Academic literature on the topic 'Recurrent crime'
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Journal articles on the topic "Recurrent crime"
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Filippova, Olga V. "Criminological characteristics of recurrent crime in the Central Federal District of Russia." Current Issues of the State and Law, no. 3 (2022): 394–403. http://dx.doi.org/10.20310/2587-9340-2022-6-3-394-403.
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In the present study, based on criminal statistics data for the period from 2011 to 2021 in Russia and the Central Federal District, an analysis of the state of recurrent crime was carried out, its dynamics, level and structure were determined, territorial features were identified. It is proved that: the level of recurrent crime in the Central Federal District is lower than the national average; recurrent crime occupies a noticeably smaller share in total crime than in Russia as a whole. The structure of recurrent crime in the Central Federal District is characterized by a greater prevalence of crimes against property and against the management order and a lower proportion of crimes against life and health, as well as against road safety and transport operation. Based on this, it is concluded that relapse in this federal district is less dangerous than in other regions. Among the negative trends of recurrent crime in central Russia, there has been a significant increase in recurrent crime in recent years and increased criminal activity of recidivists during the first year after release from prison. In addition, in some regions of Russia there is an increased level of relapse (Tambov, Kostroma regions). This should be taken into account when developing regional prevention programs.
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Tsion, Eshetu Meskela, Kibru Afework Yidnekachew, Asres Ayele Nigus, Wendwosen Teferi Muluken, and Berihun Mengist Tagele. "Designing Time Series Crime Prediction Model using Long Short-Term Memory Recurrent Neural Network." International Journal of Recent Technology and Engineering (IJRTE) 9, no. 4 (2020): 402–5. https://doi.org/10.35940/ijrte.D5025.119420.
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Crime influences people in many ways. Prior studies have shown the relationship between time and crime incidence behavior. This research attempts to determine and examine the relationship between time, crime incidences types and locations by using one of the neural network models for time series data that is, Long Short-Term Memory network. The collected data is pre-processed, analyzed and tested using Long Short-Term Memory recurrent neural network model. R-square score is also used to test the accuracy. The study results show that applying Long Short-Term Memory Recurrent Neural Network (LSTM RNN) enables to come up with more accurate prediction about crime incidence occurrence with respect to time. Predicting crimes accurately helps to improve crime prevention and decision and advance the justice system.
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Wang, Chenyu, Zongyu Lin, Xiaochen Yang, Jiao Sun, Mingxuan Yue, and Cyrus Shahabi. "HAGEN: Homophily-Aware Graph Convolutional Recurrent Network for Crime Forecasting." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 4 (2022): 4193–200. http://dx.doi.org/10.1609/aaai.v36i4.20338.
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The goal of the crime forecasting problem is to predict different types of crimes for each geographical region (like a neighborhood or censor tract) in the near future. Since nearby regions usually have similar socioeconomic characteristics which indicate similar crime patterns, recent state-of-the-art solutions constructed a distance-based region graph and utilized Graph Neural Network (GNN) techniques for crime forecasting, because the GNN techniques could effectively exploit the latent relationships between neighboring region nodes in the graph if the edges reveal high dependency or correlation. However, this distance-based pre-defined graph can not fully capture crime correlation between regions that are far from each other but share similar crime patterns. Hence, to make a more accurate crime prediction, the main challenge is to learn a better graph that reveals the dependencies between regions in crime occurrences and meanwhile captures the temporal patterns from historical crime records. To address these challenges, we propose an end-to-end graph convolutional recurrent network called HAGEN with several novel designs for crime prediction. Specifically, our framework could jointly capture the crime correlation between regions and the temporal crime dynamics by combining an adaptive region graph learning module with the Diffusion Convolution Gated Recurrent Unit (DCGRU). Based on the homophily assumption of GNN (i.e., graph convolution works better where neighboring nodes share the same label), we propose a homophily-aware constraint to regularize the optimization of the region graph so that neighboring region nodes on the learned graph share similar crime patterns, thus fitting the mechanism of diffusion convolution. Empirical experiments and comprehensive analysis on two real-world datasets showcase the effectiveness of HAGEN.
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Filippova, O. V. "The state of recurrent crime in the Siberian federal district." Siberian Law Herald 1 (2023): 72–79. http://dx.doi.org/10.26516/2071-8136.2023.1.72.
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Based on the statistical data of the Ministry of Internal Affairs of the Russian Federation and the Prosecutor General’s Office of the Russian Federation on recidivism in Russia and the Siberian Federal District (hereinafter referred to as the SFD), the main indicators of recidivism crime are determined - the level, structure of the dynamics and conclusions are drawn about the state and trends in the development of recidivism in the SFD and its individual subjects. The article shows that increased rates of recidivism are recorded in the Siberian Federal District, there are differences in the structure of recidivism from all-Russian crime. The conclusion is made about the increased rates of recidivism in the Siberian Federal District and individual subjects included in its composition, the features of the structure of recidivism in the Siberian Federal District and its differences from the all-Russian crime are highlighted. It was found that the volume of recidivism and persons who had previously committed crimes in the Siberian Federal District increased throughout the study period. The proportion of recidivist crimes in the Siberian Federal District in the total number of those investigated is the highest in the country. The largest number of recidivist crimes is registered in the Kemerovo region, Krasnoyarsk and Altai territories, Irkutsk region. The recidivism rate per 100,000 people in the Siberian Federal District is 1.5 times higher than the Russian average; in some subjects of the Siberian Federal District it exceeds the same indicator in the country to an even greater extent (the Republics of Altai, Tyva and Khakassia). It is argued that the most recidivist subjects of the Siberian Federal District are regions with a high level of general crime: the Republics of Tyva, Altai and Khakassia, where recidivism rates are 2-2.5 times higher than the national average, the level of general crime exceeds the Russian indicator by 1.9, 1, 6 and 1.5 times, respectively. In the structure of recidivism in the Siberian Federal District, a large share is occupied by crimes against life and health, as well as crimes against traffic safety and transport operation. In addition, compared with Russian indicators, the Siberian Federal District has a higher proportion of probationers among those who have committed a relapse. In the subjects of the Siberian Federal District, in which the share of crimes against property is higher than the national average, crimes against life and health occupy a relatively small share.
