scholarly journals Predictive Policing and Crime Control in The United States of America and Europe: Trends in a Decade of Research and the Future of Predictive Policing

2021 ◽  
Vol 10 (6) ◽  
pp. 234
Author(s):  
Ishmael Mugari ◽  
Emeka E. Obioha
Keyword(s):  
Crime Control ◽  
Predictive Accuracy ◽  
Criminal Activity ◽  
The United States ◽  
Modern Technology ◽  
Predictive Policing ◽  
Software Applications ◽  
Predictive Algorithms ◽  
Developed Nations ◽  
Predictive Software

There has been a significant focus on predictive policing systems, as law enforcement agents embrace modern technology to forecast criminal activity. Most developed nations have implemented predictive policing, albeit with mixed reactions over its effectiveness. Whilst at its inception, predictive policing involved simple heuristics and algorithms, it has increased in sophistication in the ever-changing technological environment. This paper, which is based on a literature survey, examines predictive policing over the last decade (2010 to 2020). The paper examines how various nations have implemented predictive policing and also documents the impediments to predictive policing. The paper reveals that despite the adoption of predictive software applications such as PredPol, Risk Terrain Modelling, HunchLab, PreMap, PRECOBS, Crime Anticipation System, and Azevea, there are several impediments that have militated against the effectiveness of predictive policing, and these include low predictive accuracy, limited scope of crimes that can be predicted, high cost of predictive policing software, flawed data input, and the biased nature of some predictive software applications. Despite these challenges, the paper reveals that there is consensus by the majority of the researchers on the importance of predictive algorithms on the policing landscape.

scholarly journals The ethical dangers and merits of predictive policing

2017 ◽  
Vol 2 (1) ◽  
pp. 13 ◽  
Author(s):  
Moish Kutnowski
Keyword(s):  
Law Enforcement ◽  
Justice System ◽  
Criminal Activity ◽  
The United States ◽  
Community Safety ◽  
Ethical Considerations ◽  
Policy Makers ◽  
Predictive Policing ◽  
Traditional Sense ◽  
Potential Opportunity

Predictive policing is an emerging law enforcement technique that uses data and statistical analysis to aid in the identification of criminal activity. Its intention is to proactively reduce crime by providing police forces with likely areas of high risk variables. While this is a noble pursuit, every new tool must be accompanied by the ethical considerations of its potential consequences. Predictive policing is still in its infancy, borne from crime analysis and big data; however, the Western criminal justice system in the traditional sense is a reactive institution with a diverse history. The use of predictive policing presents a new challenge for law enforcement in that it allows for a divergence from the distinct reality of modern policing. Using the United States as an example of the dangers and flaws of predictive policing as a discretionary tool used to justify questionable processes and biases, this paper will analyze the potential opportunity that predictive policing and new holistic forms of law enforcement and community safety initiatives can use in partnerships with communities and policy makers.

Web Services Architecture Model to Support Distributed Systems

2019 ◽  
Vol 54 (6) ◽  
Author(s):  
Sawsan Ali Hamid ◽  
Rana Alauldeen Abdalrahman ◽  
Inam Abdullah Lafta ◽  
Israa Al Barazanchi
Keyword(s):  
Web Services ◽  
Web Service ◽  
Distributed System ◽  
Modern Technology ◽  
Service Description ◽  
Architecture Model ◽  
Software Applications ◽  
Evolving Model ◽  
The Web

Recently, web services have presented a new and evolving model for constructing the distributed system. The meteoric growth of the Web over the last few years proves the efficacy of using simple protocols over the Internet as the basis for a large number of web services and applications. Web service is a modern technology of web, which can be defined as software applications with a programmatic interface based on Internet protocol. Web services became common in the applications of the web by the help of Universal, Description, Discovery and Integration; Web Service Description Language and Simple Object Access Protocol. The architecture of web services refers to a collection of conceptual components in which common sets of standard can be defined among interoperating components. Nevertheless, the existing Web service's architecture is not impervious to some challenges, such as security problems, and the quality of services. Against this backdrop, the present study will provide an overview of these issues. Therefore, it aims to propose web services architecture model to support distributed system in terms of application and issues.

Advanced Technology Programs for Small Turboshaft Engines: Past, Present, Future

1991 ◽  
Vol 113 (1) ◽  
pp. 33-39 ◽  
Author(s):  
E. T. Johnson ◽  
H. Lindsay
Keyword(s):  
United States Army ◽  
High Performance ◽  
The United States ◽  
Modern Technology ◽  
Advanced Technology ◽  
Gas Generator ◽  
Turbine Engine ◽  
Technology Programs ◽  
Aircraft Propulsion System ◽  
Year 2000

