Generating Predictable and Adaptive Dialog Policies in Single- and Multi-domain Goal-oriented Dialog Systems

2021 ◽  
Vol 15 (04) ◽  
pp. 419-439
Author(s):  
Nhat Le ◽  
A. B. Siddique ◽  
Fuad Jamour ◽  
Samet Oymak ◽  
Vagelis Hristidis
Keyword(s):  
State Of The Art ◽  
Directed Graphs ◽  
Dependency Graph ◽  
The Other ◽  
Middle Ground ◽  
User Characteristics ◽  
Dialog Systems ◽  
Dependency Graphs ◽  
Novel Structure ◽  
Art Research

Most existing commercial goal-oriented chatbots are diagram-based; i.e. they follow a rigid dialog flow to fill the slot values needed to achieve a user’s goal. Diagram-based chatbots are predictable, thus their adoption in commercial settings; however, their lack of flexibility may cause many users to leave the conversation before achieving their goal. On the other hand, state-of-the-art research chatbots use Reinforcement Learning (RL) to generate flexible dialog policies. However, such chatbots can be unpredictable, may violate the intended business constraints, and require large training datasets to produce a mature policy. We propose a framework that achieves a middle ground between the diagram-based and RL-based chatbots: we constrain the space of possible chatbot responses using a novel structure, the chatbot dependency graph, and use RL to dynamically select the best valid responses. Dependency graphs are directed graphs that conveniently express a chatbot’s logic by defining the dependencies among slots: all valid dialog flows are encapsulated in one dependency graph. Our experiments in both single-domain and multi-domain settings show that our framework quickly adapts to user characteristics and achieves up to 23.77% improved success rate compared to a state-of-the-art RL model.

scholarly journals Fast Accurate and Automatic Brushstroke Extraction

2021 ◽  
Vol 17 (2) ◽  
pp. 1-24
Author(s):  
Yunfei Fu ◽  
Hongchuan Yu ◽  
Chih-Kuo Yeh ◽  
Tong-Yee Lee ◽  
Jian J. Zhang
Keyword(s):  
Neural Network ◽  
Efficient Algorithm ◽  
Deep Neural Network ◽  
High Efficiency ◽  
State Of The Art ◽  
High Reliability ◽  
The Other ◽  
Manual Annotation ◽  
Stroke Extraction ◽  
Art Research

Brushstrokes are viewed as the artist’s “handwriting” in a painting. In many applications such as style learning and transfer, mimicking painting, and painting authentication, it is highly desired to quantitatively and accurately identify brushstroke characteristics from old masters’ pieces using computer programs. However, due to the nature of hundreds or thousands of intermingling brushstrokes in the painting, it still remains challenging. This article proposes an efficient algorithm for brush Stroke extraction based on a Deep neural network, i.e., DStroke. Compared to the state-of-the-art research, the main merit of the proposed DStroke is to automatically and rapidly extract brushstrokes from a painting without manual annotation, while accurately approximating the real brushstrokes with high reliability. Herein, recovering the faithful soft transitions between brushstrokes is often ignored by the other methods. In fact, the details of brushstrokes in a master piece of painting (e.g., shapes, colors, texture, overlaps) are highly desired by artists since they hold promise to enhance and extend the artists’ powers, just like microscopes extend biologists’ powers. To demonstrate the high efficiency of the proposed DStroke, we perform it on a set of real scans of paintings and a set of synthetic paintings, respectively. Experiments show that the proposed DStroke is noticeably faster and more accurate at identifying and extracting brushstrokes, outperforming the other methods.

scholarly journals Diagnostic Impact of Radiological Findings and Extracellular Vesicles: Are We Close to Radiovesicolomics?