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S. Jeya Selvakumari, V. Joseph Peter. "Crime Classification Using GRU and 1CNN Techniques." Tuijin Jishu/Journal of Propulsion Technology 44, no. 4 (2023): 4792–802. http://dx.doi.org/10.52783/tjjpt.v44.i4.1796.
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Criminal activity is a widespread social problem that affects a nation's standard of living, rate of economic development, and international standing. Numerous crimes have proliferated worldwide in recent years. It has a variety of effects on people of all types. Classification of crime is necessary to create a safe society. Many researchers classify the crimes using machine learning techniques with a common dataset, which presents numerous computational opportunities and challenges. Using the learning capabilities of several deep learning architectures, we are trying to classify the criminal activity from the real-time dataset of particular city. In the proposed work, Gated Recurrent Unit (GRU) and Convolutional Neural Network (1CNN) deep learning architecture are used for crime classification. We have conducted performance comparison for classifying the crime with real-time dataset. The effectiveness of the aforementioned deep learning models was assessed by Training and Validation Loss curve. It was discovered that 1CNN models achieve better result compared to GRU. 1CNN produced 97% accuracy.
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Barbosa, Manuel Fernando Santos, and Luis Manuel Coelho Monteiro. "Recurrent Criminal Behavior and Executive Dysfunction." Spanish Journal of Psychology 11, no. 1 (2008): 259–65. http://dx.doi.org/10.1017/s1138741600004297.
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Objective:To experimentally test the hypothesis that people who repeatedly participate in forms of non-violent crime exhibit an executive deficit detected in tests of high ecological validity, having changes in prefrontal functioning as neurophysiologic basis.Participants and Methods:A battery to assess executive dysfunction was administered – the Behavioural Assessment of the Dysexecutive Syndrome (BADS) –to an experimental group of 30 inmates convicted of crimes against property (mean age = 39.3, SD =9.98), and a control group of 30 (mean age = 32.7, SD = 11.8), all male.Results:The group of recurrent inmates performed significantly worse than the control group in their global scores on the battery, as well as in the majority of subscales.Conclusion:Without removing from consideration the fact that sample size was not very large and, primarily, alerting ourselves to the dangerous hypothesis of a “frontal criminogenesis,” the authors interpret criminal recurrence and resistance to penal measures in terms of the scarcity of control that individuals from the experimental group have over their behavior and its respective consequences.
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Arias Badia, Blanca, and Jenny Brumme. "Subtitling stereotyped discourse in the crime TV series Dexter (2006) and Castle (2009)." Journal of Specialised Translation, no. 22 (July 25, 2014): 110–31. https://doi.org/10.26034/cm.jostrans.2014.364.
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Recurrent communicative events in TV police procedurals, as dictated by genre conventions, lead to the use of recurrent, stereotypical language in these audiovisual products. This paper explores repeated lexicon and syntactic structures (text blocks) from corpse finding and initial forensic analysis, as well as from interrogation sequences in crime TV shows. It also reflects on the extent to which such repetition poses a challenge for subtitlers. The examples for analysis have been taken from the American TV shows Dexter (2006) and Castle (2009). The paper sheds light on how textual recurrence supports recognition of the genre and plot structures and helps to condense, up to a certain degree, the relevant elements of the message in the case of subtitling. As the genre under study is at the crossroads between fiction, specialised discourse and evocation of everyday conversation, this paper combines approaches from different research fields in order to use the most widespread concepts related to recurrence for the benefit of translation studies.
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Perc, Matjaž, Karsten Donnay, and Dirk Helbing. "Understanding Recurrent Crime as System-Immanent Collective Behavior." PLoS ONE 8, no. 10 (2013): e76063. http://dx.doi.org/10.1371/journal.pone.0076063.
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Ofori-Dua, Kwadwo, Nachinaab John Onzaberigu, and Richard Kofi Nimako. "Victims, the Forgotten Party in the Criminal Justices System: The Perception and Experiences of Crime Victims in Kumasi Metropolis in Ghana." Journal of Victimology and Victim Justice 2, no. 2 (2019): 109–28. http://dx.doi.org/10.1177/2516606919885516.
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Crime victims are an integral part of the criminal justice system. There has been recurrent consensus of opinion that without crime victims there can be no effective prosecution. Nevertheless, most studies have been crime-offender-centred. This research explored the experiences of the crime victim in the criminal justice system. Methodologically, this study employed a qualitative technique, face-to-face interviews to collect data. Purposive, snowball, expert sampling techniques were used to select respondents. The study revealed that although most crime victims were satisfied at the reporting stage, they were dissatisfied getting to the end of the criminal justice system process. Victims of offences as robbery and defrauding wanted their monies back after the imprisonment of offender whilst victims of violent crimes like rape, assault and murder want compensation to foot medical bills and other losses they incurred. Victims generally perceive that prosecution and conviction given to perpetrators were not deterring enough. The findings showed that crime victims felt re-victimised by CJS officials; especially because they were not treated with human dignity and the victims had many interesting conceptions of ‘being treated with dignity’ and ‘not being treated with dignity. The study concluded that the CJS should administer justice expeditiously and should be more inclusive.
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Batyrgareieva, Vladislava S., and Sandra Kaija. "Criminal Recidivism Prevention as One of the Determinative Directions of the Agenda of the United Nations Congress on the Prevention of Crime and the Treatment of Offenders." SOCRATES. Rīgas Stradiņa universitātes Juridiskās fakultātes elektroniskais juridisko zinātnisko rakstu žurnāls / SOCRATES. Rīga Stradiņš University Faculty of Law Electronic Scientific Journal of Law 3, no. 15 (2019): 24–36. http://dx.doi.org/10.25143/socr.15.2019.3.024-036.