This paper addresses approximately 15 years of advanced technology programs sponsored by the United States Army Aviation Applied Technology Directorate and its predecessor organizations and conducted by GE Aircraft Engines (GEAE). Included in these programs is the accomplishment of (1) the 1500 shp demonstrator (GE12), which led to the 1700, and (2) the 5000 shp Modern Technology Demonstrator Engine (MTDE/GE27). Also included are several advanced technology component programs that have been completed or are ongoing through the early 1990s. The goals for the next generation of tri-service small advanced gas generator demonstration programs are shown. A prediction is thus made of the advancements required to fulfill the aircraft propulsion system established by the DoD/NASA Integrated High-Performance Turbine Engine Technology (IHPTET) initiative through the year 2000.

scholarly journals Frontlash: Race and the Development of Punitive Crime Policy

2007 ◽  
Vol 21 (2) ◽  
pp. 230-265 ◽  
Author(s):  
Vesla M. Weaver
Keyword(s):  
United States ◽  
Civil Rights ◽  
Western Europe ◽  
Crime Control ◽  
War On Drugs ◽  
The United States ◽  
Turn Of The Century ◽  
Federal Sentencing Guidelines ◽  
State Supervision ◽  
Capital Crimes

Civil rights cemented its place on the national agenda with the passage of the Civil Rights Act of 1964, fair housing legislation, federal enforcement of school integration, and the outlawing of discriminatory voting mechanisms in the Voting Rights Act of 1965. Less recognized but no less important, the Second Reconstruction also witnessed one of the most punitive interventions in United States history. The death penalty was reinstated, felon disenfranchisement statutes from the First Reconstruction were revived, and the chain gang returned. State and federal governments revised their criminal codes, effectively abolishing parole, imposing mandatory minimum sentences, and allowing juveniles to be incarcerated in adult prisons. Meanwhile, the Law Enforcement Assistance Act of 1965 gave the federal government an altogether new role in crime control; several subsequent policies, beginning with the Crime Control and Safe Streets Act of 1968 and culminating with the Federal Sentencing Guidelines, ‘war on drugs,’ and extension of capital crimes, significantly altered the approach. These and other developments had an exceptional and long-lasting effect, with imprisonment increasing six-fold between 1973 and the turn of the century. Certain groups felt the burden of these changes most acutely. As of the last census, fully half of those imprisoned are black and one in three black men between ages 20 and 29 are currently under state supervision. Compared to its advanced industrial counterparts in western Europe, the United States imprisons at least five times more of its citizens per capita.

Firearm Injuries Affecting the Pediatric Population

PEDIATRICS ◽  
1992 ◽  
Vol 89 (4) ◽  
pp. 788-790
Author(s):  
Keyword(s):  
United States ◽  
Children And Adolescents ◽  
Pediatric Population ◽  
Age Groups ◽  
Unintentional Injury ◽  
The United States ◽  
Male Adolescents ◽  
Firearm Injuries ◽  
Group 2 ◽  
Developed Nations

In the United States approximately 30 000 people die from firearm injuries each year. Many more are wounded. In the mid 1980s, more than 3000 of the dead were children and adolescents aged 1 to 19 years.1 In 1989 nearly 4000 firearm deaths were among children 1 to 19 years of age, accounting for 12% of all deaths in that age group.2 All of these deaths or injuries affect other children because the victims who are killed or wounded are frequently relatives, neighbors, or friends. Comparison data for childhood age groups demonstrate that in 1987, 203 children aged 1 to 9 years, 484 children aged 10 to 14 years, and 2705 adolescents aged 15 to 19 years died as a result of firearm injuries.1 Firearm deaths include unintentional injuries, homicides, and suicides. Among the 1- to 9-year-olds, half of the deaths were homicides and half were unintentional. Among the 10- to 14-year-olds, one third of the deaths were homicides, one third were suicides, and one third were unintentional. Among the 15- to 19-year-olds, 48% were homicides, 42% were suicides, and 8% were unintentional.1 Firearm homicides are the leading cause of death for some US subpopulations, such as urban black male adolescents and young adults.3 Table 1 indicates how firearms contributed to the deaths of children and adolescents (homicides, suicides, and all causes) in 1987. Table 2 illustrates the unusual scale of firearm violence affecting young people in the United States compared with other developed nations.4 Firearm injuries are the fourth leading cause of unintentional injury deaths to children younger than 15 years of age in the US.5

External Validation of the Cardiac Surgery Score in a Quaternary Hospital in the United States of America

2021 ◽  
pp. 088506662110668
Author(s):  
Asha Singh ◽  
Chen Liang ◽  
Stephanie L. Mick ◽  
Chiedozie Udeh
Keyword(s):  
United States ◽  
Cardiac Surgery ◽  
United States Of America ◽  
Predictive Accuracy ◽  
External Validation ◽  
Cleveland Clinic ◽  
Area Under The Curve ◽  
The United States ◽  
Mortality Data ◽  
The Usa

