scholarly journals Spatio‐temporal mixed membership models for criminal activity

2021 ◽  
Author(s):  
Seppo Virtanen ◽  
Mark Girolami
Keyword(s):  
Criminal Activity ◽  
Spatio Temporal ◽  
Mixed Membership Models

A STATISTICAL MODEL OF CRIMINAL BEHAVIOR

2008 ◽  
Vol 18 (supp01) ◽  
pp. 1249-1267 ◽  
Author(s):  
M. B. SHORT ◽  
M. R. D'ORSOGNA ◽  
V. B. PASOUR ◽  
G. E. TITA ◽  
P. J. BRANTINGHAM ◽  
...  
Keyword(s):  
Criminal Behavior ◽  
Discrete System ◽  
Continuum Model ◽  
Criminal Activity ◽  
Quantitative Agreement ◽  
Residential Burglary ◽  
Feedback Mechanisms ◽  
Random Walker ◽  
Spatio Temporal ◽  
Parameter Values

Motivated by empirical observations of spatio-temporal clusters of crime across a wide variety of urban settings, we present a model to study the emergence, dynamics, and steady-state properties of crime hotspots. We focus on a two-dimensional lattice model for residential burglary, where each site is characterized by a dynamic attractiveness variable, and where each criminal is represented as a random walker. The dynamics of criminals and of the attractiveness field are coupled to each other via specific biasing and feedback mechanisms. Depending on parameter choices, we observe and describe several regimes of aggregation, including hotspots of high criminal activity. On the basis of the discrete system, we also derive a continuum model; the two are in good quantitative agreement for large system sizes. By means of a linear stability analysis we are able to determine the parameter values that will lead to the creation of stable hotspots. We discuss our model and results in the context of established criminological and sociological findings of criminal behavior.

scholarly journals Spatio-Temporal Modeling of Criminal Activity

2017 ◽  
Author(s):  
Michail Misyrlis ◽  
Chung Ming Cheung ◽  
Ajitesh Srivastava ◽  
Rajgopal Kannan ◽  
Viktor Prasanna
Keyword(s):  
Criminal Activity ◽  
Temporal Modeling ◽  
Spatio Temporal

Self-organised critical hot spots of criminal activity

2010 ◽  
Vol 21 (4-5) ◽  
pp. 371-399 ◽  
Author(s):  
H. BERESTYCKI ◽  
J.-P. NADAL
Keyword(s):  
Law Enforcement ◽  
Hot Spots ◽  
Temporal Dynamics ◽  
Criminal Activity ◽  
Limited Resources ◽  
Minimal Set ◽  
Long Range Interactions ◽  
Spatio Temporal ◽  
Illegal Activities ◽  
High Level

In this paper1 we introduce a family of models to describe the spatio-temporal dynamics of criminal activity. It is argued here that with a minimal set of mechanisms corresponding to elements that are basic in the study of crime, one can observe the formation of hot spots. By analysing the simplest versions of our model, we exhibit a self-organised critical state of illegal activities that we propose to call a warm spot or a tepid milieu2 depending on the context. It is characterised by a positive level of illegal or uncivil activity that maintains itself without exploding, in contrast with genuine hot spots where localised high level or peaks are being formed. Within our framework, we further investigate optimal policy issues under the constraint of limited resources in law enforcement and deterrence. We also introduce extensions of our model that take into account repeated victimisation effects, local and long range interactions, and briefly discuss some of the resulting effects such as hysteresis phenomena.

Visualization of Criminal Activity in an Urban Population

2011 ◽  
pp. 35-49 ◽  
Author(s):  
Alex Bruer ◽  
Joshua J. Hursey ◽  
Arvind Verma
Keyword(s):  
Associated Factors ◽  
Police Department ◽  
Criminal Activity ◽  
Dynamic Activity ◽  
History Of ◽  
Multidimensional Complex ◽  
Spatio Temporal ◽  
Intuitive View ◽  
Temporal Dimensions

Crime is a multidimensional, complex, and dynamic activity. In order to understand its nature one has to comprehend not only its spatio-temporal dimensions, but also the nature of crime, the victim-offender relationship, role of guardians and history of similar previous incidents. This is a formidable task due to the limitations of present visualization methods. Both for the police department and criminal justice researcher the need to visualize a vast amount of data is a prerequisite to the task of dealing with the crime phenomenon. This chapter presents an interactive visualization intended to present the viewer with an accurate and intuitive view of the criminal activity in a cityscape. The technique employs many different visualization elements, which taken together presents a useful methodology that can be used to visualize many of the associated factors of crime. The chapter also presents the software technique and discusses points for future investigation.

scholarly journals The CR‐Ω+ Classification Algorithm for Spatio‐Temporal Prediction of Criminal Activity

