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Academic literature on the topic 'Variable Order Markov Model'

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Published: 9 March 2023

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Journal articles on the topic "Variable Order Markov Model"

Shirgave, Suresh, Prakash Kulkarni, and José Borges. "Semantically Enriched Variable Length Markov Chain Model for Analysis of User Web Navigation Sessions." International Journal of Information Technology & Decision Making 13, no. 04 (July 2014): 721–53. http://dx.doi.org/10.1142/s0219622014500643.

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The rapid growth of the World Wide Web has resulted in intricate Web sites, demanding enhanced user skills to find the required information and more sophisticated tools that are able to generate apt recommendations. Markov Chains have been widely used to generate next-page recommendations; however, accuracy of such models is limited. Herein, we propose the novel Semantic Variable Length Markov Chain Model (SVLMC) that combines the fields of Web Usage Mining and Semantic Web by enriching the Markov transition probability matrix with rich semantic information extracted from Web pages. We show that the method is able to enhance the prediction accuracy relatively to usage-based higher order Markov models and to semantic higher order Markov models based on ontology of concepts. In addition, the proposed model is able to handle the problem of ambiguous predictions. An extensive experimental evaluation was conducted on two real-world data sets and on one partially generated data set. The results show that the proposed model is able to achieve 15–20% better accuracy than the usage-based Markov model, 8–15% better than the semantic ontology Markov model and 7–12% better than semantic-pruned Selective Markov Model. In summary, the SVLMC is the first work proposing the integration of a rich set of detailed semantic information into higher order Web usage Markov models and experimental results reveal that the inclusion of detailed semantic data enhances the prediction ability of Markov models.

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Begleiter, R., R. El-Yaniv, and G. Yona. "On Prediction Using Variable Order Markov Models." Journal of Artificial Intelligence Research 22 (December 1, 2004): 385–421. http://dx.doi.org/10.1613/jair.1491.

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This paper is concerned with algorithms for prediction of discrete sequences over a finite alphabet, using variable order Markov models. The class of such algorithms is large and in principle includes any lossless compression algorithm. We focus on six prominent prediction algorithms, including Context Tree Weighting (CTW), Prediction by Partial Match (PPM) and Probabilistic Suffix Trees (PSTs). We discuss the properties of these algorithms and compare their performance using real life sequences from three domains: proteins, English text and music pieces. The comparison is made with respect to prediction quality as measured by the average log-loss. We also compare classification algorithms based on these predictors with respect to a number of large protein classification tasks. Our results indicate that a ``decomposed'' CTW (a variant of the CTW algorithm) and PPM outperform all other algorithms in sequence prediction tasks. Somewhat surprisingly, a different algorithm, which is a modification of the Lempel-Ziv compression algorithm, significantly outperforms all algorithms on the protein classification problems.

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Tengke Xiong, Shengrui Wang, Qingshan Jiang, and Joshua Zhexue Huang. "A Novel Variable-order Markov Model for Clustering Categorical Sequences." IEEE Transactions on Knowledge and Data Engineering 26, no. 10 (October 2014): 2339–53. http://dx.doi.org/10.1109/tkde.2013.104.

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Cunial, Fabio, Jarno Alanko, and Djamal Belazzougui. "A framework for space-efficient variable-order Markov models." Bioinformatics 35, no. 22 (April 20, 2019): 4607–16. http://dx.doi.org/10.1093/bioinformatics/btz268.

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Abstract Motivation Markov models with contexts of variable length are widely used in bioinformatics for representing sets of sequences with similar biological properties. When models contain many long contexts, existing implementations are either unable to handle genome-scale training datasets within typical memory budgets, or they are optimized for specific model variants and are thus inflexible. Results We provide practical, versatile representations of variable-order Markov models and of interpolated Markov models, that support a large number of context-selection criteria, scoring functions, probability smoothing methods, and interpolations, and that take up to four times less space than previous implementations based on the suffix array, regardless of the number and length of contexts, and up to ten times less space than previous trie-based representations, or more, while matching the size of related, state-of-the-art data structures from Natural Language Processing. We describe how to further compress our indexes to a quantity related to the redundancy of the training data, saving up to 90% of their space on very repetitive datasets, and making them become up to 60 times smaller than previous implementations based on the suffix array. Finally, we show how to exploit constraints on the length and frequency of contexts to further shrink our compressed indexes to half of their size or more, achieving data structures that are a hundred times smaller than previous implementations based on the suffix array, or more. This allows variable-order Markov models to be used with bigger datasets and with longer contexts on the same hardware, thus possibly enabling new applications. Availability and implementation https://github.com/jnalanko/VOMM Supplementary information Supplementary data are available at Bioinformatics online.

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POSCH, STEFAN, JAN GRAU, ANDRE GOHR, IRAD BEN-GAL, ALEXANDER E. KEL, and IVO GROSSE. "RECOGNITION OF CIS-REGULATORY ELEMENTS WITH VOMBAT." Journal of Bioinformatics and Computational Biology 05, no. 02b (April 2007): 561–77. http://dx.doi.org/10.1142/s0219720007002886.

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Variable order Markov models and variable order Bayesian trees have been proposed for the recognition of cis-regulatory elements, and it has been demonstrated that they outperform traditional models such as position weight matrices, Markov models, and Bayesian trees for the recognition of binding sites in prokaryotes. Here, we study to which degree variable order models can improve the recognition of eukaryotic cis-regulatory elements. We find that variable order models can improve the recognition of binding sites of all the studied transcription factors. To ease a systematic evaluation of different model combinations based on problem-specific data sets and allow genomic scans of cis-regulatory elements based on fixed and variable order Markov models and Bayesian trees, we provide the VOMBATserver to the public community.

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Xiao Li, Yuhao Wang, and Yuan Liu. "A Channel Cognitive Method for Local Fading Characteristics using Variable-Order Markov Model." Journal of Communications and Information Sciences 1, no. 2 (2011): 1–12. http://dx.doi.org/10.4156/jcis.vol1.issue2.1.

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Saadani, A., P. Gelpi, and P. Tortelier. "A Variable-Order Markov-Chain-Based Model for Rayleigh Fading and Rake Receiver." IEEE Signal Processing Letters 11, no. 3 (March 2004): 356–58. http://dx.doi.org/10.1109/lsp.2003.822915.

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Qi, Zhang, Wen Guang, Chen Zhixin, Zhou Qin, Xiang Guoqi, Yang Guangchun, and Zhang Xuegang. "Contact stress reliability analysis based on first order second moment for variable hyperbolic circular arc gear." Advances in Mechanical Engineering 14, no. 7 (July 2022): 168781322211112. http://dx.doi.org/10.1177/16878132221111210.