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Crime structure of any country in the world always has recurrent crime, the scale of which is not amenable to reduction practically. This crime is the most dangerous manifestation of criminal behaviour of a person, because the return of a person to committing new crimes indicates that the measures which were taken to re-socialise them have proved ineffective. Therefore, the problem of criminal recidivism and combating with it occupies a prominent place among issues which are discussed at the level of UN Congresses on the prevention of crime and the treatment of offenders. In the article the provisions of the materials of these Congresses on criminal recidivism and the practice of its prevention are analysed in detail. At the same time, approaches to the calculation of recurrent crimes on the example of separate countries (USA, UK and Ukraine) are clarified. It is concluded that the scale of recidivism because of different methods of counting recurrent crimes is very different in different countries. This leads to the inability to draw a single picture of the prevalence of criminal recidivism in different regions of the world. It is concluded that to achieve appreciable results in the combating recidivism first of all, some methodological issues need to be resolved. One of them should be an attempt at an international level to develop a more or less standardised method of accounting for recidivism in national practices, which would include: firstly, a clear understanding of which offenses should be considered as recurrent; and secondly, the definition of terms based on which quantitative indicators of recidivism are provided. Jebkuras pasaules valsts noziedzības struktūrā vienmēr pastāv recidīvs, kura mērogu praktiski nav iespējams samazināt. Recidīvā noziedzība ir visbīstamākā personas noziedzīgās uzvedības izpausme, jo personas atgriešanās pie jaunu noziedzīgu nodarījumu izdarīšanas liecina, ka pasākumi to socializēšanai ir izrādījušies neefektīvi. Tāpēc recidīva problēma un tā apkarošana ir būtisks jautājums, kas tiek apspriests Apvienoto Nāciju kongresos par noziedzības novēršanu un sankcijām attiecībā uz likumpārkāpējiem. Rakstā analizēti šo kongresu materiāli par noziedzīgo nodarījumu recidīvu un tā novēršanas praksi, raksturotas atsevišķu valstu (ASV, Lielbritānijas un Ukrainas) pieejas noziedzīgo nodarījumu recidīva aprēķināšanā. Secināts, ka dažādās valstīs recidīvisma mērogs atšķirīgu atkārtotu noziegumu skaitīšanas metožu dēļ ir ļoti atšķirīgs. Un tas noved pie tā, ka nav iespējams izveidot vienotu ainu par noziedzīgo nodarījumu recidīva izplatību dažādos pasaules reģionos. Secināts, ka vērā ņemamu rezultātu sasniegšanai recidīva apkarošanā ir jāatrisina daži metodoloģiski jautājumi. Vienam no tiem vajadzētu būt mēģinājumam starptautiskā līmenī izstrādāt vairāk vai mazāk standartizētu recidīvisma uzskaites metodi nacionālajā praksē, kas ietvertu: pirmkārt, skaidri definētu izpratni par to, kuri nodarījumi uzskatāmi par atkārtotiem; un, otrkārt, tādu terminu definēšanu, uz kuru pamata tiek sniegti recidīvisma kvantitatīvie rādītāji.
Dissertations / Theses on the topic "Recurrent crime"
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Holm, Noah, and Emil Plynning. "Spatio-temporal prediction of residential burglaries using convolutional LSTM neural networks." Thesis, KTH, Geoinformatik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-229952.
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The low amount solved residential burglary crimes calls for new and innovative methods in the prevention and investigation of the cases. There were 22 600 reported residential burglaries in Sweden 2017 but only four to five percent of these will ever be solved. There are many initiatives in both Sweden and abroad for decreasing the amount of occurring residential burglaries and one of the areas that are being tested is the use of prediction methods for more efficient preventive actions. This thesis is an investigation of a potential method of prediction by using neural networks to identify areas that have a higher risk of burglaries on a daily basis. The model use reported burglaries to learn patterns in both space and time. The rationale for the existence of patterns is based on near repeat theories in criminology which states that after a burglary both the burgled victim and an area around that victim has an increased risk of additional burglaries. The work has been conducted in cooperation with the Swedish Police authority. The machine learning is implemented with convolutional long short-term memory (LSTM) neural networks with max pooling in three dimensions that learn from ten years of residential burglary data (2007-2016) in a study area in Stockholm, Sweden. The model's accuracy is measured by performing predictions of burglaries during 2017 on a daily basis. It classifies cells in a 36x36 grid with 600 meter square grid cells as areas with elevated risk or not. By classifying 4% of all grid cells during the year as risk areas, 43% of all burglaries are correctly predicted. The performance of the model could potentially be improved by further configuration of the parameters of the neural network, along with a use of more data with factors that are correlated to burglaries, for instance weather. Consequently, further work in these areas could increase the accuracy. The conclusion is that neural networks or machine learning in general could be a powerful and innovative tool for the Swedish Police authority to predict and moreover prevent certain crime. This thesis serves as a first prototype of how such a system could be implemented and used.
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Hickey, Mary Beth, and Karen Eva Smithson. "Risk factors associated with recurrent child maltreatment." CSUSB ScholarWorks, 2005. https://scholarworks.lib.csusb.edu/etd-project/2900.
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The purpose of this study was to identify factors that contribute to the recurrence of child maltreatment within a variety of families. The following discussion addresses the safety and security of children, child protective services, cultural sensitivity, and perception of poverty.
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Singh, Prakash. "Time series forecasting on crime data in Amsterdam for a software company." Master's thesis, 2018. http://hdl.handle.net/10362/57826.
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Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics<br>In recent years, there have been many discussions of data mining technology implementation in the fight against terrorism and crime. Sentient as a software company has been supporting the police for years by applying data mining techniques in the DataDetective application (Sentient, 2017). Experimenting with various types of predictive model solutions, selecting the most efficient and promising solution are the objectives of this internship.
Initially, extended literatures were reviewed in the field of data mining, crime analysis and crime data mining. Sentient provided 7 years of crime data which was aggregated on daily basis to create a univariate dataset. Also, an incidence type daily aggregation was done to create a multivariate dataset. The prediction length for each solution was 7 days. The experiments were divided into two major categories: Statistical models and neural network models. Neural networks outperformed statistical models for the crime data.
This paper provides the overview of statistical models and neural network models used. A comparative study of all the models on similar dataset gives a clear picture of their performance on available data and generalization capability. Evidently, the experiments showed that Gated Recurrent units (GRU) produced better prediction in comparison to other models. In conclusion, gated recurrent unit implementation could give benefit to police in predicting crime. Hence, time series analysis using GRU could be a prospective additional feature in DataDetective.