2010 ◽  
Vol 8 (01) ◽  
Author(s):  
S Godoy Calderón ◽  
H Calvo ◽  
V M Martínez Hernández ◽  
M A Moreno Armendáriz
Keyword(s):  
Inductive Learning ◽  
Criminal Activity ◽  
Large Data ◽  
Combinatorial Algorithms ◽  
Temporal Prediction ◽  
The Family ◽  
Crime Family ◽  
Activity Behavior ◽  
Spatio Temporal ◽  
Tendency Analysis

We present a spatio‐temporal prediction model that allows forecasting of the criminal activity behavior in a particular region by using supervised classification. The degree of membership of each pattern is interpreted as the forecasted increase or decrease in the criminal activity for the specified time and location. The proposed forecasting model (CR‐Ω+) is based on the family of Kora‐Ω Logical‐Combinatorial algorithms operating on large data volumes from several heterogeneous sources using an inductive learning process. We propose several modifications to the original algorithms by Bongard and Baskakova and Zhuravlëv which improve the prediction performance on the studied dataset of criminal activity. We perform two analyses: punctual prediction and tendency analysis, which show that it is possible to predict punctually one of four crimes to be perpetrated (crime family, in a specific space and time), and 66% of effectiveness in the prediction of the place of crime, despite of the noise of the dataset. The tendency analysis yielded an STRMSE (Spatio‐Temporal RMSE) of less than 1.0.

E3 ubiquitin ligases

2005 ◽  
Vol 41 ◽  
pp. 15-30 ◽  
Author(s):  
Helen C. Ardley ◽  
Philip A. Robinson
Keyword(s):  
Protein Complexes ◽  
Loss Of Function ◽  
Direct Role ◽  
Cellular Processes ◽  
Substrate Protein ◽  
Protein Ubiquitination ◽  
C Terminus ◽  
Full Complement ◽  
Spatio Temporal ◽  
Eukaryotic Organisms

The selectivity of the ubiquitin–26 S proteasome system (UPS) for a particular substrate protein relies on the interaction between a ubiquitin-conjugating enzyme (E2, of which a cell contains relatively few) and a ubiquitin–protein ligase (E3, of which there are possibly hundreds). Post-translational modifications of the protein substrate, such as phosphorylation or hydroxylation, are often required prior to its selection. In this way, the precise spatio-temporal targeting and degradation of a given substrate can be achieved. The E3s are a large, diverse group of proteins, characterized by one of several defining motifs. These include a HECT (homologous to E6-associated protein C-terminus), RING (really interesting new gene) or U-box (a modified RING motif without the full complement of Zn2+-binding ligands) domain. Whereas HECT E3s have a direct role in catalysis during ubiquitination, RING and U-box E3s facilitate protein ubiquitination. These latter two E3 types act as adaptor-like molecules. They bring an E2 and a substrate into sufficiently close proximity to promote the substrate's ubiquitination. Although many RING-type E3s, such as MDM2 (murine double minute clone 2 oncoprotein) and c-Cbl, can apparently act alone, others are found as components of much larger multi-protein complexes, such as the anaphase-promoting complex. Taken together, these multifaceted properties and interactions enable E3s to provide a powerful, and specific, mechanism for protein clearance within all cells of eukaryotic organisms. The importance of E3s is highlighted by the number of normal cellular processes they regulate, and the number of diseases associated with their loss of function or inappropriate targeting.

Elucidating cyclic AMP signaling in subcellular domains with optogenetic tools and fluorescent biosensors

2019 ◽  
Vol 47 (6) ◽  
pp. 1733-1747 ◽  
Author(s):  
Christina Klausen ◽  
Fabian Kaiser ◽  
Birthe Stüven ◽  
Jan N. Hansen ◽  
Dagmar Wachten
Keyword(s):  
Cyclic Amp ◽  
Adenosine Monophosphate ◽  
Adenylyl Cyclases ◽  
Temporal Precision ◽  
Fluorescent Biosensors ◽  
Subcellular Domains ◽  
Spatio Temporal ◽  
Hydrolysis Of ◽  
Shed Light ◽  
Cyclic Amp Signaling

The second messenger 3′,5′-cyclic nucleoside adenosine monophosphate (cAMP) plays a key role in signal transduction across prokaryotes and eukaryotes. Cyclic AMP signaling is compartmentalized into microdomains to fulfil specific functions. To define the function of cAMP within these microdomains, signaling needs to be analyzed with spatio-temporal precision. To this end, optogenetic approaches and genetically encoded fluorescent biosensors are particularly well suited. Synthesis and hydrolysis of cAMP can be directly manipulated by photoactivated adenylyl cyclases (PACs) and light-regulated phosphodiesterases (PDEs), respectively. In addition, many biosensors have been designed to spatially and temporarily resolve cAMP dynamics in the cell. This review provides an overview about optogenetic tools and biosensors to shed light on the subcellular organization of cAMP signaling.

Sign in / Sign up

Export Citation Format

Share Document