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Aiming at the contact strength reliability of variable hyperbolic circular arc gear, a reliability analysis method for contact strength of variable hyperbolic circular arc gear based on Kriging model and advanced first-order and second-moment algorithm is proposed. Kriging model was used to establish the limit state equation of the contact stress reliability analysis of variable hyperbolic circular arc gear, and the advanced first-order second-moment method was used to analyze the contact stress reliability of variable hyperbolic circular arc gear based on the limit state equation of the contact stress. In order to verify the effectiveness of the proposed algorithm, a Markov Chain Monte Carlo reliability analysis method based on Important Sampling was proposed. Markov Chain and Important Sampling were exploited to improve the accuracy of contact reliability analysis based on Monte Carlo method for variable hyperbolic circular arc gear. The comparison between the analysis results of Markov Chain Monte Carlo with Important Sampling method and first order second moment shows that it is feasible to analyze the reliability of variable hyperbolic circular arc gear by first-order second-moment method.

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Melikov, A. Z., L. A. Ponomarenko, and S. A. Bagirova. "Markov Models of Queueing–Inventory Systems with Variable Order Size." Cybernetics and Systems Analysis 53, no. 3 (May 2017): 373–86. http://dx.doi.org/10.1007/s10559-017-9937-3.

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Kohli, Amit Kumar, Amrita Rai, and Meher Krishna Patel. "Variable Forgetting Factor LS Algorithm for Polynomial Channel Model." ISRN Signal Processing 2011 (December 30, 2011): 1–4. http://dx.doi.org/10.5402/2011/915259.

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Variable forgetting factor (VFF) least squares (LS) algorithm for polynomial channel paradigm is presented for improved tracking performance under nonstationary environment. The main focus is on updating VFF when each time-varying fading channel is considered to be a first-order Markov process. In addition to efficient tracking under frequency-selective fading channels, the incorporation of proposed numeric variable forgetting factor (NVFF) in LS algorithm reduces the computational complexity.

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Dissertations / Theses on the topic "Variable Order Markov Model"

Zippo, A. G. "NEURONAL ENSEMBLE MODELING AND ANALYSIS WITH VARIABLE ORDER MARKOV MODELS." Doctoral thesis, Università degli Studi di Milano, 2010. http://hdl.handle.net/2434/150077.

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Neuronal cells (neurons) mainly transmit signals by action potentials or spikes. Neuronal electrical activity is recorded from experimental animals by microelectrodes placed in specific brain areas. These electrochemical fast phenomena occur as all-or-none events and can be analyzed as boolean sequences. Following this approach, several computational analyses reported most variable neuronal behaviors expressed through a large variety of firing patterns. These patterns have been modeled as symbolic strings with a number of different techniques. As a rule, single neurons or neuronal ensembles are manageable as unknown discrete symbol sources S = <Σ, P> where Σ is the source alphabet and P is the unknown symbol probability distribution. Within the hierarchy of Markov Models (MMs), Markov Chains and Hidden MMs have been profusely employed to model neuronal recording data. However, due to the highly complex dynamic profiles of single neuron (SN) and neuronal ensemble (NE) firing patterns, those models failed to capture biologically relevant dynamical features. K-Order MMs could overcome these failures, but their time and space computational complexity turned them into unfeasibility. Variable Order MMs (VOMMs) meet with these restrictions confining modeling to the effective symbols of a given sequence up to a D maximum order. Formally a VOMM is characterized by a couple s, D where s ∈ Σ^∗ is the training sequence and the returned P is an estimation of P from source S. Given an arbitrary finite sequence s ∈ Σ^∗ , delivered by a generic source S, a VOMM builds a structure for S. Once a structure has been captured (or learnt) it may undergo tasks like prediction or compression or, again, analysis. Thus, a lossless compression algorithm originated from a VOMM can perform prediction tasks and every prediction algorithm can perform compression tasks. Statistically Based Compression Algorithms (SBCAs) build a prefix tree to estimate the symbol probability by combining conditional probability of a symbol with a chain rule, given d previous symbols (d ≤ D). In particular, just on the track of previously discussed issues, I took into consideration three SBCAs: Prediction by Partial Matching (PPM), Context-Tree Weighting (CTW) and Probabilistic Suffix Tree (PST). Prediction capability of these algorithms can be exploited in at least two ways: i) to draw a similarity function between experiments and ii) to analyze the changes of stationary phase of specific experiment dynamics from SN or NE datasets. The predictive accuracy can be measured by functions like the average log-loss (self-information). The average log-loss function measures the average compression rate of s assuming its P distribution and so the P prediction accuracy. Once the VOMM is trained with a given sequence source A, the average log-loss between the obtained VOMM model and another arbitrary sequence source B approximates their similarity measure μ(A, B). Where the sequences represent whole recording experiments, the VOMMs identify the similarity between different recordings, otherwise, if the sequences represent contiguous recorded experiment subsequences, the VOMMs can detect the switching between stationary phases, through average log-loss peaks. These VOMMs can also measure the information redundancy present in the sequence. This application, as shown in results, is particularly relevant for neurophysiologists and provides significant results when applied to recordings of chronic pain animal models. To confirm, by other estimation paths, the similarity measure between whole recording stages, I chose to introduce a more computationally efficient similarity measure (the Normalized Compression Distance, NCD) based on widely acknowledged faster compressors like gzip, bzip2, lzma and others. The results obtained with these methods come (i) from Ventrobasal Thalamic Nuclei (VB) and Somatosensory Cortex (SSI) in Chronic Pain Animals (CPAs), (ii) from Primary Visual (V1) and (SSI) in rat Cortices and, finally, (iii) from IL human Thalamus Nuclei in patients suffering from states of disordered consciousness like Persistent Vegetative State (PVS) and Minimum Conscious State (MCS).

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Schimert, James. "A high order hidden Markov model /." Thesis, Connect to this title online; UW restricted, 1992. http://hdl.handle.net/1773/8939.

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Xu, Xuechun. "Sequential recommendation for food recipes with Variable Order Markov Chain." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-223567.

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One of the key tasks in the study of the recommendation system is to model the dynamics aspect of a person's preference, i.e. to give sequential recommendations. Markov Chain (MC), which is famous for its capability of learning a transition graph, is the most popular approach to address the task. In previous work, the recommendation system attempts to model the short-term dynamics of the personal preference based on the long-term dynamics, which implies the assumption that the personal preference over a set of items remains same over time. However, in the field of food science, the study of Sensory-Specific Satiety (SSS) shows that the personal preference on food changes along time and previous meals. However, whether such changes follow certain patterns remains unclear. In this paper, a recommendation system is built based on Variable Order Markov Chain (VOMC), which is capable of modeling various lengths of sequential patterns using the suffix tree (ST) search. This recommendation system aims to understand and model the short-term dynamics aspect of the personal preference on food. To evaluate the system, a Food Diary survey is carried to collect users’ meals data over seven days. The results show that this recommendation system can give meaningful recommendations.
En av huvuduppgifterna när det kommer till rekommenderingsplatformar är att modellera kortsidiga dynamiska egenskaper, dvs. användares sekventiella beteenden. Markov Chain (MC), som är mest känd för sin förmåga att lära sig övergångsgrafer, är den mest populära metoden för att ge sig på denna uppgift. I föregående arbeten så har rekommenderingsplatformar ofta tenderat att modellera kortsidig dynamik baserat på långsidig dynamik, t.ex. likheter mellan objekt eller användares relativa preferenser givet olika tillfällen. Att använda den här metoden brukar medföra att användares långsiktiga dynamik, i detta fall personliga smakpreferenser, är alltid densamma. Däremot, så har studien av Sensory-Specific Satiety visat att användares preferenser gällande mat varierar. I detta arbete så undersöks ett rekommenderingssystem som baseras på Variable Order Markov Chain (VOMC) som kan anpassa sig efter den observerade realiseringen genom att använda suffix tree (ST) för att extrahera sekventiella mönster. Detta rekommenderingssystem fokuserar på kortsidig dynamik istället för att kombinera kort- och långsidig dynamik. För att evaluera metoden, en undersökning av vilken mat som konsumeras, under loppet av sju dagar, ges ut för att samla data om vilken mat och i vilken ordning användare konsumerar. I resultaten så visas att det föreslagna rekommenderingsystemet kan ge meningsfulla rekommendationer.

