor Surface Barrier detector to calibrate the absorbed doses of Gamma chamber-1200 and Folded Tandem Ion Accelerator respectively. Gold standard cell survival assay and gene conversion assay were used to compare gamma and proton radiation induced cell death and genetic endpoint. Multi target single hit model was used to derive mathematical formula for RBE estimation. The results show a linear survival-dose response after proton radiation and sigmoid survival-dose response after gamma radiation treatment. The calculated RBE value from the survival and gene conversion studies was 1.60 and 3.93, respectively. The derived mathematical formula is very useful in calculating RBE value, which varies from 3.61 to 1.80 with increasing dose. The estimated RBE value from the mathematical formula is comparable with the experimental values. With the help of the present mathematical formulation, RBE value at any dose can be calculated in the exponential and sigmoidal regions of the survival curve without actually extending the experiment in that dose region, which is not possible using conventional methods.
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Silvana de Rosa, Annamaria, Elena Bocci, and Laura Dryjanska. "Rapid Changes in Approaching First-Time Destination Historical Cities." In Encyclopedia of Organizational Knowledge, Administration, and Technology, 1709–22. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-3473-1.ch117.

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Within the theoretical framework of social representations this chapter features the web-based multi-faced sources of information about three European capitals: London, Madrid, and Warsaw. In line with the “modelling approach to social representations”, the research verifies a set of three hypotheses concerning each considered web-based media source (a: institutional municipal websites; b: social networks; c: Google Earth) and its relationship with more traditional forms of communication. The communicative capacity of the municipal websites and the manner of creating virtual itineraries by Google Earth are related to the overall self-rated importance of sources of information about cities; while exchanges about the same target cities through social networks reflect the interactive nature of interpersonal communication. The results from web-based media studies will be also compared with those based on the field study, involving 420 first-time visitors from France, Germany, Italy, Poland, Spain, UK, and USA, contacted before and after their first-time visit.
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Conference papers on the topic "Linear Multi-Target"

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Musicki, D., and R. Evans. "Track decoupling: linear joint IPDA (LJIPDA) and multi-target linear IPDA (MLIPDA)." In Information, Decision and Control. IEEE, 2002. http://dx.doi.org/10.1109/idc.2002.995427.

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Kim, Sijong, and Myung Jin Chung. "Online multi-target tracking using non-linear motion estimation." In 2014 11th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI). IEEE, 2014. http://dx.doi.org/10.1109/urai.2014.7057490.

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McLaughlin, Niall, Jesus Martinez Del Rincon, and Paul Miller. "Enhancing Linear Programming with Motion Modeling for Multi-target Tracking." In 2015 IEEE Winter Conference on Applications of Computer Vision (WACV). IEEE, 2015. http://dx.doi.org/10.1109/wacv.2015.17.

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Memon, Sufyan Ali. "Smoothing Data Association for Linear Multi-target Tracking in Clutter." In 2021 36th International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC). IEEE, 2021. http://dx.doi.org/10.1109/itc-cscc52171.2021.9501486.

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Hunde, Andinet, and Beshah Ayalew. "Linear Multi-Target Integrated Probabilistic Data Association Filter With Automatic Track Management for Autonomous Vehicles." In ASME 2018 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/dscc2018-8930.

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Target tracking in public traffic calls for a tracking system with automated track initiation and termination facilities in a randomly evolving driving environment. In addition, the key problem of data association needs to be handled effectively considering the limitations in the computational resources onboard an autonomous car. In this paper, we discuss a multi-target tracking system that addresses target birth/initiation and death/termination processes with automatic track management feature. The tracking system is based on Linear Multi-target Integrated Probabilistic Data Association Filter (LMIPDAF), which is adapted to specifically include algorithms that handle track initiation and termination, clutter density estimation and track management. The performance of the proposed tracking algorithm is compared to other single and multi-target tracking schemes and is shown to have acceptable tracking error. It is further illustrated through multiple traffic simulations that the computational requirement of the tracking algorithm is less than that of optimal multi-target tracking algorithms that explicitly address data association uncertainties.
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Vo, Ba-tuong, Ba-ngu Vo, and Antonio Cantoni. "The Cardinalized Probability Hypothesis Density Filter for Linear Gaussian Multi-Target Models." In 2006 40th Annual Conference on Information Sciences and Systems. IEEE, 2006. http://dx.doi.org/10.1109/ciss.2006.286554.

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Zhang, Qian, Yifan Xie, and Taek Lyul Song. "Distributed multi-target tracking in clutter for passive linear array sonar systems." In 2017 20th International Conference on Information Fusion (Fusion). IEEE, 2017. http://dx.doi.org/10.23919/icif.2017.8009687.

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Davey, Samuel J., and Brian Cheung. "A Linear Complexity Approximate Method for Multi-Target Particle Filter Track before Detect." In 2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA). IEEE, 2015. http://dx.doi.org/10.1109/dicta.2015.7371215.

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Bo Yang and R. Nevatia. "Multi-target tracking by online learning of non-linear motion patterns and robust appearance models." In 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2012. http://dx.doi.org/10.1109/cvpr.2012.6247892.

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Campbell, Mark, and Daniel E. Clark. "Joint stereo camera calibration and multi-target tracking using the linear-complexity factorial cumulant filter." In 2019 Sensor Data Fusion: Trends, Solutions, Applications (SDF). IEEE, 2019. http://dx.doi.org/10.1109/sdf.2019.8916653.