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Pereira, Susana Ramos. "Relatório de estágio no DIAP da Comarca de Viana do Castelo." Master's thesis, 2018. http://hdl.handle.net/10362/46496.
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This four-month internship was developed in the generic competence section of the DIAP (Department of Investigation and Prossecution) of Viana do Castelo, and my activity was essentially limited to cases related to violent, highly organized and complex crime. This work combines the observation of trials, consultation of cases, analysis of statistical data, interviews with magistrates and several conversations with them, in which doubts were clarified and other issues were discussed. First, I introduce the Public Prosecuter's Office and then I make a framework for the DIAP (structure and organization). I also found relevant, as part of the characterization of the internship's place, to know the type of crime most recurrent in the area and its evolution between the period of 2011-2016. Then, I make a brief presentation of the knowledge seized in the trials assisted and I present questions to the magistrates. Therefore, my investigation consists on verifying the connection between the measures of coercion promoted by the Public Prosecuter’s Office and those that are actually applied by the Public Prosecuter’s Office, but essentially the focus of my study lies in the analysis of some questions that arise regarding the telephone tapping. Lastly, I finish with some conclusions concerning the loss of the useful effect of telephone tapping in the future, given the evolution of the new forms of communication, and I provide a final summary of my experience.<br>Este estágio teve a duração de 4 meses e desenvolveu-se na secção de competência genérica do DIAP de Viana do Castelo, sendo certo que a minha actividade se circunscreveu, essencialmente, aos processos relacionados com a criminalidade violenta, altamente organizada e de especial complexidade. De cariz essencialmente prático, o trabalho aqui apresentado foi o culminar de assistências a julgamentos, consulta de processos, análise de dados estatísticos, entrevistas a magistrados e várias conversas com os mesmos onde dúvidas foram esclarecidas e outras questões foram debatidas. Em primeiro lugar, apresento em que consiste a magistratura do MP e, de seguida, faço um enquadramento do DIAP (estrutura e organização). Também achei relevante, como caracterização do local de estágio, saber qual o tipo de criminalidade mais predominante na comarca e a sua evolução ao longo do período compreendido entre 2011 e 2016. De seguida, faço uma breve apresentação dos conhecimentos apreendidos nos julgamentos assistidos e apresento algumas respostas a questões efectuadas aos magistrados. Posto isto, a minha investigação mais aprofundada consiste na verificação da concordância das medidas de coacção promovidas pelo MP com as que são efectivamente aplicadas pelo MP mas, essencialmente, o enfoque do meu estudo recai na análise de algumas questões que se levantam a propósito das escutas telefónicas. Finalmente, termino com algumas conclusões referentes à perda do efeito útil das escutas telefónicas no futuro, face à evolução das novas formas de comunicação, e faço um balanço final desta minha experiência.
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Champagne, Alexandra. "Caractérisation des comorbidités psychiatriques et comportementales des enfants et des adolescents ayant subi une première crise épileptique." Thèse, 2018. http://hdl.handle.net/1866/22142.
Full textBooks on the topic "Recurrent crime"
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Rock, Paul Elliott. The eternal recurrence of crime and control: Essays in honour of Paul Rock. Oxford University Press, 2010.
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Ameli, Saied Reza. Getting the message: The recurrence of hate crimes in the UK. Islamic Human Rights Commission, 2011.
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Perry, Barbara. Hate Crimes. Praeger, 2009. http://dx.doi.org/10.5040/9798216972020.
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Hate crimes continue to be a pervasive problem in the United States. The murder of Matthew Shepard, the lynching of James Byrd, the murderous rampage of Benjamin Smith, and anti-Muslim violence remind us that incidence of deadly bigotry is not only a recurring chapter in U.S. history, but also a part of our present-day world. Contrary to common belief, hate mongers who commit crimes are rarely members of the Ku Klux Klan or a skinhead group. In fact, fewer than 5 percent of identifiable offenders are members of organized hate groups. Yet rather than being an individual crime, hate crime represents an assault against all members of stigmatized and marginalized communities. To fully understand the phenomenon of hate crime and reduce its incidence, it is necessary to clearly define the term itself, to examine the victims and the offenders, and to evaluate the consequences and harms of hate crimes. This comprehensive five-volume set carefully addresses the disturbing variety and incidence of hate crimes, exposing their impacts on the broader realms of crime, punishment, individual communities, and society. The contributing authors and editors pay critical attention to cutting-edge topics such as online hate crimes, hate-based music, anti-Latino hostilities, Islamaphobia, hate crimes in the War on Terror, school-based anti-hate initiatives, and more. The final volume of Hate Crimes provides valuable food for thought on possible legislative, educational, social policy, or community organizational responses to the varied forms of hate crime.
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Perry, Barbara. Hate Crimes. Praeger, 2009. http://dx.doi.org/10.5040/9798216971986.
Full textAbstract:
Hate crimes continue to be a pervasive problem in the United States. The murder of Matthew Shepard, the lynching of James Byrd, the murderous rampage of Benjamin Smith, and anti-Muslim violence remind us that incidence of deadly bigotry is not only a recurring chapter in U.S. history, but also a part of our present-day world. Contrary to common belief, hate mongers who commit crimes are rarely members of the Ku Klux Klan or a skinhead group. In fact, fewer than 5 percent of identifiable offenders are members of organized hate groups. Yet rather than being an individual crime, hate crime represents an assault against all members of stigmatized and marginalized communities. To fully understand the phenomenon of hate crime and reduce its incidence, it is necessary to clearly define the term itself, to examine the victims and the offenders, and to evaluate the consequences and harms of hate crimes. This comprehensive five-volume set carefully addresses the disturbing variety and incidence of hate crimes, exposing their impacts on the broader realms of crime, punishment, individual communities, and society. The contributing authors and editors pay critical attention to cutting-edge topics such as online hate crimes, hate-based music, anti-Latino hostilities, Islamaphobia, hate crimes in the War on Terror, school-based anti-hate initiatives, and more. The final volume of Hate Crimes provides valuable food for thought on possible legislative, educational, social policy, or community organizational responses to the varied forms of hate crime.
