scholarly journals STEIM: A Spatiotemporal Event Interaction Model in V2X Systems Based on a Time Period and a Raster Map

2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Cheng Xu ◽  
Hengjie Luo ◽  
Hong Bao ◽  
Pengfei Wang
Keyword(s):  
Spatial Information ◽  
Formal Semantics ◽  
Operational Semantics ◽  
Interaction Model ◽  
Research Field ◽  
Event Stream ◽  
Spatiotemporal Information ◽  
Time Period ◽  
Temporal Model ◽  
Event Flow

The Internet of Vehicles (IoV) is an important artificial intelligence research field for intelligent transportation applications. Complex event interactions are important methods for data flow processing in a Vehicle to Everything (V2X) environment. Unlike the classic Internet of Things (IoT) systems, data streams in V2X include both temporal information and spatial information. Thus, effectively expressing and addressing spatiotemporal data interactions in the IoV is an urgent problem. To solve this problem, we propose a spatiotemporal event interaction model (STEIM). STEIM uses a time period and a raster map for its temporal model and spatial model, respectively. In this paper, first, we provide a spatiotemporal operator and a complete STEIM grammar that effectively expresses the spatiotemporal information of the spatiotemporal event flow in the V2X environment. Second, we describe the design of the operational semantics of the STEIM from the formal semantics. In addition, we provide a spatiotemporal event-stream processing algorithm that is based on the Petri net model. The STEIM establishes a mechanism for V2X event-stream temporal and spatial processing. Finally, the effectiveness of the STEIM-based system is demonstrated experimentally.

scholarly journals PGNet: Pipeline Guidance for Human Key-Point Detection

Entropy ◽  
2020 ◽  
Vol 22 (3) ◽  
pp. 369 ◽  
Author(s):  
Feng Hong ◽  
Changhua Lu ◽  
Chun Liu ◽  
Ruru Liu ◽  
Weiwei Jiang ◽  
...  
Keyword(s):  
Network Structure ◽  
Semantic Information ◽  
Spatial Information ◽  
Operation Time ◽  
Research Field ◽  
Feature Model ◽  
Communication Overhead ◽  
Network Computing ◽  
Deep Layers ◽  
Point Detection

Human key-point detection is a challenging research field in computer vision. Convolutional neural models limit the number of parameters and mine the local structure, and have made great progress in significant target detection and key-point detection. However, the features extracted by shallow layers mainly contain a lack of semantic information, while the features extracted by deep layers contain rich semantic information but a lack of spatial information that results in information imbalance and feature extraction imbalance. With the complexity of the network structure and the increasing amount of computation, the balance between the time of communication and the time of calculation highlights the importance. Based on the improvement of hardware equipment, network operation time is greatly improved by optimizing the network structure and data operation methods. However, as the network structure becomes deeper and deeper, the communication consumption between networks also increases, and network computing capacity is optimized. In addition, communication overhead is also the focus of recent attention. We propose a novel network structure PGNet, which contains three parts: pipeline guidance strategy (PGS); Cross-Distance-IoU Loss (CIoU); and Cascaded Fusion Feature Model (CFFM).

Considerations in Design of Transition Behaviors for Dynamic Thematic Maps

2010 ◽  
pp. 16-32 ◽  
Author(s):  
Sarah E. Battersby ◽  
Kirk P. Goldsberry
Keyword(s):  
Spatial Information ◽  
Dynamic Environment ◽  
Communication Process ◽  
Communication Effectiveness ◽  
Thematic Maps ◽  
Research Areas ◽  
Spatiotemporal Information ◽  
Visual Variables ◽  
Map Design ◽  
Research Based Best Practices

Maps provide a means for visual communication of spatial information. The success of this communication process largely rests on the design and symbolization choices made by the cartographer. For static mapmaking we have seen substantial research in how our design decisions can influence the legibility of the map’s message, however, we have limited knowledge about how dynamic maps communicate most effectively. Commonly, dynamic maps communicate spatiotemporal information by 1) displaying known data at discrete points in time and 2) employing cartographic transitions that depict changes that occur between these points. Since these transitions are a part of the communication process, we investigate how three common principles of static map design (visual variables, level of measurement, and classed vs. unclassed data representations) relate to cartographic transitions and their abilities to congruently and coherently represent temporal change in dynamic phenomena. In this review we find that many principles for static map design are less than reliable in a dynamic environment; the principles of static map symbolization and design do not always appear to be effective or congruent graphical representations of change. Through the review it becomes apparent that we are in need of additional research in the communication effectiveness of dynamic thematic maps. We conclude by identifying several research areas that we believe are key to developing research-based best practices for communicating about dynamic geographic processes.

scholarly journals Baby Modula-3 and a theory of objects

1994 ◽  
Vol 4 (2) ◽  
pp. 249-283 ◽  
Author(s):  
Martin Abadi
Keyword(s):  
Programming Language ◽  
Formal Semantics ◽  
Operational Semantics ◽  
Object Oriented ◽  
Denotational Semantics ◽  
Object Oriented Programming ◽  
The Core ◽  
Functional Object ◽  
Oriented Programming Language