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Schwardt, Ludwig. "Efficient Mixed-Order Hidden Markov Model Inference." Thesis, Link to the online version, 2007. http://hdl.handle.net/10019/709.

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Jindasawat, Jutaporn. "Testing the order of a Markov chain model." Thesis, University of Newcastle Upon Tyne, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.446197.

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Avila, Manuel. "Optimisation de modèles markoviens pour la reconnaissance de l'écrit." Rouen, 1996. http://www.theses.fr/1996ROUES034.

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Cette thèse traite de l'optimisation de modèles markoviens dédiés à la reconnaissance de textes manuscrits, dans le cas particulier d'une application à vocabulaire réduit : la lecture des montants littéraux de chèques. Le premier chapitre décrit brièvement les techniques utilisées pour la reconnaissance de l'écrit. Nous présentons également les descriptions des mots que nous avons utilisées. Le second chapitre présente les modèles de Markov cache. Nous présentons notamment les différents niveaux de représentation du problème de la lecture de l'écrit dans le cas de modélisations markoviennes : les niveaux phrase, mot et lettre. Finalement, nous présentons les algorithmes couramment utilisés pour exploiter des modèles de Markov : les algorithmes de Viterbi et de Baum-welch, avec des variantes que nous avons adaptées à nos besoins. Dans le troisième chapitre, nous traitons du problème d'une optimisation des descriptions des mots. Nous donnons trois méthodes de représentation des mots. Nous présentons ensuite une méthode de recherche de l'ordre optimal d'un processus de Markov basée sur la minimisation de critères d'information de type Akaike soit AIC, BIC etc. Finalement, nous comparons les résultats des trois alphabets pour les ordres de 1 à 3. Ceci nous permet de valider le choix de la description des mots et de l'ordre du modèle de Markov correspondant. Nous réutilisons ces résultats au chapitre 4. Dans ce chapitre, trois approches sont proposées pour la reconnaissance des mots : la première est une approche globale qui par définition ne s'attache pas à l'identification des lettres, la seconde est une approche analytique basée sur une modélisation complètement explicitée, la troisième méthode est une approche pseudo-analytique intermédiaire entre les deux approches précédentes. Elle modélise le mot de manière analytique en utilisant des modèles globaux de lettres. Finalement, les résultats de ces trois méthodes sont ensuite fusionnés : chapitre 5. Ce chapitre traite de l'identification des montants littéraux de chèques. La stratégie développée se décompose en trois parties : validation de la segmentation des mots, identification des mots et reconstitution de la phrase. A chaque partie correspond une modélisation markovienne adaptée.

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Mainguy, Yves. "A robust variable order facet model for image data." Thesis, This resource online, 1991. http://scholar.lib.vt.edu/theses/available/etd-10222009-124949/.

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Engelbrecht, Herman A. "Efficient Decoding of High-order Hidden Markov Models." Thesis, Stellenbosch : University of Stellenbosch, 2007. http://hdl.handle.net/10019.1/1095.

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Thesis (PhD (Electrical and Electronic Engineering))--University of Stellenbosch, 2007.
Most speech recognition and language identification engines are based on hidden Markov models (HMMs). Higher-order HMMs are known to be more powerful than first-order HMMs, but have not been widely used because of their complexity and computational demands. The main objective of this dissertation was to develop a more time-efficient method of decoding high-order HMMs than the standard Viterbi decoding algorithm currently in use. We proposed, implemented and evaluated two decoders based on the Forward-Backward Search (FBS) paradigm, which incorporate information obtained from low-order HMMs. The first decoder is based on time-synchronous Viterbi-beam decoding where we wish to base our state pruning on the complete observation sequence. The second decoder is based on time-asynchronous A* search. The choice of heuristic is critical to the A* search algorithms and a novel, task-independent heuristic function is presented. The experimental results show that both these proposed decoders result in more time-efficient decoding of the fully-connected, high-order HMMs that were investigated. Three significant facts have been uncovered. The first is that conventional forward Viterbi-beam decoding of high-order HMMs is not as computationally expensive as is commonly thought. The second (and somewhat surprising) fact is that backward decoding of conventional, high-order left-context HMMs is significantly more expensive than the conventional forward decoding. By developing the right-context HMM, we showed that the backward decoding of a mathematically equivalent right-context HMM is as expensive as the forward decoding of the left-context HMM. The third fact is that the use of information obtained from low-order HMMs significantly reduces the computational expense of decoding high-order HMMs. The comparison of the two new decoders indicate that the FBS-Viterbi-beam decoder is more time-efficient than the A* decoder. The FBS-Viterbi-beam decoder is not only simpler to implement, it also requires less memory than the A* decoder. We suspect that the broader research community regards the Viterbi-beam algorithm as the most efficient method of decoding HMMs. We hope that the research presented in this dissertation will result in renewed investigation into decoding algorithms that are applicable to high-order HMMs.

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Wang, Chaohui. "Distributed and Higher-Order Graphical Models : towards Segmentation, Tracking, Matching and 3D Model Inference." Phd thesis, Ecole Centrale Paris, 2011. http://tel.archives-ouvertes.fr/tel-00658765.

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This thesis is devoted to the development of graph-based methods that address several of the most fundamental computer vision problems, such as segmentation, tracking, shape matching and 3D model inference. The first contribution of this thesis is a unified, single-shot optimization framework for simultaneous segmentation, depth ordering and multi-object tracking from monocular video sequences using a pairwise Markov Random Field (MRF). This is achieved through a novel 2.5D layered model where object-level and pixel-level representations are seamlessly combined through local constraints. Towards introducing high-level knowledge, such as shape priors, we then studied the problem of non-rigid 3D surface matching. The second contribution of this thesis consists of a higher-order graph matching formulation that encodes various measurements of geometric/appearance similarities and intrinsic deformation errors. As the third contribution of this thesis, higher-order interactions were further considered to build pose-invariant statistical shape priors and were exploited for the development of a novel approach for knowledge-based 3D segmentation in medical imaging which is invariant to the global pose and the initialization of the shape model. The last contribution of this thesis aimed to partially address the influence of camera pose in visual perception. To this end, we introduced a unified paradigm for 3D landmark model inference from monocular 2D images to simultaneously determine both the optimal 3D model and the corresponding 2D projections without explicit estimation of the camera viewpoint, which is also able to deal with misdetections/occlusions

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Crespo, Cuaresma Jesus, and Philipp Piribauer. "Bayesian Variable Selection in Spatial Autoregressive Models." WU Vienna University of Economics and Business, 2015. http://epub.wu.ac.at/4584/1/wp199.pdf.

