Clustering-Based Online Player Modeling

Being able to imitate individual players in a game can benefit game development by providing a means to create a variety of autonomous agents and aid understanding of which aspects of game states influence game-play. This paper presents a clustering and locally weighted regression method for modeling and imitating individual players. The algorithm first learns a generic player cluster model that is updated online to capture an individual’s game-play tendencies. The models can then be used to play the game or for analysis to identify how different players react to separate aspects of game states. The method is demonstrated on a tablet-based trajectory generation game called Space Navigator

A Function-to-Task Process Model for Adaptive Automation System Design

Adaptive automation systems allow the user to complete a task seamlessly with a computer performing tasks at which the human operator struggles. Unlike traditional systems that allocate functions to either the human or the machine, adaptive automation varies the allocation of functions during system operation. Creating these systems requires designers to consider issues not present during static system development. To assist in adaptive automation system design, this paper presents the concept of inherent tasks and takes advantage of this concept to create the function-to-task design process model. This process model helps the designer determine how to allocate functions to the human, machine, or dynamically between the two. An illustration of the process demonstrates the potential complexity within adaptive automation systems and how the process model aids in understanding this complexity during early stage design

Final Report of the AFIT Quality Initiative: Gap Analysis and Investment Strategy Guidance

This report presents the investment strategy guidance emanating from the Air Force Institute of Technology’s (AFIT’s) Quality Initiative. This report culminates a two-year effort involving external discovery, internal discovery, gap analysis, and investment strategy guidance formulation. The overarching purpose of the Quality Initiative is to recommend investment strategy guidance with the intention of modernizing AFIT’s instructional capabilities. Although this report provides an overview of the entirety of AFIT’s quality initiative efforts, the two primary foci of this report are (1) discussing the six initiatives identified by the Gap Analysis Committee and (2) presenting investment strategy guidance

Final Report of the AFIT Quality Initiative External Discovery Committee

This report summarizes the findings of the Air Force Institute of Technology’s (AFIT’s) Quality Initiative - External Discovery Team. The overarching purpose of the Quality Initiative is to create a detailed, executable investment strategy for modernizing AFIT’s instructional capabilities across five thrust areas. These activities were completed over the course of one year, beginning in June of 2016 and concluding in June of 2017. The data gathered were evaluated and several recommendations for further review were decided upon by the External Discovery Team. The following report briefly covers those recommendations and provides sources from which the recommendations were gleaned. These recommendations are meant to serve as a baseline for ways in which AFIT could begin to program resources to help improve teaching and instruction across the institution as a whole. The data presented here are meant to serve as a compliment to the Internal Discovery Team’s report that focuses on data and feedback gathered from institutions internal to AFIT

Impact Of The Energy Model On The Complexity Of RNA Folding With Pseudoknots

International audiencePredicting the folding of an RNA sequence, while allowing general pseudoknots (PK), consists in finding a minimal free-energy matching of its $n$ positions. Assuming independently contributing base-pairs, the problem can be solved in $\Theta(n^3)$-time using a variant of the maximal weighted matching. By contrast, the problem was previously proven NP-Hard in the more realistic nearest-neighbor energy model. In this work, we consider an intermediate model, called the stacking-pairs energy model. We extend a result by Lyngs\o, showing that RNA folding with PK is NP-Hard within a large class of parametrization for the model. We also show the approximability of the problem, by giving a practical $\Theta(n^3)$ algorithm that achieves at least a $5$-approximation for any parametrization of the stacking model. This contrasts nicely with the nearest-neighbor version of the problem, which we prove cannot be approximated within any positive ratio, unless $P=NP$.La prédiction du repliement, avec pseudonoeuds généraux, d'une séquence d'ARN de taille $n$ est équivalent à la recherche d'un couplage d'énergie libre minimale. Dans un modèle d'énergie simple, où chaque paire de base contribue indépendamment à l'énergie, ce problème peut être résolu en temps $\Theta(n^3)$ grâce à une variante d'un algorithme de couplage pondéré maximal. Cependant, le même problème a été démontré NP-difficile dans le modèle d'énergie dit des plus proches voisins. Dans ce travail, nous étudions les propriétés du problème sous un modèle d'empilements, constituant un modèle intermédiaire entre ceux d'appariement et des plus proches voisins. Nous démontrons tout d'abord que le repliement avec pseudo-noeuds de l'ARN reste NP-difficile dans de nombreuses valuations du modèle d'énergie. . Par ailleurs, nous montrons que ce problème est approximable, en proposant un algorithme polynomial garantissant une $1/5$-approximation. Ce résultat illustre une différence essentielle entre ce modèle et celui des plus proches voisins, pour lequel nous montrons qu'il ne peut être approché à aucun ratio positif par un algorithme en temps polynomial sauf si $N=NP$

CyloFold: secondary structure prediction including pseudoknots

Computational RNA secondary structure prediction approaches differ by the way RNA pseudoknot interactions are handled. For reasons of computational efficiency, most approaches only allow a limited class of pseudoknot interactions or are not considering them at all. Here we present a computational method for RNA secondary structure prediction that is not restricted in terms of pseudoknot complexity. The approach is based on simulating a folding process in a coarse-grained manner by choosing helices based on established energy rules. The steric feasibility of the chosen set of helices is checked during the folding process using a highly coarse-grained 3D model of the RNA structures. Using two data sets of 26 and 241 RNA sequences we find that this approach is competitive compared to the existing RNA secondary structure prediction programs pknotsRG, HotKnots and UnaFold. The key advantages of the new method are that there is no algorithmic restriction in terms of pseudoknot complexity and a test is made for steric feasibility. Availability: The program is available as web server at the site: http://cylofold.abcc.ncifcrf.gov