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Reports on the topic "Linear Multi-Target"

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Jorgensen, Frieda, Andre Charlett, Craig Swift, Anais Painset, and Nicolae Corcionivoschi. A survey of the levels of Campylobacter spp. contamination and prevalence of selected antimicrobial resistance determinants in fresh whole UK-produced chilled chickens at retail sale (non-major retailers). Food Standards Agency, June 2021. http://dx.doi.org/10.46756/sci.fsa.xls618.

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Campylobacter spp. are the most common bacterial cause of foodborne illness in the UK, with chicken considered to be the most important vehicle for this organism. The UK Food Standards Agency (FSA) agreed with industry to reduce Campylobacter spp. contamination in raw chicken and issued a target to reduce the prevalence of the most contaminated chickens (those with more than 1000 cfu per g chicken neck skin) to below 10 % at the end of the slaughter process, initially by 2016. To help monitor progress, a series of UK-wide surveys were undertaken to determine the levels of Campylobacter spp. on whole UK-produced, fresh chicken at retail sale in the UK. The data obtained for the first four years was reported in FSA projects FS241044 (2014/15) and FS102121 (2015 to 2018). The FSA has indicated that the retail proxy target for the percentage of highly contaminated raw whole retail chickens should be less than 7% and while continued monitoring has demonstrated a sustained decline for chickens from major retailer stores, chicken on sale in other stores have yet to meet this target. This report presents results from testing chickens from non-major retailer stores (only) in a fifth survey year from 2018 to 2019. In line with previous practise, samples were collected from stores distributed throughout the UK (in proportion to the population size of each country). Testing was performed by two laboratories - a Public Health England (PHE) laboratory or the Agri-Food & Biosciences Institute (AFBI), Belfast. Enumeration of Campylobacter spp. was performed using the ISO 10272-2 standard enumeration method applied with a detection limit of 10 colony forming units (cfu) per gram (g) of neck skin. Antimicrobial resistance (AMR) to selected antimicrobials in accordance with those advised in the EU harmonised monitoring protocol was predicted from genome sequence data in Campylobacter jejuni and Campylobacter coli isolates The percentage (10.8%) of fresh, whole chicken at retail sale in stores of smaller chains (for example, Iceland, McColl’s, Budgens, Nisa, Costcutter, One Stop), independents and butchers (collectively referred to as non-major retailer stores in this report) in the UK that are highly contaminated (at more than 1000 cfu per g) with Campylobacter spp. has decreased since the previous survey year but is still higher than that found in samples from major retailers. 8 whole fresh raw chickens from non-major retailer stores were collected from August 2018 to July 2019 (n = 1009). Campylobacter spp. were detected in 55.8% of the chicken skin samples obtained from non-major retailer shops, and 10.8% of the samples had counts above 1000 cfu per g chicken skin. Comparison among production plant approval codes showed significant differences of the percentages of chicken samples with more than 1000 cfu per g, ranging from 0% to 28.1%. The percentage of samples with more than 1000 cfu of Campylobacter spp. per g was significantly higher in the period May, June and July than in the period November to April. The percentage of highly contaminated samples was significantly higher for samples taken from larger compared to smaller chickens. There was no statistical difference in the percentage of highly contaminated samples between those obtained from chicken reared with access to range (for example, free-range and organic birds) and those reared under standard regime (for example, no access to range) but the small sample size for organic and to a lesser extent free-range chickens, may have limited the ability to detect important differences should they exist. Campylobacter species was determined for isolates from 93.4% of the positive samples. C. jejuni was isolated from the majority (72.6%) of samples while C. coli was identified in 22.1% of samples. A combination of both species was found in 5.3% of samples. C. coli was more frequently isolated from samples obtained from chicken reared with access to range in comparison to those reared as standard birds. C. jejuni was less prevalent during the summer months of June, July and August compared to the remaining months of the year. Resistance to ciprofloxacin (fluoroquinolone), erythromycin (macrolide), tetracycline, (tetracyclines), gentamicin and streptomycin (aminoglycosides) was predicted from WGS data by the detection of known antimicrobial resistance determinants. Resistance to ciprofloxacin was detected in 185 (51.7%) isolates of C. jejuni and 49 (42.1%) isolates of C. coli; while 220 (61.1%) isolates of C. jejuni and 73 (62.9%) isolates of C. coli isolates were resistant to tetracycline. Three C. coli (2.6%) but none of the C. jejuni isolates harboured 23S mutations predicting reduced susceptibility to erythromycin. Multidrug resistance (MDR), defined as harbouring genetic determinants for resistance to at least three unrelated antimicrobial classes, was found in 10 (8.6%) C. coli isolates but not in any C. jejuni isolates. Co-resistance to ciprofloxacin and erythromycin was predicted in 1.7% of C. coli isolates. 9 Overall, the percentages of isolates with genetic AMR determinants found in this study were similar to those reported in the previous survey year (August 2016 to July 2017) where testing was based on phenotypic break-point testing. Multi-drug resistance was similar to that found in the previous survey years. It is recommended that trends in AMR in Campylobacter spp. isolates from retail chickens continue to be monitored to realise any increasing resistance of concern, particulary to erythromycin (macrolide). Considering that the percentage of fresh, whole chicken from non-major retailer stores in the UK that are highly contaminated (at more than 1000 cfu per g) with Campylobacter spp. continues to be above that in samples from major retailers more action including consideration of interventions such as improved biosecurity and slaughterhouse measures is needed to achieve better control of Campylobacter spp. for this section of the industry. The FSA has indicated that the retail proxy target for the percentage of highly contaminated retail chickens should be less than 7% and while continued monitoring has demonstrated a sustained decline for chickens from major retailer stores, chicken on sale in other stores have yet to meet this target.
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