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This paper compares the performance of Bayesian variable selection approaches for spatial autoregressive models. We present two alternative approaches which can be implemented using Gibbs sampling methods in a straightforward way and allow us to deal with the problem of model uncertainty in spatial autoregressive models in a flexible and computationally efficient way. In a simulation study we show that the variable selection approaches tend to outperform existing Bayesian model averaging techniques both in terms of in-sample predictive performance and computational efficiency. (authors' abstract)
Series: Department of Economics Working Paper Series

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Books on the topic "Variable Order Markov Model"

United States. National Aeronautics and Space Administration., ed. Low-order nonlinear dynamic model of IC engine-variable pitch propeller system for general aviation aircraft. [Washington, D.C.]: National Aeronautics and Space Administration, 1995.

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Koldaev, Viktor. Theoretical and methodological aspects of the use of information technologies in education. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1014651.

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The article summarizes the experience of implementing a personality-oriented approach to the formation of a structural and content model of the educational process at the university. The results of the introduction of information technologies and their services in the field of education are presented, as well as the impact of computerization on the quality of education in the framework of the modern educational paradigm. The priority directions of innovative educational strategies of the university are identified and a graph model of the individual educational route of the student is proposed in order to predict the state of the educational system and adopt optimal learning strategies. Meets the requirements of the federal state educational standards of higher education of the latest generation. For graduate students and university teachers in the design of variable models of training in any areas of training and specialties. It will be useful for advanced training on the problems of innovative educational strategies.

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Gestión de calidad y su impacto en la innovación ecológica del Distrito de Ica, Perú. Editora Acadêmica Periodicojs, 2021. http://dx.doi.org/10.51249/hp01.2021.21.

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The purpose of the study was to evaluate the existing impact between quality management and ecological innovation in the District of Ica, during 2018. The model used is a basic research of correlational and explanatory level, with a cross-sectional and non-experimental design. The sample determination technique was stratified by census type, consisting of 60 collaborators, of which 30 were administrative workers of the Municipality of Ica and the other 30, were administrative workers of the Regional Government of Ica to whom a questionnaire with in order to evaluate each of the study variables. The research concluded with an r2= 043, that there is a direct and positive relationship between quality management and ecological innovation. Likewise, the specific hypotheses could be verified, where the existing relationship between each of the stages of the continuous improvement cycle of the quality management system with respect to ecological innovation was tested, concluding that there is a direct and positive relationship in the stages of Plan, Do, Verify, Act and the ecological innovation variable.

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Li, Quan. Using R for Data Analysis in Social Sciences. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190656218.001.0001.

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This book seeks to teach undergraduate and graduate students in social sciences how to use R to manage, visualize, and analyze data in order to answer substantive questions and replicate published findings. This book distinguishes itself from other introductory R or statistics books in three ways. First, targeting an audience rarely exposed to statistical programming, it adopts a minimalist approach and covers only the most important functions and skills in R that one will need for conducting reproducible research projects. Second, it emphasizes meeting the practical needs of students using R in research projects. Specifically, it teaches students how to import, inspect, and manage data; understand the logic of statistical inference; visualize data and findings via histograms, boxplots, scatterplots, and diagnostic plots; and analyze data using one-sample t-test, difference-of-means test, covariance, correlation, ordinary least squares (OLS) regression, and model assumption diagnostics. Third, it teaches students how to replicate the findings in published journal articles and diagnose model assumption violations. The principle behind this book is to teach students to learn as little R as possible but to do as much reproducible, substance-driven data analysis at the beginner or intermediate level as possible. The minimalist approach dramatically reduces the learning cost but still proves adequate information for meeting the practical research needs of senior undergraduate and beginning graduate students. Having completed this book, students can use R and statistical analysis to answer questions regarding some substantively interesting continuous outcome variable in a cross-sectional design.

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Zydroń, Tymoteusz. Wpływ systemów korzeniowych wybranych gatunków drzew na przyrost wytrzymałości gruntu na ścinanie. Publishing House of the University of Agriculture in Krakow, 2019. http://dx.doi.org/10.15576/978-83-66602-46-5.