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Perry, Barbara. Hate Crimes. Praeger, 2009. http://dx.doi.org/10.5040/9798216971993.
Full textAbstract:
Hate crimes continue to be a pervasive problem in the United States. The murder of Matthew Shepard, the lynching of James Byrd, the murderous rampage of Benjamin Smith, and anti-Muslim violence remind us that incidence of deadly bigotry is not only a recurring chapter in U.S. history, but also a part of our present-day world. Contrary to common belief, hate mongers who commit crimes are rarely members of the Ku Klux Klan or a skinhead group. In fact, fewer than 5 percent of identifiable offenders are members of organized hate groups. Yet rather than being an individual crime, hate crime represents an assault against all members of stigmatized and marginalized communities. To fully understand the phenomenon of hate crime and reduce its incidence, it is necessary to clearly define the term itself, to examine the victims and the offenders, and to evaluate the consequences and harms of hate crimes. This comprehensive five-volume set carefully addresses the disturbing variety and incidence of hate crimes, exposing their impacts on the broader realms of crime, punishment, individual communities, and society. The contributing authors and editors pay critical attention to cutting-edge topics such as online hate crimes, hate-based music, anti-Latino hostilities, Islamaphobia, hate crimes in the War on Terror, school-based anti-hate initiatives, and more. The final volume of Hate Crimes provides valuable food for thought on possible legislative, educational, social policy, or community organizational responses to the varied forms of hate crime.
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Perry, Barbara. Hate Crimes. Praeger, 2009. http://dx.doi.org/10.5040/9798216972006.
Full textAbstract:
Hate crimes continue to be a pervasive problem in the United States. The murder of Matthew Shepard, the lynching of James Byrd, the murderous rampage of Benjamin Smith, and anti-Muslim violence remind us that incidence of deadly bigotry is not only a recurring chapter in U.S. history, but also a part of our present-day world. Contrary to common belief, hate mongers who commit crimes are rarely members of the Ku Klux Klan or a skinhead group. In fact, fewer than 5 percent of identifiable offenders are members of organized hate groups. Yet rather than being an individual crime, hate crime represents an assault against all members of stigmatized and marginalized communities. To fully understand the phenomenon of hate crime and reduce its incidence, it is necessary to clearly define the term itself, to examine the victims and the offenders, and to evaluate the consequences and harms of hate crimes. This comprehensive five-volume set carefully addresses the disturbing variety and incidence of hate crimes, exposing their impacts on the broader realms of crime, punishment, individual communities, and society. The contributing authors and editors pay critical attention to cutting-edge topics such as online hate crimes, hate-based music, anti-Latino hostilities, Islamaphobia, hate crimes in the War on Terror, school-based anti-hate initiatives, and more. The final volume of Hate Crimes provides valuable food for thought on possible legislative, educational, social policy, or community organizational responses to the varied forms of hate crime.
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Perry, Barbara. Hate Crimes. Greenwood Publishing Group, Inc., 2009. http://dx.doi.org/10.5040/9798216972013.
Full textAbstract:
Hate crimes continue to be a pervasive problem in the United States. The murder of Matthew Shepard, the lynching of James Byrd, the murderous rampage of Benjamin Smith, and anti-Muslim violence remind us that incidence of deadly bigotry is not only a recurring chapter in U.S. history, but also a part of our present-day world. Contrary to common belief, hate mongers who commit crimes are rarely members of the Ku Klux Klan or a skinhead group. In fact, fewer than 5 percent of identifiable offenders are members of organized hate groups. Yet rather than being an individual crime, hate crime represents an assault against all members of stigmatized and marginalized communities. To fully understand the phenomenon of hate crime and reduce its incidence, it is necessary to clearly define the term itself, to examine the victims and the offenders, and to evaluate the consequences and harms of hate crimes. This comprehensive five-volume set carefully addresses the disturbing variety and incidence of hate crimes, exposing their impacts on the broader realms of crime, punishment, individual communities, and society. The contributing authors and editors pay critical attention to cutting-edge topics such as online hate crimes, hate-based music, anti-Latino hostilities, Islamaphobia, hate crimes in the War on Terror, school-based anti-hate initiatives, and more. The final volume of Hate Crimes provides valuable food for thought on possible legislative, educational, social policy, or community organizational responses to the varied forms of hate crime.
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King, Geoff. Arthouse Crime Scenes. Bloomsbury Publishing Plc, 2024. http://dx.doi.org/10.5040/9798765108161.
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How is crime represented in art cinema? And how can this be understood in the context of global sociopolitical and film-industrial trends? Crime might be shown or lurk only at the edges. It might be left unresolved or unexplained. Arthouse crimes can be petty and small scale or raise big questions associated with the arthouse sector: political issues, the nature of humanity, truth and knowability. Arthouse Crime Scenesis the first book to address the relationship between art cinema and crime, contributing to the study of both categories. Case studies are provided of works by celebrated filmmakers including Lucretia Martell, Kleber Mendonça Filho, Bong Joon Ho, Nuri Bilge Ceylan, Hirokazu Kore-eda, Jia Zhangke, Andrey Zvyagintsez and Lee Chang-dong. Textual analysis is combined with focus on social and industrial contexts. A recurring theme is the situation of arthouse crime films within differing manifestations of broader processes of late-modern neoliberal globalization and cultural hybridity. Approaches examined range from the oblique to social realism and other mixtures of crime and arthouse tendencies.
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Black, Donald W. Bad Boys, Bad Men 3rd edition. 3rd ed. Oxford University Press, 2021. http://dx.doi.org/10.1093/med/9780197616918.001.0001.
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This book describes much of what has been learned about antisocial personality disorder (ASPD) and traces the continuing search for answers. Perhaps the best, most concise definition of ASPD comes from psychiatrists Donald Goodwin and Samuel Guze: “Sociopathy (sociopathic personality or antisocial personality) is a pattern of recurrent antisocial, delinquent, or criminal behavior that begins in early childhood or early adolescence and is manifested by disturbances in many areas of life: family relations, schooling, work, military service, and marriage.” Thus, the diagnosis of ASPD relies on a mental health professional’s ability to uncover this pattern and trace it through a patient’s life. The book explores the possibility that ASPD may be at the root of a substantial amount of the troubles that plague society, and that learning more about the disorder might help in fighting crime, violence, and other social ills. It also highlights how ASPD is more common in men than women.