RNA secondary structure prediction from multi-aligned sequences

It has been well accepted that the RNA secondary structures of most functional non-coding RNAs (ncRNAs) are closely related to their functions and are conserved during evolution. Hence, prediction of conserved secondary structures from evolutionarily related sequences is one important task in RNA bioinformatics; the methods are useful not only to further functional analyses of ncRNAs but also to improve the accuracy of secondary structure predictions and to find novel functional RNAs from the genome. In this review, I focus on common secondary structure prediction from a given aligned RNA sequence, in which one secondary structure whose length is equal to that of the input alignment is predicted. I systematically review and classify existing tools and algorithms for the problem, by utilizing the information employed in the tools and by adopting a unified viewpoint based on maximum expected gain (MEG) estimators. I believe that this classification will allow a deeper understanding of each tool and provide users with useful information for selecting tools for common secondary structure predictions.Comment: A preprint of an invited review manuscript that will be published in a chapter of the book `Methods in Molecular Biology'. Note that this version of the manuscript may differ from the published versio

Role of 3′UTRs in the Translation of mRNAs Regulated by Oncogenic eIF4E—A Computational Inference

Eukaryotic cap-dependent mRNA translation is mediated by the initiation factor eIF4E, which binds mRNAs and stimulates efficient translation initiation. eIF4E is often overexpressed in human cancers. To elucidate the molecular signature of eIF4E target mRNAs, we analyzed sequence and structural properties of two independently derived polyribosome recruited mRNA datasets. These datasets originate from studies of mRNAs that are actively being translated in response to cells over-expressing eIF4E or cells with an activated oncogenic AKT: eIF4E signaling pathway, respectively. Comparison of eIF4E target mRNAs to mRNAs insensitive to eIF4E-regulation has revealed surprising features in mRNA secondary structure, length and microRNA-binding properties. Fold-changes (the relative change in recruitment of an mRNA to actively translating polyribosomal complexes in response to eIF4E overexpression or AKT upregulation) are positively correlated with mRNA G+C content and negatively correlated with total and 3′UTR length of the mRNAs. A machine learning approach for predicting the fold change was created. Interesting tendencies of secondary structure stability are found near the start codon and at the beginning of the 3′UTR region. Highly upregulated mRNAs show negative selection (site avoidance) for binding sites of several microRNAs. These results are consistent with the emerging model of regulation of mRNA translation through a dynamic balance between translation initiation at the 5′UTR and microRNA binding at the 3′UTR

RNAG: a new Gibbs sampler for predicting RNA secondary structure for unaligned sequences

Motivation: RNA secondary structure plays an important role in the function of many RNAs, and structural features are often key to their interaction with other cellular components. Thus, there has been considerable interest in the prediction of secondary structures for RNA families. In this article, we present a new global structural alignment algorithm, RNAG, to predict consensus secondary structures for unaligned sequences. It uses a blocked Gibbs sampling algorithm, which has a theoretical advantage in convergence time. This algorithm iteratively samples from the conditional probability distributions P(Structure | Alignment) and P(Alignment | Structure). Not surprisingly, there is considerable uncertainly in the high-dimensional space of this difficult problem, which has so far received limited attention in this field. We show how the samples drawn from this algorithm can be used to more fully characterize the posterior space and to assess the uncertainty of predictions

Effects of total laryngectomy on olfactory function, health-related quality of life, and communication: a 3-year follow-up study

<p>Abstract</p> <p>Background</p> <p>As total laryngectomy results in loss of airflow through the nose, one of the adverse effects for a majority of patients is the reduced or complete loss of olfactory function. However, with the introduction of a new method, the Nasal Airflow-Inducing Maneuver (NAIM), an important technique is available for laryngectomized patients to regain the ability to smell. The purpose of the present study was to assess changes in olfaction, health-related quality of life (HRQL) and communication 3 years after NAIM rehabilitation.</p> <p>Methods</p> <p>18 patients (15 men and 3 women; mean age, 71 years) who had undergone laryngectomy and NAIM rehabilitation were followed longitudinally for 3 years. For comparison an age and gender matched control group with laryngeal cancer treated with radical radiotherapy was included. Olfactory function was assessed using the Questionnaire on Odor, Taste and Appetite and the Scandinavian Odor Identification Test. HRQL was assessed by: 1) the European Organization for Research and Treatment for cancer quality of life questionnaires; and 2) the Hospital Anxiety and Depression Scale. Communication was assessed by the Swedish Self-Evaluation of Communication Experiences after Laryngeal Cancer. Descriptive statistics with 95% confidence interval were calculated according to standard procedure. Changes over time as well as tests between pairs of study patients and control patients were analyzed with the Fisher nonparametric permutation test for matched pairs.</p> <p>Results</p> <p>Thirty-six months after rehabilitation 14 of 18 laryngectomized patients (78%) were smellers. There were, with one exception (sleep disturbances), no clinically or statistically significant differences between the study and the control group considering HRQL and mental distress. However, statistical differences (p < 0.001) were found between the study and the control group concerning changes in communication.</p> <p>Conclusion</p> <p>Olfactory training with NAIM should be integrated into the multidisciplinary rehabilitation program after total laryngectomy. Our study shows that patients who were successfully rehabilitated concerning olfaction and communication had an overall good HRQL and no mental distress. Moreover, the EORTC questionnaires should be complemented with more specific questionnaires when evaluating olfaction and communication in laryngectomized patients.</p