scholarly journals Spatial-Temporal Sequential Hypergraph Network for Crime Prediction with Dynamic Multiplex Relation Learning

2021 ◽  
Author(s):  
Lianghao Xia ◽  
Chao Huang ◽  
Yong Xu ◽  
Peng Dai ◽  
Liefeng Bo ◽  
...  
Keyword(s):  
Message Passing ◽  
Temporal Dynamics ◽  
Dynamic Environment ◽  
Semantic Relationships ◽  
Global Context ◽  
Fine Grained ◽  
Crime Prediction ◽  
Hypergraph Learning ◽  
Crime Types ◽  
Relation Learning

Crime prediction is crucial for public safety and resource optimization, yet is very challenging due to two aspects: i) the dynamics of criminal patterns across time and space, crime events are distributed unevenly on both spatial and temporal domains; ii) time-evolving dependencies between different types of crimes (e.g., Theft, Robbery, Assault, Damage) which reveal fine-grained semantics of crimes. To tackle these challenges, we propose Spatial-Temporal Sequential Hypergraph Network (ST-SHN) to collectively encode complex crime spatial-temporal patterns as well as the underlying category-wise crime semantic relationships. In specific, to handle spatial-temporal dynamics under the long-range and global context, we design a graph-structured message passing architecture with the integration of the hypergraph learning paradigm. To capture category-wise crime heterogeneous relations in a dynamic environment, we introduce a multi-channel routing mechanism to learn the time-evolving structural dependency across crime types. We conduct extensive experiments on two real-word datasets, showing that our proposed ST-SHN framework can significantly improve the prediction performance as compared to various state-of-the-art baselines. The source code is available at https://github.com/akaxlh/ST-SHN.

Civil sphere and democracy in Latin America

2020 ◽  
pp. 23-40
Author(s):  
Jeffrey Ch. Alexander ◽  
Carlo Tognato
Keyword(s):  
Latin America ◽  
Social Relations ◽  
Political Institutions ◽  
The United States ◽  
Way Of Life ◽  
Global Context ◽  
Fine Grained ◽  
Class Stratification ◽  
Civil Sphere ◽  
The Everyday

The purpose of the article is to demonstrate that the civil spheres of Latin America remain in force, even when under threat, and to expand the method of theorizing democracy, understanding it not only as a state form, but also as a way of life. Moreover, the task of the authors goes beyond the purely application of the theory of the civil sphere in order to emphasize the relevance not only in practice, but also in the theory of democratic culture and institutions of Latin America. This task requires decolonizing the arrogant attitude of North theorists towards democratic processes outside the United States and Europe. The peculiarities of civil spheres in Latin America are emphasized. It is argued that over the course of the nineteenth century the non-civil institutions and value spheres that surrounded civil spheres deeply compromised them. The problems of development that pockmarked Latin America — lagging economies, racial and ethnic and class stratification, religious strife — were invariably filtered through the cultural aspirations and institutional patterns of civil spheres. The appeal of the theory of the civil sphere to the experience of Latin America reveals the ambitious nature of civil society and democracy on new and stronger foundations. Civil spheres had extended significantly as citizens confronted uncomfortable facts, collectively searched for solutions, and envisioned new courses of collective action. However when populism and authoritarianism advance, civil understandings of legitimacy come under pressure from alternative, anti-democratic conceptions of motives, social relations, and political institutions. In these times, a fine-grained understanding of the competitive dynamics between civil, non-civil, and anti-civil becomes particularly critical. Such a vision is constructively applied not only to the realities of Latin America, but also in a wider global context. The authors argue that in order to understand the realities and the limits of populism and polarization, civil sphere scholars need to dive straight into the everyday life of civil communities, setting the civil sphere theory (CST) in a more ethnographic, “anthropological” mode.

Lingering neighbourhood effects: A framework to account for residential histories and temporal dynamics

Urban Studies ◽  
2016 ◽  
Vol 55 (1) ◽  
pp. 151-174 ◽  
Author(s):  
Emily M Miltenburg ◽  
Tom WG van der Meer
Keyword(s):  
Temporal Dynamics ◽  
Single Point ◽  
Population Data ◽  
Blind Spot ◽  
Neighbourhood Effects ◽  
Temporal Dimension ◽  
Individual Level ◽  
Fine Grained ◽  
Conventional Models ◽  
Total Body