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Newburn, Tim. The Eternal Recurrence of Crime and Control: Essays in Honour of Paul Rock. Edited by David Downes and Dick Hobbs. Oxford University Press, 2010. http://dx.doi.org/10.1093/acprof:oso/9780199580231.001.0001.
Full textBook chapters on the topic "Recurrent crime"
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Wang, Ke, Peidong Zhu, Haoyang Zhu, Pengshuai Cui, and Zhenyu Zhang. "An Interweaved Time Series Locally Connected Recurrent Neural Network Model on Crime Forecasting." In Neural Information Processing. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70139-4_47.
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Fernández-Suárez, Belén. "The Rhetoric of Reaction in Spain: Radical Right, Gender, and Immigration." In IMISCOE Research Series. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-65623-1_2.
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AbstractThis chapter provides an analysis of VOX’s political discourse on gender equality and immigration. VOX belongs to the European radical right and is characterized by conservatism, centralist nationalism, and nativism. The literature reviewed establishes a dialogue between migration studies and gender studies concerning the rise of these traditionalist and nationalist forces in Europe. The objectives are to present VOX’s main arguments on the role of women, gender equality, and immigration in Spain and to explore the relationship between these recurring topics in their political discourse. The methodology is qualitative, grounded on document analysis of VOX materials (program, statutes, founding manifesto) and parliamentary discourses in the Congress of Deputies in the XIII and XIV Legislatures. The results indicate that arguments and proposals regarding immigration seek to strengthen border control, toughen penalties, and consider irregular migration as a crime, targeting Muslim migrants. Regarding gender issues, their nativist vision implies to preserve traditional roles, oppose feminism, and promote natalist policies reinforcing mothers’ roles in caregiving. To conclude, VOX associates Muslim immigration with a perceived thret to women’s freedom in Western countries, link it to sexual crimes against women.
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R., Chitra, Anusha Bamini A. M., Chenthil Jegan T. M., and Padmaveni K. "Anomaly Detection in Biometric Authentication Dataset Using Recurrent Neural Networks." In Advances in Digital Crime, Forensics, and Cyber Terrorism. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-6444-1.ch009.
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In the biometric authentication, the stored data is used for the verification of used identity. The unique biological traits commonly used for biological authentication are facial characteristics, fingerprints, and retinas. It also offers superior fraud detection and customer satisfaction, compared to all other traditional multi factor authentication. Deep learning algorithms plays a major role in anomaly detection and fraud identification in various real-time applications. RNNs have proven that they work well in analysing and detecting anomalies in time series data. RNNs have the unique ability for each cell to have its own memory of all the previous cells before it. This allows for RNNs to process sequential data in time steps which other machine learning models cannot do. RNNs can also be found sorting through your emails to sort out spam and phishing emails from friendly emails. This chapter reviews the methodologies, purposes, results, and the benefits of RNNs in anomaly detection in biometric authentication.
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Rodensky, Lisa. "Prologue to George Eliot’s Crimes." In The Crime in Mind. Oxford University PressNew York, NY, 2003. http://dx.doi.org/10.1093/oso/9780195150735.003.0003.
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Abstract Taking up the distinction between law and morals in The Concept of the Law, H. L. A. Hart explains: The most famous attempt to convey in summary fashion their essential difference is the theory which asserts that, while legal rules only require “external” behavior and are indifferent to the motives, intentions, or other “internal” accompaniments of conduct, morals on the other hand do not require any specific external actions but only a good will or proper intentions or motive. This really amounts to the surprising assertion that legal and moral rules properly understood could not ever have the same content; and though it does contain a hint of truth it is, as it stands, profoundly misleading.... None the less there is something of importance caricatured in this confused argument; the vague sense that the difference between law and morals is connected with the contrast between the “internality” of the one and the “externality” of the other is too recurrent a theme in speculation about law and morals to be altogether baseless.
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Mohanta, Abhinash, Sneha, and Himanshu Sekhar Muduli. "Evaluating Environmental Crimes Through the Prism of Criminological Theories." In Advances in Electronic Government, Digital Divide, and Regional Development. IGI Global, 2023. http://dx.doi.org/10.4018/978-1-6684-7020-6.ch006.
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Humans and society are structured on cyclical routines, recurrent happenings, and patterns. Our brains are so wired for this habit that we frequently detect chaotic patterns when none exist. Environmental crimes are no different—we hear about different forms of environmental crimes on a daily basis. Crimes like poaching, wildlife killing, pollution, artificial forest fires, illegal logging, and the list go long. Addressing the topic academically is necessary to know this particular type of crime, and what triggers the perpetrators to commit such offenses. Criminology has always been supportive as a step towards every social science subject. So, in that sense, it's necessary to learn about environmental crimes through the prism of criminological theories. The chapter provides detailed insight with the help of a systematic review of major criminological theories in environmental crimes. The need for the chapter is crucial because before getting into the paradox of addressing and punishing such crimes, it's necessary to address the genesis of such crimes.
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Zimring, Franklin E., and Gordon Hawkins. "On Mass Media Effects." In Crime Is Not the Problem. Oxford University PressNew York, NY, 1997. http://dx.doi.org/10.1093/oso/9780195110654.003.0008.
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Abstract Mass communications are full of violence because they reflect the interests, values, and concerns of their audience. But do these communications increase the level of real-world violence in the United States as well as reflect it? There is widespread belief that they do. Eight out of ten American adults believe that media renditions of violence are themselves a problem, and the topic is considered important enough to have attracted the attention of Senator Robert Dole of Kansas in the early stages of campaigning for the presidency of the United States (Broder 1995). The issue of mass media effects on violence was one of the small number of topics that generated a full-blown task force investigation by the National Commission appointed by Lyndon Johnson in the late 1960s (U.S. National Commission 1969b:xi). And it has been the subject of recurrent research by behavioral scientists for decades.