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The aim of the paper was to determine the influence of root systems of chosen tree species found in the Polish Flysch Carpathians on the increase of soil shear strength (root cohesion) in terms of slope stability. The paper's goal was achieved through comprehensive tests on root systems of eight relatively common in the Polish Flysch Carpathians tree species. The tests that were carried out included field work, laboratory work and analytical calculations. As part of the field work, the root area ratio (A IA) of the roots was determined using the method of profiling the walls of the trench at a distance of about 1.0 m from the tree trunk. The width of the. trenches was about 1.0 m, and their depth depended on the ground conditions and ranged from 0.6 to 1.0 m below the ground level. After preparing the walls of the trench, the profile was divided into vertical layers with a height of 0.1 m, within which root diameters were measured. Roots with diameters from 1 to 10 mm were taken into consideration in root area ratio calculations in accordance with the generally accepted methodology for this type of tests. These measurements were made in Biegnik (silver fir), Ropica Polska (silver birch, black locust) and Szymbark (silver birch, European beech, European hornbeam, silver fir, sycamore maple, Scots pine, European spruce) located near Gorlice (The Low Beskids) in areas with unplanned forest management. In case of each tested tree species the samples of roots were taken, transported to the laboratory and then saturated with water for at least one day. Before testing the samples were obtained from the water and stretched in a. tensile testing machine in order to determine their tensile strength and flexibility. In general, over 2200 root samples were tested. The results of tests on root area ratio of root systems and their tensile strength were used to determine the value of increase in shear strength of the soils, called root cohesion. To this purpose a classic Wu-Waldron calculation model was used as well as two types of bundle models, the so called static model (Fiber Bundle Model — FIRM, FBM2, FBM3) and the deformation model (Root Bundle Model— RBM1, RBM2, mRBM1) that differ in terms of the assumptions concerning the way the tensile force is distributed to the roots as well as the range of parameters taken into account during calculations. The stability analysis of 8 landslides in forest areas of Cicikowicleie and Wignickie Foothills was a form of verification of relevance of the obtained calculation results. The results of tests on root area ratio in the profile showed that, as expected, the number of roots in the soil profile and their ApIA values are very variable. It was shown that the values of the root area ratio of the tested tree species with a diameter 1-10 ram are a maximum of 0.8% close to the surface of the ground and they decrease along with the depth reaching the values at least one order of magnitude lower than close to the surface at the depth 0.5-1.0 m below the ground level. Average values of the root area ratio within the soil profile were from 0.05 to 0.13% adequately for Scots pine and European beech. The measured values of the root area ratio are relatively low in relation to the values of this parameter given in literature, which is probably connected with great cohesiveness of the soils and the fact that there were a lot of rock fragments in the soil, where the tests were carried out. Calculation results of the Gale-Grigal function indicate that a distribution of roots in the soil profile is similar for the tested species, apart from the silver fir from Bie§nik and European hornbeam. Considering the number of roots, their distribution in the soil profile and the root area ratio it appears that — considering slope stability — the root systems of European beech and black locust are the most optimal, which coincides with tests results given in literature. The results of tensile strength tests showed that the roots of the tested tree species have different tensile strength. The roots of European beech and European hornbeam had high tensile strength, whereas the roots of conifers and silver birch in deciduous trees — low. The analysis of test results also showed that the roots of the studied tree species are characterized by high variability of mechanical properties. The values Of shear strength increase are mainly related to the number and size (diameter) of the roots in the soil profile as well as their tensile strength and pullout resistance, although they can also result from the used calculation method (calculation model). The tests showed that the distribution of roots in the soil and their tensile strength are characterized by large variability, which allows the conclusion that using typical geotechnical calculations, which take into consideration the role of root systems is exposed to a high risk of overestimating their influence on the soil reinforcement. hence, while determining or assuming the increase in shear strength of soil reinforced with roots (root cohesion) for design calculations, a conservative (careful) approach that includes the most unfavourable values of this parameter should be used. Tests showed that the values of shear strength increase of the soil reinforced with roots calculated using Wu-Waldron model in extreme cases are three times higher than the values calculated using bundle models. In general, the most conservative calculation results of the shear strength increase were obtained using deformation bundle models: RBM2 (RBMw) or mRBM1. RBM2 model considers the variability of strength characteristics of soils described by Weibull survival function and in most cases gives the lowest values of the shear strength increase, which usually constitute 50% of the values of shear strength increase determined using classic Wu-Waldron model. Whereas the second model (mRBM1.) considers averaged values of roots strength parameters as well as the possibility that two main mechanism of destruction of a root bundle - rupture and pulling out - can occur at the same. time. The values of shear strength increase calculated using this model were the lowest in case of beech and hornbeam roots, which had high tensile strength. It indicates that in the surface part of the profile (down to 0.2 m below the ground level), primarily in case of deciduous trees, the main mechanism of failure of the root bundle will be pulling out. However, this model requires the knowledge of a much greater number of geometrical parameters of roots and geotechnical parameters of soil, and additionally it is very sensitive to input data. Therefore, it seems practical to use the RBM2 model to assess the influence of roots on the soil shear strength increase, and in order to obtain safe results of calculations in the surface part of the profile, the Weibull shape coefficient equal to 1.0 can be assumed. On the other hand, the Wu-Waldron model can be used for the initial assessment of the shear strength increase of soil reinforced with roots in the situation, where the deformation properties of the root system and its interaction with the soil are not considered, although the values of the shear strength increase calculated using this model should be corrected and reduced by half. Test results indicate that in terms of slope stability the root systems of beech and hornbeam have the most favourable properties - their maximum effect of soil reinforcement in the profile to the depth of 0.5 m does not usually exceed 30 kPa, and to the depth of 1 m - 20 kPa. The root systems of conifers have the least impact on the slope reinforcement, usually increasing the soil shear strength by less than 5 kPa. These values coincide to a large extent with the range of shear strength increase obtained from the direct shear test as well as results of stability analysis given in literature and carried out as part of this work. The analysis of the literature indicates that the methods of measuring tree's root systems as well as their interpretation are very different, which often limits the possibilities of comparing test results. This indicates the need to systematize this type of tests and for this purpose a root distribution model (RDM) can be used, which can be integrated with any deformation bundle model (RBM). A combination of these two calculation models allows the range of soil reinforcement around trees to be determined and this information might be used in practice, while planning bioengineering procedures in areas exposed to surface mass movements. The functionality of this solution can be increased by considering the dynamics of plant develop¬ment in the calculations. This, however, requires conducting this type of research in order to obtain more data.

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Book chapters on the topic "Variable Order Markov Model"

Armentano, Marcelo G., and Analía A. Amandi. "Recognition of User Intentions for Interface Agents with Variable Order Markov Models." In User Modeling, Adaptation, and Personalization, 173–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02247-0_18.

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Nagata, Yuichi. "Population Diversity Measures Based on Variable-Order Markov Models for the Traveling Salesman Problem." In Parallel Problem Solving from Nature – PPSN XIV, 973–83. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45823-6_91.

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Illescas, Gustavo, Mariano Martínez, Arturo Mora-Soto, and Jose Roberto Cantú-González. "How to Think Like a Data Scientist: Application of a Variable Order Markov Model to Indicators Management." In Advances in Intelligent Systems and Computing, 153–63. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26285-7_13.

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Dalevi, Daniel, and Devdatt Dubhashi. "The Peres-Shields Order Estimator for Fixed and Variable Length Markov Models with Applications to DNA Sequence Similarity." In Lecture Notes in Computer Science, 291–302. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11557067_24.

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Parag, Toufiq, and Ahmed Elgammal. "Higher Order Markov Networks for Model Estimation." In Advances in Visual Computing, 246–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24028-7_23.

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Han, Jinyu, Gautham J. Mysore, and Bryan Pardo. "Audio Imputation Using the Non-negative Hidden Markov Model." In Latent Variable Analysis and Signal Separation, 347–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28551-6_43.

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Tonne, Jens, and Olaf Stursberg. "Constrained Model Predictive Control of Processes with Uncertain Structure Modeled by Jump Markov Linear Systems." In Variable-Structure Approaches, 335–61. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31539-3_12.

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Sierociuk, Dominik, Michal Macias, and Pawel Ziubinski. "Experimental Results of Modeling Variable Order System Based on Discrete Fractional Variable Order State-Space Model." In Theoretical Developments and Applications of Non-Integer Order Systems, 129–39. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23039-9_11.

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Babich, Fulvio, Owen E. Kelly, and Giancarlo Lombardi. "A Variable-Order Discrete Model for the Fading Channel." In Broadband Wireless Communications, 259–66. London: Springer London, 1998. http://dx.doi.org/10.1007/978-1-4471-1570-0_24.

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Kermorvant, Christopher, and Pierre Dupont. "Improved Smoothing for Probabilistic Suffix Trees Seen as Variable Order Markov Chains." In Lecture Notes in Computer Science, 185–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-36755-1_16.

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Conference papers on the topic "Variable Order Markov Model"

Yang, Jie, Jian Xu, Ming Xu, Ning Zheng, and Yu Chen. "Predicting next location using a variable order Markov model." In SIGSPATIAL '14: 22nd SIGSPATIAL International Conference on Advances in Geographic Information Systems. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2676552.2676557.

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Zhu, Simin, Xin Lv, and Lin Yu. "Location Privacy Protection Method based on Variable-Order Markov Prediction Model." In CSSE 2021: 2021 4th International Conference on Computer Science and Software Engineering. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3494885.3494890.

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Xia, Ying, Yu Gong, Xu Zhang, and Hae-young Bae. "Location Prediction Based on Variable-order Markov Model and User's Spatio-temporal Rule." In 2018 International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2018. http://dx.doi.org/10.1109/ictc.2018.8539593.

