Predicting Lane Changes by Identifying Sequence Patterns of Implicit Communication Cues

2021 ◽  
pp. 3-10
Author(s):  
Ann-Christin Hensch ◽  
Matthias Beggiato ◽  
Josef F. Krems
Keyword(s):  
Lane Changes ◽  
Implicit Communication ◽  
Sequence Patterns

Flexible k-mers with variable-length indels for identifying binding sequences of protein dimers

2019 ◽  
Vol 21 (5) ◽  
pp. 1787-1797
Author(s):  
Chenyang Hong ◽  
Kevin Y Yip
Keyword(s):  
Binding Proteins ◽  
Affinity Purification ◽  
Classification Performance ◽  
Variable Regions ◽  
Binding Motifs ◽  
New Class ◽  
Protein Dimers ◽  
Sequence Patterns ◽  
Standard Chip ◽  
Exponential Enrichment

Abstract Many DNA-binding proteins interact with partner proteins. Recently, based on the high-throughput consecutive affinity-purification systematic evolution of ligands by exponential enrichment (CAP-SELEX) method, many such protein pairs have been found to bind DNA with flexible spacing between their individual binding motifs. Most existing motif representations were not designed to capture such flexibly spaced regions. In order to computationally discover more co-binding events without prior knowledge about the identities of the co-binding proteins, a new representation is needed. We propose a new class of sequence patterns that flexibly model such variable regions and corresponding algorithms that identify co-bound sequences using these patterns. Based on both simulated and CAP-SELEX data, features derived from our sequence patterns lead to better classification performance than patterns that do not explicitly model the variable regions. We also show that even for standard ChIP-seq data, this new class of sequence patterns can help discover co-bound events in a subset of sequences in an unsupervised manner. The open-source software is available at https://github.com/kevingroup/glk-SVM.

scholarly journals Development of an Improved Rapidly Exploring Random Trees Algorithm for Static Obstacle Avoidance in Autonomous Vehicles

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2244
Author(s):  
S. M. Yang ◽  
Y. A. Lin
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Optimal Path ◽  
Random Trees ◽  
Average Deviation ◽  
Lane Changes ◽  
Path Smoothing ◽  
Rapidly Exploring Random Trees

Safe path planning for obstacle avoidance in autonomous vehicles has been developed. Based on the Rapidly Exploring Random Trees (RRT) algorithm, an improved algorithm integrating path pruning, smoothing, and optimization with geometric collision detection is shown to improve planning efficiency. Path pruning, a prerequisite to path smoothing, is performed to remove the redundant points generated by the random trees for a new path, without colliding with the obstacles. Path smoothing is performed to modify the path so that it becomes continuously differentiable with curvature implementable by the vehicle. Optimization is performed to select a “near”-optimal path of the shortest distance among the feasible paths for motion efficiency. In the experimental verification, both a pure pursuit steering controller and a proportional–integral speed controller are applied to keep an autonomous vehicle tracking the planned path predicted by the improved RRT algorithm. It is shown that the vehicle can successfully track the path efficiently and reach the destination safely, with an average tracking control deviation of 5.2% of the vehicle width. The path planning is also applied to lane changes, and the average deviation from the lane during and after lane changes remains within 8.3% of the vehicle width.

Animal-assisted dyadic therapy: A therapy model promoting development of the reflective function in the parent–child bond

2016 ◽  
Vol 22 (1) ◽  
pp. 46-58 ◽  
Author(s):  
Liat Shani
Keyword(s):  
Nonverbal Communication ◽  
Child Psychotherapy ◽  
Theoretical Development ◽  
Reflective Function ◽  
Therapeutic Approaches ◽  
Implicit Communication ◽  
Special Value ◽  
Therapy Model ◽  
Ethical Stance ◽  
Parent Child

Animal-assisted psychotherapy (AAP) inherently incorporates standpoints, interventions, and ways of action promoting the development of the reflective function and mentalization, and thus has special value for parent–child psychotherapy. Two central tools in AAP contribute to this process. The first is the ethical stance of the therapist, who sees the animals as full partners in the therapy situation, respecting them as subjects with needs, desires, and thoughts of their own. The second tool combines nonverbal communication with animals together with the relating, in the here and now, to the understanding and decoding of body language of everyone in the setting. Nonverbal communication in AAP enables access to implicit communication patterns occurring between parent and child. This article provides a survey of theoretical development and research constituting a basis for the development of therapeutic approaches for the improvement of parent–children dynamics, followed by a description of a dyadic therapy model of a mentalization-based treatment originating from a psychoanalytic-relational orientation. Clinical examples are provided to illustrate AAP processes in parent–child psychotherapy (consent was received for examples that were not aggregated).

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