The large and growing body of neighbourhood effect studies has almost exclusively neglected individuals’ particular residential histories. Yet, former residential neighbourhoods are likely to have lingering effects beyond those of the current one and are dependent on exposure times and number of moves. This paper tests to what extent this blind spot induced a misestimation of neighbourhood effects for individuals with differential residential histories. Ultimately, we develop a methodological framework for studying the temporal dynamics of neighbourhood effects, capable of dealing with residential histories (moving behaviour, the passage of time and temporal exposure to different neighbourhoods). We apply cross-classified multi-level models (residents nested in current and former neighbourhoods) to analyse longitudinal individual-level population data from Dutch Statistics, covering fine-grained measures of residential histories. Our systematic comparison to conventional models reveals the necessity of including a temporal dimension: our models reveal an overestimation of the effect of the current neighbourhood by 16–30%, and an underestimation of the total body of neighbourhood effects by at least 13–24%. Our results show that neighbourhood effects are lingering, long-lasting and structural and also cannot be confined to a single point in time.

Saliency-based Rhythmic Coordination of Perceptual Predictions

2020 ◽  
Vol 32 (2) ◽  
pp. 201-211 ◽  
Author(s):  
Qiaoli Huang ◽  
Huan Luo
Keyword(s):  
Temporal Dynamics ◽  
Theta Band ◽  
Behavioral Profile ◽  
Fine Grained ◽  
Attentional Process ◽  
Behavioral Measurement ◽  
Processing Resources ◽  
Rhythmic Coordination ◽  
The Brain ◽  
Different Levels

Objects, shown explicitly or held in mind internally, compete for limited processing resources. Recent studies have demonstrated that attention samples locations and objects rhythmically. Interestingly, periodic sampling not only operates over objects in the same scene but also occurs for multiple perceptual predictions that are held in attention for incoming inputs. However, how the brain coordinates perceptual predictions that are endowed with different levels of bottom–up saliency information remains unclear. To address the issue, we used a fine-grained behavioral measurement to investigate the temporal dynamics of processing of high- and low-salient visual stimuli, which have equal possibility to occur within experimental blocks. We demonstrate that perceptual predictions associated with different levels of saliency are organized via a theta-band rhythmic course and are optimally processed in different phases within each theta-band cycle. Meanwhile, when the high- and low-salient stimuli are presented in separate blocks and thus not competing with each other, the periodic behavioral profile is no longer present. In summary, our findings suggest that attention samples and coordinates multiple perceptual predictions through a theta-band rhythm according to their relative saliency. Our results, in combination with previous studies, advocate the rhythmic nature of attentional process.

scholarly journals Examining Deep Learning Architectures for Crime Classification and Prediction

Forecasting ◽  
2021 ◽  
Vol 3 (4) ◽  
pp. 741-762
Author(s):  
Panagiotis Stalidis ◽  
Theodoros Semertzidis ◽  
Petros Daras
Keyword(s):  
Deep Learning ◽  
State Of The Art ◽  
Open Data ◽  
Training Data ◽  
Crime Prediction ◽  
Crime Types ◽  
Improved Performance ◽  
Learning Architectures ◽  
And Training ◽  
Crime Classification

In this paper, a detailed study on crime classification and prediction using deep learning architectures is presented. We examine the effectiveness of deep learning algorithms in this domain and provide recommendations for designing and training deep learning systems for predicting crime areas, using open data from police reports. Having time-series of crime types per location as training data, a comparative study of 10 state-of-the-art methods against 3 different deep learning configurations is conducted. In our experiments with 5 publicly available datasets, we demonstrate that the deep learning-based methods consistently outperform the existing best-performing methods. Moreover, we evaluate the effectiveness of different parameters in the deep learning architectures and give insights for configuring them to achieve improved performance in crime classification and finally crime prediction.

scholarly journals RL mechanisms of short-term plasticity of auditory cortex

2016 ◽  
Author(s):  
Elena Krugliakova ◽  
Alexey Gorin ◽  
Anna Shestakova ◽  
Tommaso Fedele ◽  
Vasily Klucharev
Keyword(s):  
Decision Making ◽  
Auditory Cortex ◽  
Sensory Processing ◽  
Dynamic Environment ◽  
Influential Factors ◽  
Oddball Paradigm ◽  
Fine Grained ◽  
Before And After ◽  
Monetary Incentive Delay ◽  
External Stimuli