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Surmeli, Bans Gun, Feyza Eksen, Bilal Dinc, Peter Schuller, and Borahan Tumer. "Unsupervised mode detection in cyber-physical systems using variable order Markov models." In 2017 IEEE 15th International Conference on Industrial Informatics (INDIN). IEEE, 2017. http://dx.doi.org/10.1109/indin.2017.8104881.

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Ji, Guoli, Huanghui Zhang, Xiaohui Wu, and Meishuang Tang. "Identification of plant messenger RNA polyadenylation sites using length-variable second order Markov model." In 2011 IEEE International Conference on Systems, Man and Cybernetics - SMC. IEEE, 2011. http://dx.doi.org/10.1109/icsmc.2011.6083769.

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Devanarayana, C., and A. S. Alfa. "Predictive Channel Access in Cognitive Radio Networks Based on Variable Order Markov Models." In 2011 IEEE Global Communications Conference (GLOBECOM 2011). IEEE, 2011. http://dx.doi.org/10.1109/glocom.2011.6133706.

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Araújo, Felipe Rocha de, Denis Lima Rosário, Kassio Machado, Eduardo Coelho Cerqueira, and Leandro Villas. "TEMMUS: A Mobility Predictor based on Temporal Markov Model with User Similarity." In XXXVII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/sbrc.2019.7389.

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Location-Based Social Networks (LBSN) data contains spatial, temporal, and social features of user activity, providing valuable information that is currently available on large-scale and low-cost fashion via traditional data collection methods. In this way, LBSN data enables to predict user mobility based on spatial, temporal, and social features, which can be used in several areas, such as device-to-device (D2D) communication, caching, and others. In addition, a Temporal Markov Chain (TMC) is a stochastic model used to model randomly changing systems, such as mobility prediction based on the spatiotemporal factor such as location and day of the week. In this paper, we introduce the Temporal Markov Model with User Similarity (TEMMUS) mobility prediction model. TEMMUS considers a TMC of variable order based on the day of the week (weekday or weekend) and the user similarity to predict the user's future location. The results highlight a higher accuracy of TEMMUS compared to three state-of-the-art Markov Model predictors.

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Chen, Yuqiao, Nicholas Ruozzi, and Sriraam Natarajan. "Lifted Message Passing for Hybrid Probabilistic Inference." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/790.

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Lifted inference algorithms for first-order logic models, e.g., Markov logic networks (MLNs), have been of significant interest in recent years. Lifted inference methods exploit model symmetries in order to reduce the size of the model and, consequently, the computational cost of inference. In this work, we consider the problem of lifted inference in MLNs with continuous or both discrete and continuous groundings. Existing work on lifting with continuous groundings has mostly been limited to special classes of models, e.g., Gaussian models, for which variable elimination or message-passing updates can be computed exactly. Here, we develop approximate lifted inference schemes based on particle sampling. We demonstrate empirically that our approximate lifting schemes perform comparably to existing state-of-the-art for models for Gaussian MLNs, while having the flexibility to be applied to models with arbitrary potential functions.

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Yannou, Bernard, Jiliang Wang, Ndrianarilala Rianantsoa, Chris Hoyle, Mark Drayer, Wei Chen, Fabrice Alizon, and Jean-Pierre Mathieu. "Usage Coverage Model for Choice Modeling: Principles." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-87534.

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Accurately capturing the future demand for a given product is a hard task in today’s new product development initiatives. As customers become more market-savvy and markets continue fragment, current demand models could greatly benefit from exploiting the rich contextual information that exists in customers’ product usage. As such, we propose a Usage Coverage Model (UCM) as a more thorough means to quantify and capture customer demand by utilizing factors of usage context in order to inform an integrated engineering design and choice modeling approach. We start by presenting the principles of the UCM model: terms, definitions, variable classes and relation classes so as to obtain a common usage language. The usage model exhibits the ability to differentiate between individuals’ product performance experiences. With Discrete Choice Analysis, individuals’ performance with a given product is compared against that of competitive products, capturing individual customers’ choice behavior and thereby creating an effective model of product demand. As a demonstration of our methods, we apply our model in a case study regarding the general task of cutting a wood board with a jigsaw tool. We conclude by presenting the scope of future work for the case study and the contribution of the entire current and future work to the field as a whole.

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Mori, Shinsuke, and Gakuto Kurata. "Class-based variable memory length Markov model." In Interspeech 2005. ISCA: ISCA, 2005. http://dx.doi.org/10.21437/interspeech.2005-6.

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Reports on the topic "Variable Order Markov Model"

Соловйов, Володимир Миколайович, Vladimir Saptsin, and Dmitry Chabanenko. Prediction of financial time series with the technology of high-order Markov chains. AGSOE, March 2009. http://dx.doi.org/10.31812/0564/1131.

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In this research the technology of complex Markov chains, i.e. Markov chains with a memory is applied to forecast the ﬁnancial time-series. The high-order Markov chains can be simpliﬁed to ﬁrst-order ones by generalizing the states in Markov chains. Considering the *generalized state* as the sequence of states makes a possibility to model high-order Markov chains like ﬁrst-order ones. The adaptive method of deﬁning the states is proposed, it is concerned with the statistic properties of price returns. The algorithm of prediction includes the next steps: (1) Generate the hierarchical set of time discretizations; (2) Reducing the discretiza- tion of initial data and doing prediction at the every time-level (3) Recurrent conjunction of prediction series of diﬀerent discretizations in a single time-series. The hierarchy of time discretizations gives a possibility to review long-memory properties of the series without increasing the order of the Markov chains, to make prediction on the diﬀerent frequencies of the series. The technology is tested on several time-series, including: EUR/USD Forex course, the World’s indices, including Dow Jones, S&P 500, RTS, PFTS and other.

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Soloviev, V., V. Saptsin, and D. Chabanenko. Financial time series prediction with the technology of complex Markov chains. Брама-Україна, 2014. http://dx.doi.org/10.31812/0564/1305.

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Соловйов, Володимир Миколайович, V. Saptsin, and D. Chabanenko. Financial time series prediction with the technology of complex Markov chains. Transport and Telecommunication Institute, 2010. http://dx.doi.org/10.31812/0564/1145.

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In this research the technology of complex Markov chains, i.e. Markov chains with a memory is applied to forecast financial time-series. The main distinction of complex or high-order Markov chains [1] and simple first-order ones is the existing of after effect or memory. The high-order Markov chains can be simplified to first-order ones by generalizing the states in Markov chains. Considering the “generalized state” as the sequence of states makes a possibility to model high-order Markov chains like first-order ones. The adaptive method of defining the states is proposed, it is concerned with the statistic properties of price returns [2]. According to the fundamental principles of quantum measurement theories, the measurement procedure impacts not only on the result of the measurement, but also on the state of the measured system, and the behaviour of this system in the future remains undefined, despite of the precision of the measurement. This statement, in our opinion, is general and is true not only for physical systems, but to any complex systems [3].

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Kim, Changmo, Ghazan Khan, Brent Nguyen, and Emily L. Hoang. Development of a Statistical Model to Predict Materials’ Unit Prices for Future Maintenance and Rehabilitation in Highway Life Cycle Cost Analysis. Mineta Transportation Institute, December 2020. http://dx.doi.org/10.31979/mti.2020.1806.