Background The Cardiac Surgery Score (CASUS) was developed to assist in predicting post-cardiac surgery mortality using parameters measured in the intensive care unit. It is calculated by assigning points to ten physiologic variables and adding them to obtain a score (additive CASUS), or by logistic regression to weight the variables and estimate the probability of mortality (logistic CASUS). Both additive and logistic CASUS have been externally validated elsewhere, but not yet in the United States of America (USA). This study aims to validate CASUS in a quaternary hospital in the USA and compare the predictive performance of additive to logistic CASUS in this setting. Methods Additive and logistic CASUS (postoperative days 1-5) were calculated for 7098 patients at Cleveland Clinic from January 2015 to February 2017. 30-day mortality data were abstracted from institutional records and the Death Registries for Ohio State and the Centers for Disease Control. Given a low event rate, model discrimination was assessed by area under the curve (AUROC), partial AUROC (pAUC), and average precision (AP). Calibration was assessed by curves and quantified using Harrell's Emax, and Integrated Calibration Index (ICI). Results 30-day mortality rate was 1.37%. For additive CASUS, odds ratio for mortality was 1.41 (1.35-1.46, P <0.001). Additive and logistic CASUS had comparable pAUC and AUROC (all >0.83). However, additive CASUS had greater AP, especially on postoperative day 1 (0.22 vs. 0.11). Additive CASUS had better calibration curves, and lower Emax, and ICI on all days. Conclusions Additive and logistic CASUS discriminated well for postoperative 30-day mortality in our quaternary center in the USA, however logistic CASUS under-predicted mortality in our cohort. Given its ease of calculation, and better predictive accuracy, additive CASUS may be the preferred model for postoperative use. Validation in more typical cardiac surgery centers in the USA is recommended.

scholarly journals Project Tycho 2.0: a repository to improve the integration and reuse of data for global population health

2018 ◽  
Vol 25 (12) ◽  
pp. 1608-1617 ◽  
Author(s):  
Willem G van Panhuis ◽  
Anne Cross ◽  
Donald S Burke
Keyword(s):  
United States ◽  
Global Health ◽  
The United States ◽  
Health Data ◽  
Digital Object Identifier ◽  
Software Applications ◽  
Open Access Database ◽  
Fair Principles ◽  
Version 2.0 ◽  
Conference Papers

Abstract Objective In 2013, we released Project Tycho, an open-access database comprising 3.6 million counts of infectious disease cases and deaths reported for over a century by public health surveillance in the United States. Our objective is to describe how Project Tycho version 1 (v1) data has been used to create new knowledge and technology and to present improvements made in the newly released version 2.0 (v2). Materials and Methods We analyzed our user database and conducted online searches to analyze the use of Project Tycho v1 data. For v2, we added new US data and dengue data for other countries, and grouped data into 360 datasets, each with a digital object identifier and rich metadata. In addition, we used standard vocabularies to encode data where possible, improving compliance with FAIR (findable, accessible, interoperable, reusable) guiding principles for data management. Results Since release, 3174 people have registered to use Project Tycho data, leading to 18 new peer-reviewed papers and 27 other creative works, such as conference papers, student theses, and software applications. Project Tycho v2 comprises 5.7 million counts of infectious diseases in the United States and of dengue-related conditions in 98 additional countries. Discussion Project Tycho v2 contributes to improving FAIR compliance of global health data, but more work is needed to develop community-accepted standard representations for global health data. Conclusion FAIR principles are a valuable guide for improving the integration and reuse of data in global health to improve disease control and save lives.

scholarly journals Unfolding Algorithms

2019 ◽  
Vol 32 (4) ◽  
pp. 119-136
Author(s):  
Bilel Benbouzid
Keyword(s):  
Machine Learning ◽  
Research Field ◽  
Machine Learning Algorithms ◽  
Moral Vision ◽  
Predictive Policing ◽  
Method Of Calculation ◽  
Predictive Algorithms ◽  
Cautious Interpretation ◽  
The University ◽  
Two Sides

Predictive policing is a research field whose principal aim is to develop machines for predicting crimes, drawing on machine learning algorithms and the growing availability of a diversity of data. This paper deals with the case of the algorithm of PredPol, the best-known startup in predictive policing. The mathematicians behind it took their inspiration from an algorithm created by a French seismologist, a professor in earth sciences at the University of Savoie. As the source code of the PredPol platform is kept inaccessible as a trade secret, the author contacted the seismologist directly in order to try to understand the predictions of the company’s algorithm. Using the same method of calculation on the same data, the seismologist arrived at a different, more cautious interpretation of the algorithm's capacity to predict crime. How were these predictive analyses formed on the two sides of the Atlantic? How do predictive algorithms come to exist differently in these different contexts? How and why is it that predictive machines can foretell a crime that is yet to be committed in a California laboratory, and yet no longer work in another laboratory in Chambéry?  In answering these questions, I found that machine learning researchers have a moral vision of their own activity that can be understood by analyzing the values and material consequences involved in the evaluation tests that are used to create the predictions.

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