Biology ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1265
Author(s):  
Francesco Lorenzo Serafini ◽  
Paola Lanuti ◽  
Andrea Delli Pizzi ◽  
Luca Procaccini ◽  
Michela Villani ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Extracellular Vesicles ◽  
Laboratory Tests ◽  
State Of The Art ◽  
The Other ◽  
Radiological Findings ◽  
Radiological Features ◽  
Precise Diagnosis ◽  
Art Research

Currently, several pathologies have corresponding and specific diagnostic and therapeutic branches of interest focused on early and correct detection, as well as the best therapeutic approach. Radiology never ceases to develop newer technologies in order to give patients a clear, safe, early, and precise diagnosis; furthermore, in the last few years diagnostic imaging panoramas have been extended to the field of artificial intelligence (AI) and machine learning. On the other hand, clinical and laboratory tests, like flow cytometry and the techniques found in the “omics” sciences, aim to detect microscopic elements, like extracellular vesicles, with the highest specificity and sensibility for disease detection. If these scientific branches started to cooperate, playing a conjugated role in pathology diagnosis, what could be the results? Our review seeks to give a quick overview of recent state of the art research which investigates correlations between extracellular vesicles and the known radiological features useful for diagnosis.

On Self Intersections of Freeform Curves and Surfaces

2008 ◽  
Author(s):  
Gershon Elber
Keyword(s):  
Algebraic Structure ◽  
State Of The Art ◽  
Geometric Design ◽  
The Self ◽  
The Other ◽  
Challenging Problem ◽  
Curves And Surfaces ◽  
Current State ◽  
Art Research ◽  
Surface Intersections

The computations of curve-curve and surface-surface intersections are considered difficult problems in geometric design. Numerous results were annually published on these topics for the last several decades. Moreover, the detection and more so the computation and even elimination of self-intersections in freeform curves and surfaces is viewed by many as a far more challenging problem, with much fewer satisfactory results. In recent years, several methods were developed to robustly detect, compute and even eliminate self intersections in general freeform (typically NURBs) curves and surfaces, exploiting intrinsic and/or geometric properties, on one side, and the algebraic structure of the shape, on the other. Other methods are specific and employ special properties of the problem in hand, as is the case of offset computation. In this work, we will survey some of our results and others, and provide a birds view of the current state-of-the-art research, on the self-intersections problem, in the freeform domain.

scholarly journals Dependency Graph Based on User Taxonomy and Related Parameters for more Efficient Collaborative Work

2017 ◽  
Vol 869 ◽  
pp. 195-211 ◽  
Author(s):  
Franca Alexandra Rupprecht ◽  
François M. Torner ◽  
Jörg Seewig ◽  
Achim Ebert
Keyword(s):  
State Of The Art ◽  
Collaborative Work ◽  
Dependency Graph ◽  
User Centered Design ◽  
Dependency Graphs ◽  
Software Products ◽  
Network State ◽  
Complex Process ◽  
Collaboration Process

Collaboration, performed by a large group of experts of diverse fields and competences, is a time-demanding and complex process. It is crucial to provide tools to facilitate the identification and manipulation of interdependencies as well as the active collaboration process. Dependency graphs of the participants can help to improve processes, to plan tasks, and to identify potential for more efficient cooperation. Such a dependency graph comprises clear defined entities, which are linked with each other based on defined relationships [1]. In the course of this work, a taxonomy of users in industrial corporations will be introduced, which is needed to define the entities and relationships of the dependency graph and is easily adaptable to specific corporations. Such a taxonomy cannot be found in the literature, but is important for the design and development of software products under the rules of user centered design [2]. However, there is still the big challenge to display a meaningful relation between those entities and to give an easy understandable overview of the whole relationship with the goal to solve complex tasks and to improve a groups’ performance. Therefore, a set of parameters will be introduced, which help to find out how good tasks and work packages are distributed within the network. State-of-the-art techniques are used to visualize and recognize interdependencies and information flow. Based on a case study, the findings of this work are embedded and combined in an interactive and intuitive user interface that facilitates planners to recognize and explore complex multi-dimensional networks.

scholarly journals Water-Worked Gravel Bed: State-of-the-Art Review

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 694 ◽  
Author(s):  
Ellora Padhi ◽  
Subhasish Dey ◽  
Venkappayya R. Desai ◽  
Nadia Penna ◽  
Roberto Gaudio
Keyword(s):  
State Of The Art ◽  
Flow Characteristics ◽  
Streamwise Velocity ◽  
Secondary Currents ◽  
Gravel Bed ◽  
Natural Stream ◽  
Art Research ◽  
The Comparative Study ◽  
Water Work