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Prideaux, Desirée. "Introduction." In Sleuthing Miss Marple. Liverpool University Press, 2022. http://dx.doi.org/10.3828/liverpool/9781800854642.003.0001.
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The Introduction uncovers a recurrent peculiarity in crime fiction scholarship: Marple is often noted as an ‘obvious exception’ in the masculine world of golden age crime fiction; yet, this observation usually precedes a movement away from consideration of the character. Analysis is informed by the recognition of three striking aspects of the texts. The first is the range and scope of women characters and the gentle subversion of masculine-centred crime fiction which is evident from the earliest stories. The second is Christie’s quite remarkable experimentation with genre. It is widely acknowledged that her engagements with the clue-puzzle pushed the form to its limits; however, Christie’s incursions into other genres, within her crime fictions, are rarely examined. The third is the variety of underhanded ways that Christie devised to grant agency to her spinster-sleuth and other female characters. This substantiates the enquiry into gender, genre, and agency in the Marple mysteries.
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P. Z, Salma, and Maya Mohan. "Detection and Prediction of Spam Emails Using Machine Learning Models." In Handbook of Research on Cyber Crime and Information Privacy. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-5728-0.ch011.
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One of today's important means of communication is email. The extensive use of email for communication has led to many problems. Spam emails being the most crucial among them. It is one the major issues in today's internet world. Spam emails contain mostly advertisements and offensive content, which are often sent without the recipient's request and are generally annoying, time consuming, and wasting space on the communication media's resources. It creates inconveniences and financial loss to the recipients. Hence, there is always the need to filter the spam emails and separate them from the legitimate emails. There are a lot of content-based machine learning techniques that have proven to be effective in detecting and filtering spam emails. Due to a large increase in email spamming, the emails are studied and classified as spam or not spam. In this chapter, three machine learning models, Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Bidirectional LSTM (BLSTM), are used classify the emails as spam and benign.
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Smith, Roger S. "Diversion." In The Oxford Handbook of Evidence-Based Crime and Justice Policy. Oxford University Press, 2024. http://dx.doi.org/10.1093/oxfordhb/9780197618110.013.8.
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Abstract This chapter reviews the emergence and development of youth diversion and addresses the question of how we define and measure its achievements. Recurrent features of diversion are identified, such as the tension between minimum intervention and a preventive program–based approach. This enables us to focus on outcomes (intended and unintended), definitions of success, and how these are measured and evaluated. The chapter initially outlines the history of juvenile/youth diversion in the United Kingdom. Building on this, the chapter considers parallel developments in the United States and internationally, before moving on to report and reflect on the available reported evidence. The chapter develops a critique of evaluation models that concentrate primarily on reoffending as the principal success criterion for diversionary initiatives, and argues instead for approaches to research and evaluation grounded in realist analysis of system effects and wider consequences such as the potential for reinforcing or alternatively challenging discriminatory practices and impacts.
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Sushir, Rupesh D., and Sarita S. Bhutada. "Harnessing Deep Learning for Advanced Video Forensics in Application Software Development." In Advances in Business Information Systems and Analytics. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-4227-5.ch007.
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This chapter explores the integration of deep learning in video forensics, highlighting its effectiveness in large datasets and complex patterns in application software development. Deep learning algorithms are applied to enhance video analysis accuracy and efficiency by detecting, extracting, and interpreting critical information, replacing traditional methods with automated, reliable, and timely results. Advancements in convolutional neural networks, recurrent neural networks, and generative adversarial networks have been explored for image recognition, data analysis, and anomaly detection. This chapter also illustrates the practical applications of deep learning technologies in crime scene investigation, surveillance, and legal proceedings. Deep learning techniques are being integrated into video forensics, enhancing investigative capabilities and precision in digital evidence analysis.
Conference papers on the topic "Recurrent crime"
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Bahnsen, Alejandro Correa, Eduardo Contreras Bohorquez, Sergio Villegas, Javier Vargas, and Fabio A. Gonzalez. "Classifying phishing URLs using recurrent neural networks." In 2017 APWG Symposium on Electronic Crime Research (eCrime). IEEE, 2017. http://dx.doi.org/10.1109/ecrime.2017.7945048.
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Kuzmin, S. S., and A. S. Bukhmastova. "THE ROLE OF ADMINISTRATIVE SUPERVISION IN THE PREVENTION OF RECURRENT CRIME." In Молодежь, наука и цивилизация. Сибирский юридический институт Министерства внутренних дел Российской Федерации, 2018. http://dx.doi.org/10.51980/2018_192_565.
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Zhuang, Yong, Matthew Almeida, Melissa Morabito, and Wei Ding. "Crime Hot Spot Forecasting: A Recurrent Model with Spatial and Temporal Information." In 2017 IEEE International Conference on Big Knowledge (ICBK). IEEE, 2017. http://dx.doi.org/10.1109/icbk.2017.3.
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Benitez-Restrepo, Hernan, and Roger Figueroa. "Anomaly Detection in Surveillance Videos Using Spatio-Temporal Context Information." In LatinX in AI at Computer Vision and Pattern Recognition Conference 2023. Journal of LatinX in AI Research, 2023. http://dx.doi.org/10.52591/lxai2023061810.
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Several computer vision algorithms have been proposed to detect anomalous activities (robberies, murders, vandalism, among others) in videos. According to the learning approach, they can be classified into probabilistic distribution modeling, sparse coding, and deep learning based methods. The main drawbacks of these approaches are (i) extraction of low-level features that do not capture complex behaviors of instances on the scene, (ii) generation of features from irrelevant regions, (iii) overlooking of relationships among objects, and (iv) omission of long-term dependencies. To solve these issues, we propose a deep learning architecture that leverages the relationships among objects. It achieves this by using an attention mechanism and learning long-term dependencies using a multilayer recurrent neural network (multilayer LSTM). An AUC score of 0.749 on the UCF-Crime dataset confirms that the proposed algorithm competes effectively against several state-of-the-art approaches for anomaly detection in surveillance videos. It also explains the relationship between regions in the video frames and the anomaly detections.