AbstractBaby Modula-3 is a small, functional, object-oriented programming language. It is intended as a vehicle for explaining the core of Modula-3 from a biased perspective: Baby Modula-3 includes the main features of Modula-3 related to objects, but not much else. To the theoretician, Baby Modula-3 provides a tractable, concrete example of an object-oriented language, and we use it to study the formal semantics of objects. Baby Modula-3 is defined with a structured operational semantics and with a set of static type rules. A denotational semantics guarantees the soundness of this definition.

scholarly journals Expert Perceptual Behavior under the Spatiotemporal Visual Constraints in Table Tennis

2021 ◽  
Vol 23 (3) ◽  
pp. 3-10
Author(s):  
Ming-Yuan Tang ◽  
Chih-Mei Yang ◽  
Hank Jun-Ling Jwo
Keyword(s):  
Optical Flow ◽  
Spatial Information ◽  
Peak Performance ◽  
Table Tennis ◽  
Tennis Players ◽  
Critical Information ◽  
Spatiotemporal Information ◽  
Visual Constraints ◽  
Perceptual Ability

OBJECTIVES The perceptual ability to detect movement is essential for expert table tennis players. A spatiotemporal occlusion paradigm was employed to examine the critical information that facilitates athletes’ perception.METHODS Thirty-one expert table tennis players, 29 participants and 2 demonstrators, volunteered to participate in the study. Four types of temporal conditions and five types of spatial occlusions were displayed in experimental videos of two opponents playing a table tennis forehand stroke. Period t1–4 represented the four temporal conditions, with 250, 500, 750, and 1000 ms of action being occluded, respectively. The five types of spatial occlusion involved showing the kinematics of only the ball, paddle, arm, trunk, or head. The participants were instructed to judge the landing direction of the ball on the basis of the information in the footage.RESULTS The footage depicted the longest period of play. Furthermore, in separate trials, the spatial information (for the ball, torso, or head) was missing because of occlusion. The absence of such critical spatiotemporal information impaired the ability of players to make an accurate prediction.CONCLUSION Players obtained crucial spatiotemporal information if the timeframe of the video was relatively complete and spatial information on the opponent’s torso and head was available. For peak performance, expert table tennis players perceive and detect the optical flow of the ball’s flight and consider invariant information concerning their opponent’s torso and head.

scholarly journals Information Theoretic Model to Simulate Agent-Signage Interaction for Wayfinding

2019 ◽  
Author(s):  
Rohit K. Dubey ◽  
Tyler Thrash ◽  
Mubbasir Kapadia ◽  
Christoph Hoelscher ◽  
Victor R. Schinazi
Keyword(s):  
Decision Making ◽  
Spatial Information ◽  
Interaction Model ◽  
Training Dataset ◽  
Observation Angle ◽  
Theoretic Model ◽  
Viewing Distance ◽  
Crowd Sourcing ◽  
Signage System ◽  
Perceived Complexity

AbstractSignage systems are critical for communicating spatial information during wayfinding among a plethora of noise in the environment. A proper signage system can improve wayfinding performance and user experience by reducing the perceived complexity of the environment. However, previous models of sign-based wayfinding do not incorporate realistic noise or quantify the reduction in perceived complexity from the use of signage. Drawing upon concepts from information theory, we propose and validate a new agent-signage interaction model that quantifies available wayfinding information from signs for wayfinding. We conducted two online crowd-sourcing experiments to compute the distribution of a sign’s visibility and an agent’s decision-making confidence as a function of observation angle and viewing distance. We then validated this model using a virtual reality (VR) experiment with trajectories from human participants. The crowd-sourcing experiments provided a distribution of decision-making entropy (conditioned on visibility) that can be applied to any sign/environment. From the VR experiment, a training dataset of 30 trajectories was used to refine our model, and the remaining test dataset of 10 trajectories was compared with agent behavior using dynamic time warping (DTW) distance. The results revealed a reduction of 38.76% in DTW distance between the average trajectories before and after refinement. Our refined agent-signage interaction model provides realistic predictions of human wayfinding behavior using signs. These findings represent a first step towards modeling human wayfinding behavior in complex real environments in a manner that can incorporate several additional random variables (e.g., environment layout).

scholarly journals Creating a two-way Land-Use and Transport Interaction model for Budapest

2017 ◽  
Vol 10 (2) ◽  
pp. 99
Author(s):  
M. Juhász ◽  
Cs. Koren
Keyword(s):  
Land Use ◽  
Interaction Model ◽  
Data Availability ◽  
Time Cost ◽  
Limited Data ◽  
Transport Modelling ◽  
Stepping Stone ◽  
Time Period ◽  
Land Use Effects ◽  
The City

This paper intends to show that despite limited data availability it is still possible to elaborate semi-sophisticated LUTI models which can be a stepping stone for countries that are less developed in terms of transport modelling practice but eager to improve. It provides an outline of the model and of the calibrating process which was based on data from the city of Budapest. Based on the results it is undeniable that excluding land-use effects of transport in modelling could cause a serious distortion even in a shorter time period. It seems that such land-use effects and feedbacks can no longer be disregarded as it is not in accordance with the desire of improving transport modelling practice. From this aspect, the proposed approach is practical and can overcome general obstacles of time, cost and data availability issues. The next step should be to carry out tests for the estimation of real transport investments and compare the results with other models.