In a natural gravel-bed stream, the bed that has an organized roughness structure created by the streamflow is called the water-worked gravel bed (WGB). Such a bed is entirely different from that created in a laboratory by depositing and spreading gravels in the experimental flume, called the screeded gravel bed (SGB). In this paper, a review on the state-of-the-art research on WGBs is presented, highlighting the role of water-work in determining the bed topographical structures and the turbulence characteristics in the flow. In doing so, various methods used to analyze the bed topographical structures are described. Besides, the effects of the water-work on the turbulent flow characteristics, such as streamwise velocity, Reynolds and form-induced stresses, conditional turbulent events and secondary currents in WGBs are discussed. Further, the results form WGBs and SGBs are compared critically. The comparative study infers that a WGB exhibits a higher roughness than an SGB. Consequently, the former has a higher magnitude of turbulence parameters than the latter. Finally, as a future scope of research, laboratory experiments should be conducted in WGBs rather than in SGBs to have an appropriate representation of the flow field close to a natural stream.

Computer Vision and robotics in postal automation

1999 ◽  
Vol 18 (3-4) ◽  
pp. 265-273
Author(s):  
Giovanni B. Garibotto
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Pattern Recognition ◽  
Material Handling ◽  
State Of The Art ◽  
Short Description ◽  
The Other ◽  
Functional Requirements ◽  
Postal Automation ◽  
And Robotics

The paper is intended to provide an overview of advanced robotic technologies within the context of Postal Automation services. The main functional requirements of the application are briefly referred, as well as the state of the art and new emerging solutions. Image Processing and Pattern Recognition have always played a fundamental role in Address Interpretation and Mail sorting and the new challenging objective is now off-line handwritten cursive recognition, in order to be able to handle all kind of addresses in a uniform way. On the other hand, advanced electromechanical and robotic solutions are extremely important to solve the problems of mail storage, transportation and distribution, as well as for material handling and logistics. Finally a short description of new services of Postal Automation is referred, by considering new emerging services of hybrid mail and paper to electronic conversion.

Occupant pre-crash kinematics in rotated seat arrangements

2021 ◽  
pp. 095440702110045
Author(s):  
Alexander Diederich ◽  
Christophe Bastien ◽  
Karthikeyan Ekambaram ◽  
Alexis Wilson
Keyword(s):  
State Of The Art ◽  
The Other ◽  
Human Model ◽  
Multi Objective ◽  
Emergency Braking ◽  
Seating Arrangement ◽  
Current State ◽  
Occupant Comfort ◽  
Occupant Kinematics ◽  
Belt System

The introduction of automated L5 driving technologies will revolutionise the design of vehicle interiors and seating configurations, improving occupant comfort and experience. It is foreseen that pre-crash emergency braking and swerving manoeuvres will affect occupant posture, which could lead to an interaction with a deploying airbag. This research addresses the urgent safety need of defining the occupant’s kinematics envelope during that pre-crash phase, considering rotated seat arrangements and different seatbelt configurations. The research used two different sets of volunteer tests experiencing L5 vehicle manoeuvres, based in the first instance on 22 50th percentile fit males wearing a lap-belt (OM4IS), while the other dataset is based on 87 volunteers with a BMI range of 19 to 67 kg/m2 wearing a 3-point belt (UMTRI). Unique biomechanics kinematics corridors were then defined, as a function of belt configuration and vehicle manoeuvre, to calibrate an Active Human Model (AHM) using a multi-objective optimisation coupled with a Correlation and Analysis (CORA) rating. The research improved the AHM omnidirectional kinematics response over current state of the art in a generic lap-belted environment. The AHM was then tested in a rotated seating arrangement under extreme braking, highlighting that maximum lateral and frontal motions are comparable, independent of the belt system, while the asymmetry of the 3-point belt increased the occupant’s motion towards the seatbelt buckle. It was observed that the frontal occupant kinematics decrease by 200 mm compared to a lap-belted configuration. This improved omnidirectional AHM is the first step towards designing safer future L5 vehicle interiors.

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