PPT-911 Burglary Prevention &

Property crimes Investigations MECC911 Supervisor Maryam Williams 5 th Precinct Property Crimes Lt Lee Edwards Crime Prevention Specialists Amy Lavender amp Chelsea Adams Mecc 911 presentation. 213 Section Introduction: Burglary is the unlawful entry into a private structure for the purposes of committing a crime therein. Note that the second crime need not take place for the requirements & . Property crimes. Investigations. MECC/911 Supervisor. . Maryam Williams. 5. th. Precinct Property Crimes. . Lt Lee Edwards. Crime Prevention Specialists. Amy Lavender & Chelsea Adams. Mecc. Professor Shane D . Johnson. UCL Department of Security and Crime . Science. shane.johnson@ucl.ac.uk. Predicting future patterns. Questions we might ask. How many burglaries are . expected in the next few days?. Unit 4,. . Introduction to Artificial . Intelligence, . Stanford . online course. Made by: Maor Levy, . Temple University 2012. 1. Inference . in Bayes . Nets. What is the probability of getting a strong . Austin Public Safety Commission. March 7, 2011. Introduction. Local neighborhood associations in . Austin have expressed concerns about . an increase in residential burglary. While not “newsworthy,” burglaries . California Criminal Law Concepts . Chapter 14. 1. Mike Reid. LAHC. Elements. Corpus . Delicti. - _____. Does not have to be _______. May be a legal entry as into a store open for business. ____ of person does not have to physically enter structure. A general scenario:. Query . variables:. . X. Evidence . (. observed. ) . variables and their values: . E. = . e. . Unobserved . variables: . Y. . Inference problem. : answer questions about the query variables given the evidence variables. Police Department. Clear . Lake Division. . Captain . J. C. Stevens. . Law Enforcement Sensitive/Official Use Only. Clear Lake Division. 2015. 2016. Change. Murder. 7. 7. 0% . Sexual Assault (RAPE). A general scenario:. Query . variables:. . X. Evidence . (. observed. ) . variables and their values: . E. = . e. . Unobserved . variables: . Y. . Inference problem. : answer questions about the query variables given the evidence variables. December 2016. Today’s objectives. Share . Ulta’s. burglary data. What do the analytics tell us? . Where do we see correlation with risk factors?. Can we predict burglary risk?. What’s worked for Ulta in impacting burglary losses?. picture game . Burglary picture game . What are the main features of 91a and 91b?. game . This task is to test your knowledge of the relevant names and legal principles of cases in Burglary. . Using your mini whiteboards, write the name and the principles of the following case.. 12/1/14-11/30/15. Captain Paul Broxterman. Data Prepared by CRMA Autumn Morris. A Typical Day in District 4. Total number of officers in district 4- . 142. Number of officers assigned to patrol duties- . Stuff from Chapters . 11-14. Thursday: Drugs . Explaining the Violence Drop. ▪ “Usual Suspects”. ▪ Police tactics. ▪ Increase in prison populations . ▪ Economic conditions. ▪ Changes in demographics. A general scenario:. Query . variables:. . X. Evidence . (. observed. ) . variables and their values: . E. = . e. . Unobserved . variables: . Y. . Inference problem. : answer questions about the query variables given the evidence variables.