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The main objectives of this study are to investigate the trends in primary pavement materials’ unit price over time and to develop statistical models and guidelines for using predictive unit prices of pavement materials instead of uniform unit prices in life cycle cost analysis (LCCA) for future maintenance and rehabilitation (M&R) projects. Various socio-economic data were collected for the past 20 years (1997–2018) in California, including oil price, population, government expenditure in transportation, vehicle registration, and other key variables, in order to identify factors affecting pavement materials’ unit price. Additionally, the unit price records of the popular pavement materials were categorized by project size (small, medium, large, and extra-large). The critical variables were chosen after identifying their correlations, and the future values of each variable were predicted through time-series analysis. Multiple regression models using selected socio-economic variables were developed to predict the future values of pavement materials’ unit price. A case study was used to compare the results between the uniform unit prices in the current LCCA procedures and the unit prices predicted in this study. In LCCA, long-term prediction involves uncertainties due to unexpected economic trends and industrial demand and supply conditions. Economic recessions and a global pandemic are examples of unexpected events which can have a significant influence on variations in material unit prices and project costs. Nevertheless, the data-driven scientific approach as described in this research reduces risk caused by such uncertainties and enables reasonable predictions for the future. The statistical models developed to predict the future unit prices of the pavement materials through this research can be implemented to enhance the current LCCA procedure and predict more realistic unit prices and project costs for the future M&R activities, thus promoting the most cost-effective alternative in LCCA.

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Kimhi, Ayal, Barry Goodwin, Ashok Mishra, Avner Ahituv, and Yoav Kislev. The dynamics of off-farm employment, farm size, and farm structure. United States Department of Agriculture, September 2006. http://dx.doi.org/10.32747/2006.7695877.bard.

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Objectives: (1) Preparing panel data sets for both the United States and Israel that contain a rich set of farm attributes, such as size, specialization, and output composition, and farmers’ characteristics such as off-farm employment status, education, and family composition. (2) Developing an empirical framework for the joint analysis of all the endogenous variables of interest in a dynamic setting. (3) Estimating simultaneous equations of the endogenous variables using the panel data sets from both countries. (4) Analyzing, using the empirical results, the possible effects of economic policies and institutional changes on the dynamics of the farm sector. An added objective is analyzing structural changes in farm sectors in additional countries. Background: Farm sectors in developed countries, including the U.S. and Israel, have experienced a sharp decline in their size and importance during the second half of the 20th century. The overall trend is towards fewer and larger farms that rely less on family labor. These structural changes have been a reaction to changes in technology, in government policies, and in market conditions: decreasing terms of trade, increasing alternative opportunities, and urbanization pressures. As these factors continue to change, so does the structure of the agricultural sector. Conclusions: We have shown that all major dimensions of structural changes in agriculture are closely interlinked. These include farm efficiency, farm scale, farm scope (diversification), and off-farm labor. We have also shown that these conclusions hold and perhaps even become stronger whenever dynamic aspects of structural adjustments are explicitly modeled using longitudinal data. While the results vary somewhat in the different applications, several common features are observed for both the U.S. and Israel. First, the trend towards the concentration of farm production in a smaller number of larger farm enterprises is likely to continue. Second, at the micro level, increased farm size is negatively associated with increased off-farm labor, with the causality going both ways. Third, the increase in farm size is mostly achieved by diversifying farm production into additional activities (crops or livestock). All these imply that the farm sector converges towards a bi-modal farm distribution, with some farms becoming commercial while the remaining farm households either exit farming altogether or continue producing but rely heavily on off-farm income. Implications: The primary scientific implication of this project is that one should not analyze a specific farm attribute in isolation. We have shown that controlling for the joint determination of the various farm and household attributes is crucial for obtaining meaningful empirical results. The policy implications are to some extent general but could be different in the two countries. The general implication is that farm policy is an important determinant of structural changes in the farm sector. For the U.S., we have shown the different effects of coupled and decoupled (direct) farm payments on the various farm attributes, and also shown that it is important to take into account the joint farm-household decisions in order to conduct a meaningful policy analysis. Only this kind of analysis explains the indirect effect of direct farm payments on farm production decisions. For Israel, we concluded that farm policy (or lack of farm policy) has contributed to the fast structural changes we observed over the last 25 years. The sharp change of direction in farm policy that started in the early 1980s has accelerated structural changes that could have been smoother otherwise. These accelerated structural changes most likely lead to welfare losses in rural areas.

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Lasko, Kristofer, and Elena Sava. Semi-automated land cover mapping using an ensemble of support vector machines with moderate resolution imagery integrated into a custom decision support tool. Engineer Research and Development Center (U.S.), November 2021. http://dx.doi.org/10.21079/11681/42402.

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Land cover type is a fundamental remote sensing-derived variable for terrain analysis and environmental mapping applications. The currently available products are produced only for a single season or a specific year. Some of these products have a coarse resolution and quickly become outdated, as land cover type can undergo significant change over a short time period. In order to enable on-demand generation of timely and accurate land cover type products, we developed a sensor-agnostic framework leveraging pre-trained machine learning models. We also generated land cover models for Sentinel-2 (20m) and Landsat 8 imagery (30m) using either a single date of imagery or two dates of imagery for mapping land cover type. The two-date model includes 11 land cover type classes, whereas the single-date model contains 6 classes. The models’ overall accuracies were 84% (Sentinel-2 single date), 82% (Sentinel-2 two date), and 86% (Landsat 8 two date) across the continental United States. The three different models were built into an ArcGIS Pro Python toolbox to enable a semi-automated workflow for end users to generate their own land cover type maps on demand. The toolboxes were built using parallel processing and image-splitting techniques to enable faster computation and for use on less-powerful machines.

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Tao, Yang, Amos Mizrach, Victor Alchanatis, Nachshon Shamir, and Tom Porter. Automated imaging broiler chicksexing for gender-specific and efficient production. United States Department of Agriculture, December 2014. http://dx.doi.org/10.32747/2014.7594391.bard.