scholarly journals DETECTING FLU OUTBREAKS BASED ON SPATIOTEMPORAL INFORMATION FROM URBAN SYSTEMS – DESIGNING A NOVEL STUDY

2018 ◽  
Vol XLII-3/W4 ◽  
pp. 231-237
Author(s):  
L. O. Grottenberg ◽  
O. Njå ◽  
E. Tøssebro ◽  
G. S. Braut ◽  
R. Tønnessen ◽  
...  
Keyword(s):  
Real Time ◽  
Spatial Information ◽  
Road Traffic ◽  
Epidemiological Data ◽  
Urban Transport ◽  
Urban Systems ◽  
Transport Systems ◽  
Time Data ◽  
Spatiotemporal Information ◽  
Seasonal Flu

<p><strong>Abstract.</strong> This paper explores the application of real-time spatial information from urban transport systems to understand the outbreak, severity and spread of seasonal flu epidemics from a spatial perspective. We believe that combining travel data with epidemiological data will be the first step to develop a tool to predict future epidemics and to better understand the effects that these outbreaks have on societal functions over time. Real-time data-streams provide a powerful, yet underutilised tool when it comes to monitoring and detecting changes to the daily behaviour of inhabitants.<br> In this paper, we describe and discuss the design of the geospatial project, in which we will draw upon data sources available from the Norwegian cities of Oslo and Bergen. Historical datasets from public transport and road traffic will serve as an initial indication of whether changes in daily transport patterns corresponds to seasonal flu data. It is expected that changes in daily transportation habits corresponds to swings in daily and weekly flu activity and that these differences can be measured through geostatistical analysis. Conceptually one could be able to monitor changes in human behaviour and activity in nearly true time by using indicators derived from outside the clinical health services. This type of more up-to-date and geographically precise information could contribute to earlier detection of flu outbreaks and serve as background for implementing tailor-made emergency response measures over the course of the outbreaks.</p>

Transregional Collaborative Research Center SFB/TR 8 Spatial Cognition: Reasoning, Action, Interaction (Sonderforschungsbereich/Transregio SFB/TR 8 Raumkognition: Schließen, Handeln, Interagieren)

2005 ◽  
Vol 47 (3) ◽  
Author(s):  
Thomas Barkowsky ◽  
John Bateman ◽  
Christian Freksa ◽  
Wolfram Burgard ◽  
Markus Knauff
Keyword(s):  
Spatial Cognition ◽  
Interdisciplinary Research ◽  
Collaborative Research ◽  
Spatial Information ◽  
Research Field ◽  
Cognitive Robotics ◽  
Research Center ◽  
Research Projects ◽  
German Science ◽  
German Science Foundation

SummuryThe Transregional Collaborative Research Center SFB/TR 8 Spatial Cognition was established by the German Science Foundation (DFG) at the Universities of Bremen and Freiburg in January 2003. 13 Research projects pursue interdisciplinary research on intelligent spatial information processing. This article introduces the research field of spatial cognition and reports on aspects from cognitive psychology, cognitive robotics, linguistics, and artificial intelligence.

scholarly journals STS: Spatial–Temporal–Semantic Personalized Location Recommendation

2020 ◽  
Vol 9 (9) ◽  
pp. 538 ◽  
Author(s):  
Wenchao Li ◽  
Xin Liu ◽  
Chenggang Yan ◽  
Guiguang Ding ◽  
Yaoqi Sun ◽  
...  
Keyword(s):  
Spatial Information ◽  
State Of The Art ◽  
Behavior Patterns ◽  
Mobility Patterns ◽  
Displacement Prediction ◽  
Location Recommendation ◽  
Category Information ◽  
Temporal Model ◽  
Location Based Social Network ◽  
Temporal And Spatial

The rapidly growing location-based social network (LBSN) has become a promising platform for studying users’ mobility patterns. Many online applications can be built based on such studies, among which, recommending locations is of particular interest. Previous studies have shown the importance of spatial and temporal influences on location recommendation; however, most existing approaches build a universal spatial–temporal model for all users despite the fact that users always demonstrate heterogeneous check-in behavior patterns. In order to realize truly personalized location recommendations, we propose a Gaussian process based model for each user to systematically and non-linearly combine temporal and spatial information to predict the user’s displacement from their currently checked-in location to the next one. The locations whose distances to the user’s current checked-in location are the closest to the predicted displacement are recommended. We also propose an enhancement to take into account category information of locations for semantic-aware recommendation. A unified recommendation framework called spatial–temporal–semantic (STS) is introduced to combine displacement prediction and the semantic-aware enhancement to provide final top-N recommendation. Extensive experiments over real datasets show that the proposed STS framework significantly outperforms the state-of-the-art location recommendation models in terms of precision and mean reciprocal rank (MRR).

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