AbstractThe decision-making process is exposed to modulatory factors, and, according to the expected value (EV) concept the two most influential factors are magnitude of prospective behavioural outcome and probability of receiving this outcome. The discrepancy between received and predicted outcomes is reflected by the reward prediction error (RPE), which is believed to play a crucial role in learning in dynamic environment. Feedback related negativity (FRN), a frontocentral negative component registered in EEG during feedback presentation, has been suggested as a neural signature of RPE. In modern neurobiological models of decision-making the primary sensory input is assumed to be constant over the time and independent of the evaluation of the option associated to it. In this study we investigated whether the electrophysiological changes in auditory cues perception is modulated by the strengths of reinforcement signal, represented in the EEG as FRN.We quantified the changes in sensory processing through a classical passive oddball paradigm before and after performance a neuroeconomic monetary incentive delay (MID) task. Outcome magnitude and probability were encoded in the physical characteristics of auditory incentive cues. We evaluated the association between individual biomarkers of reinforcement signal (FRN) and the degree of perceptual learning, reflected by changes in auditory ERP components (mismatch negativity and P3a). We observed a significant correlation of MMN and valence - dFRN, reflecting differential processing of gains and omission of gains. Changes in P3a were correlated to probability - dFRN, including information on salience of the outcome, in addition to its valence.MID task performance evokes plastic changes associated with more fine-grained discrimination of auditory anticipatory cues and enhanced involuntary attention switch towards these cues. Observed signatures of neuro-plasticity of the auditory cortex may play an important role in learning and decision-making processes through facilitation of perceptual discrimination of valuable external stimuli. Thus, the sensory processing of options and the evaluation of options are not independent as implicitly assumed by the modern neuroeconomics models of decision-making.

scholarly journals Unified fault-tolerance framework for hybrid task-parallel message-passing applications

2016 ◽  
Vol 32 (5) ◽  
pp. 641-657 ◽  
Author(s):  
Omer Subasi ◽  
Tatiana Martsinkevich ◽  
Ferad Zyulkyarov ◽  
Osman Unsal ◽  
Jesus Labarta ◽  
...  
Keyword(s):  
Fault Tolerance ◽  
Performance Improvement ◽  
Message Passing ◽  
Message Passing Interface ◽  
Fault Tolerant ◽  
Performance Score ◽  
Fine Grained ◽  
Transient Errors ◽  
Task Parallel ◽  
Complete Failure

We present a unified fault-tolerance framework for task-parallel message-passing applications to mitigate transient errors. First, we propose a fault-tolerant message-logging protocol that only requires the restart of the task that experienced the error and transparently handles any message passing interface calls inside the task. In our experiments we demonstrate that our fault-tolerant solution has a reasonable overhead, with a maximum observed overhead of 4.5%. We also show that fine-grained parallelization is important for hiding the overheads related to the protocol as well as the recovery of tasks. Secondly, we develop a mathematical model to unify task-level checkpointing and our protocol with system-wide checkpointing in order to provide complete failure coverage. We provide closed formulas for the optimal checkpointing interval and the performance score of the unified scheme. Experimental results show that the performance improvement can be as high as 98% with the unified scheme.

COMMUNICATION SCHEDULING WITH RE-ROUTING BASED ON STATIC AND HYBRID TECHNIQUES

2004 ◽  
Vol 13 (05) ◽  
pp. 1039-1064
Author(s):  
DAVID R. SURMA ◽  
EDWIN H.-M. SHA ◽  
NELSON PASSOS
Keyword(s):  
Message Passing ◽  
Dynamic Scheduling ◽  
A Priori ◽  
Dynamic Environment ◽  
Graph Model ◽  
Communication Overhead ◽  
Hybrid Technique ◽  
Static Scheduling ◽  
Hybrid Techniques ◽  
Tightly Coupled

In massively parallel systems, the performance gains are often significantly diminished by the inherent communication overhead. This overhead is caused by the required message passing resulting from the task allocation scheme. In this paper, techniques to reduce this communication overhead by both scheduling the communication and determining the routing that the messages should take within a tightly-coupled processor network are presented. Using the recently developed Collision Graph model, static scheduling algorithms are derived which work at compile-time to determine the ordering and routing of the individual message transmissions. Since a priori knowledge about the network traffic required by static scheduling may not be available or accurate, this work also considers dynamic scheduling. A novel hybrid technique is presented which operates in a dynamic environment yet uses known information obtained by analyzing the communication patterns. Experiments performed show significant improvement over baseline techniques.

scholarly journals General hardware multicasting for fine-grained message-passing architectures

2021 ◽  
Author(s):  
Matthew Naylor ◽  
Simon W. Moore ◽  
David Thomas ◽  
Jonathan R. Beaumont ◽  
Shane Fleming ◽  
...  
Keyword(s):  
Message Passing ◽  
Fine Grained
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