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Extending the previous two years of research results (Mizarch, et al, 2012, Tao, 2011, 2012), the third year’s efforts in both Maryland and Israel were directed towards the engineering of the system. The activities included the robust chick handling and its conveyor system development, optical system improvement, online dynamic motion imaging of chicks, multi-image sequence optimal feather extraction and detection, and pattern recognition. Mechanical System Engineering The third model of the mechanical chick handling system with high-speed imaging system was built as shown in Fig. 1. This system has the improved chick holding cups and motion mechanisms that enable chicks to open wings through the view section. The mechanical system has achieved the speed of 4 chicks per second which exceeds the design specs of 3 chicks per second. In the center of the conveyor, a high-speed camera with UV sensitive optical system, shown in Fig.2, was installed that captures chick images at multiple frames (45 images and system selectable) when the chick passing through the view area. Through intensive discussions and efforts, the PIs of Maryland and ARO have created the protocol of joint hardware and software that uses sequential images of chick in its fall motion to capture opening wings and extract the optimal opening positions. This approached enables the reliable feather feature extraction in dynamic motion and pattern recognition. Improving of Chick Wing Deployment The mechanical system for chick conveying and especially the section that cause chicks to deploy their wings wide open under the fast video camera and the UV light was investigated along the third study year. As a natural behavior, chicks tend to deploy their wings as a mean of balancing their body when a sudden change in the vertical movement was applied. In the latest two years, this was achieved by causing the chicks to move in a free fall, in the earth gravity (g) along short vertical distance. The chicks have always tended to deploy their wing but not always in wide horizontal open situation. Such position is requested in order to get successful image under the video camera. Besides, the cells with checks bumped suddenly at the end of the free falling path. That caused the chicks legs to collapse inside the cells and the image of wing become bluer. For improving the movement and preventing the chick legs from collapsing, a slowing down mechanism was design and tested. This was done by installing of plastic block, that was printed in a predesign variable slope (Fig. 3) at the end of the path of falling cells (Fig.4). The cells are moving down in variable velocity according the block slope and achieve zero velocity at the end of the path. The slop was design in a way that the deacceleration become 0.8g instead the free fall gravity (g) without presence of the block. The tests showed better deployment and wider chick's wing opening as well as better balance along the movement. Design of additional sizes of block slops is under investigation. Slops that create accelerations of 0.7g, 0.9g, and variable accelerations are designed for improving movement path and images.

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Alchanatis, Victor, Stephen W. Searcy, Moshe Meron, W. Lee, G. Y. Li, and A. Ben Porath. Prediction of Nitrogen Stress Using Reflectance Techniques. United States Department of Agriculture, November 2001. http://dx.doi.org/10.32747/2001.7580664.bard.

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Commercial agriculture has come under increasing pressure to reduce nitrogen fertilizer inputs in order to minimize potential nonpoint source pollution of ground and surface waters. This has resulted in increased interest in site specific fertilizer management. One way to solve pollution problems would be to determine crop nutrient needs in real time, using remote detection, and regulating fertilizer dispensed by an applicator. By detecting actual plant needs, only the additional nitrogen necessary to optimize production would be supplied. This research aimed to develop techniques for real time assessment of nitrogen status of corn using a mobile sensor with the potential to regulate nitrogen application based on data from that sensor. Specifically, the research first attempted to determine the system parameters necessary to optimize reflectance spectra of corn plants as a function of growth stage, chlorophyll and nitrogen status. In addition to that, an adaptable, multispectral sensor and the signal processing algorithm to provide real time, in-field assessment of corn nitrogen status was developed. Spectral characteristics of corn leaves reflectance were investigated in order to estimate the nitrogen status of the plants, using a commercial laboratory spectrometer. Statistical models relating leaf N and reflectance spectra were developed for both greenhouse and field plots. A basis was established for assessing nitrogen status using spectral reflectance from plant canopies. The combined effect of variety and N treatment was studied by measuring the reflectance of three varieties of different leaf characteristic color and five different N treatments. The variety effect on the reflectance at 552 nm was not significant (a = 0.01), while canonical discriminant analysis showed promising results for distinguishing different variety and N treatment, using spectral reflectance. Ambient illumination was found inappropriate for reliable, one-beam spectral reflectance measurement of the plants canopy due to the strong spectral lines of sunlight. Therefore, artificial light was consequently used. For in-field N status measurement, a dark chamber was constructed, to include the sensor, along with artificial illumination. Two different approaches were tested (i) use of spatially scattered artificial light, and (ii) use of collimated artificial light beam. It was found that the collimated beam along with a proper design of the sensor-beam geometry yielded the best results in terms of reducing the noise due to variable background, and maintaining the same distance from the sensor to the sample point of the canopy. A multispectral sensor assembly, based on a linear variable filter was designed, constructed and tested. The sensor assembly combined two sensors to cover the range of 400 to 1100 nm, a mounting frame, and a field data acquisition system. Using the mobile dark chamber and the developed sensor, as well as an off-the-shelf sensor, in- field nitrogen status of the plants canopy was measured. Statistical analysis of the acquired in-field data showed that the nitrogen status of the com leaves can be predicted with a SEP (Standard Error of Prediction) of 0.27%. The stage of maturity of the crop affected the relationship between the reflectance spectrum and the nitrogen status of the leaves. Specifically, the best prediction results were obtained when a separate model was used for each maturity stage. In-field assessment of the nitrogen status of corn leaves was successfully carried out by non contact measurement of the reflectance spectrum. This technology is now mature to be incorporated in field implements for on-line control of fertilizer application.

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Chapman, Ray, Phu Luong, Sung-Chan Kim, and Earl Hayter. Development of three-dimensional wetting and drying algorithm for the Geophysical Scale Transport Multi-Block Hydrodynamic Sediment and Water Quality Transport Modeling System (GSMB). Engineer Research and Development Center (U.S.), July 2021. http://dx.doi.org/10.21079/11681/41085.

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The Environmental Laboratory (EL) and the Coastal and Hydraulics Laboratory (CHL) have jointly completed a number of large-scale hydrodynamic, sediment and water quality transport studies. EL and CHL have successfully executed these studies utilizing the Geophysical Scale Transport Modeling System (GSMB). The model framework of GSMB is composed of multiple process models as shown in Figure 1. Figure 1 shows that the United States Army Corps of Engineers (USACE) accepted wave, hydrodynamic, sediment and water quality transport models are directly and indirectly linked within the GSMB framework. The components of GSMB are the two-dimensional (2D) deep-water wave action model (WAM) (Komen et al. 1994, Jensen et al. 2012), data from meteorological model (MET) (e.g., Saha et al. 2010 - http://journals.ametsoc.org/doi/pdf/10.1175/2010BAMS3001.1), shallow water wave models (STWAVE) (Smith et al. 1999), Coastal Modeling System wave (CMS-WAVE) (Lin et al. 2008), the large-scale, unstructured two-dimensional Advanced Circulation (2D ADCIRC) hydrodynamic model (http://www.adcirc.org), and the regional scale models, Curvilinear Hydrodynamics in three dimensions-Multi-Block (CH3D-MB) (Luong and Chapman 2009), which is the multi-block (MB) version of Curvilinear Hydrodynamics in three-dimensions-Waterways Experiments Station (CH3D-WES) (Chapman et al. 1996, Chapman et al. 2009), MB CH3D-SEDZLJ sediment transport model (Hayter et al. 2012), and CE-QUAL Management - ICM water quality model (Bunch et al. 2003, Cerco and Cole 1994). Task 1 of the DOER project, “Modeling Transport in Wetting/Drying and Vegetated Regions,” is to implement and test three-dimensional (3D) wetting and drying (W/D) within GSMB. This technical note describes the methods and results of Task 1. The original W/D routines were restricted to a single vertical layer or depth-averaged simulations. In order to retain the required 3D or multi-layer capability of MB-CH3D, a multi-block version with variable block layers was developed (Chapman and Luong 2009). This approach requires a combination of grid decomposition, MB, and Message Passing Interface (MPI) communication (Snir et al. 1998). The MB single layer W/D has demonstrated itself as an effective tool in hyper-tide environments, such as Cook Inlet, Alaska (Hayter et al. 2012). The code modifications, implementation, and testing of a fully 3D W/D are described in the following sections of this technical note.

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