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Abd Hasan Naser AL.KHAFAJE, Hawraa. "Measuring the crime of crime in the province of Diyala." In V. International Congress of Humanities and Educational Research. Rimar Academy, 2022. http://dx.doi.org/10.47832/ijhercongress5-7.
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This research is concerned with standing up on questions that are addressed in scientific theatres related to the study of the phenomenon of crime and its spread in a geographical area without jealousy ،which is when a crime is considered endemic in a specific place and not others? Why do they occur somewhere in a relatively constant context? In order to achieve this ،this research focused on finding a tool for measuring and indicating a set of local factors that cause the recurrence of crime in a geographical area without others ،and this prompts the researcher to interpret the spatial variation and temporal recurrence of occurrence in a specific context. The results of the research can draw up curative and preventive policies to reduce the endemic nature of crime ،as its spatial and temporal variation indicates the state of its concentration in certain foci and not others ،unlike the case of convergent spread ،which is explained by the predominance of chaos and crime in the entire study area. Thus ،the temporal recurrence of the occurrence of a crime in a frequent manner close to the average in a specific part of the study area and not in others will be explained by the endemic nature of that crime under study in that place ،and this geographical spot to the exclusion of any other part of the study area. In the part affected by this crime ،the study relied on data for a group of crimes committed in the Diyala Governorate for the period (2007-2017), where a period of time is not short to determine the most endemic crime in the studied area. A crime and its recurrence varied temporally and spatially, where the recurrence of its occurrence in certain proportions or with a recurrence close to the average for the same geographical area and for a period of time not short (at least ten years) indicates that the occurrence is stable ،in other words ،the crime is endemic in that place ،and the reason for that can be explained by local factors Mostly what requires focusing attention and taking care of it As it threatens the security of the community. By determining the two values of the crime rate and the deviation of the values from their rates ،it is easy to derive a coefficient of variation (Coefficient of Variation) through (dividing the value of the standard deviation by the rate and multiplying the result by percent). It fluctuates, and since the value of the covariance coefficient is a percentage (of the average value), it is standard and is used in comparisons between the various variables based on their different values and measures. Therefore, the Endemic Crime Index can be adopted to reveal its location and foci of its spread in the study area.
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Wu, Jie, Wei Zhang, Guanbin Li, et al. "Weakly-Supervised Spatio-Temporal Anomaly Detection in Surveillance Video." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/162.
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In this paper, we introduce a novel task, referred to as Weakly-Supervised Spatio-Temporal Anomaly Detection (WSSTAD) in surveillance video. Specifically, given an untrimmed video, WSSTAD aims to localize a spatio-temporal tube (i.e., a sequence of bounding boxes at consecutive times) that encloses the abnormal event, with only coarse video-level annotations as supervision during training. To address this challenging task, we propose a dual-branch network which takes as input the proposals with multi-granularities in both spatial-temporal domains. Each branch employs a relationship reasoning module to capture the correlation between tubes/videolets, which can provide rich contextual information and complex entity relationships for the concept learning of abnormal behaviors. Mutually-guided Progressive Refinement framework is set up to employ dual-path mutual guidance in a recurrent manner, iteratively sharing auxiliary supervision information across branches. It impels the learned concepts of each branch to serve as a guide for its counterpart, which progressively refines the corresponding branch and the whole framework. Furthermore, we contribute two datasets, i.e., ST-UCF-Crime and STRA, consisting of videos containing spatio-temporal abnormal annotations to serve as the benchmarks for WSSTAD. We conduct extensive qualitative and quantitative evaluations to demonstrate the effectiveness of the proposed approach and analyze the key factors that contribute more to handle this task.
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Sundharakumar, K. B., N. Bhalaji, and M. Muthu Palaniappan. "Spatio Temporal Modelling of Repeat Crimes and Hotspots Prediction Using Recurrent Deep Neural Networks." In 2024 5th International Conference on Innovative Trends in Information Technology (ICITIIT). IEEE, 2024. http://dx.doi.org/10.1109/icitiit61487.2024.10580830.
Full textReports on the topic "Recurrent crime"
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Vignoles, Christopher, and Anneke Jessen. CARICOM Report No. 2 (2005). Inter-American Development Bank, 2005. http://dx.doi.org/10.18235/0008587.
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Economic growth in the Caribbean Community (CARICOM) has been slow in the last two decades, averaging just 1.8 percent a year, compared to annual growth of 3.5 percent in the world economy and 4.3 percent in developing countries. Growth has varied considerably among CARICOM¿s 15 member states, but in most countries it has slowed over the years. The Organization of Eastern Caribbean States (OECS), for example, witnessed above-average growth of 5.4 percent a year in the period 1984-1994, but only 3.3 percent in 1994-1999, and only 1.2 percent in 1999-2004. Of the remaining CARICOM countries, only four have seen accelerated growth in recent years. Unemployment rates are high throughout the region, particularly among younger workers. Apart from slow growth and high unemployment, CARICOM countries face many other problems, among them a high prevalence and rising incidence of HIV/AIDS infections; persistent poverty in several countries of the region; high rates of drug abuse, violence and crime linked to the narcotics trade; and recurring devastation caused by hurricanes and other natural disasters. Meanwhile, the world economy is changing rapidly, requiring huge efforts among the small Caribbean countries to adjust to change while continuing to pursue growth and development.
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Sanahuja, José Antonio, and Andrea Mila-Maldonado. LA INSEGURIDAD CIUDADANA Y LOS RIESGOS PARA LA DEMOCRACIA EN AMÉRICA LATINA. Fundación Carolina, 2024. http://dx.doi.org/10.33960/ac_05.2024.
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América Latina experimenta uno de los momentos más complejos de su historia reciente en términos de descontento y desafección ciudadana hacia la democracia. En relación con ello, varios de sus países han visto aumentar los índices de violencia y homicidios, y hay mayor presencia del crimen organizado, con hechos de violencia sin precedentes. Sin posibilidad de dar respuesta a corto o medio plazo a los problemas estructurales de desigualdad y debilidad institucional, preocupa que líderes, partidos políticos y gobiernos recurran a políticas “de mano dura”, con discursos y prácticas punitivistas, caracterizadas por la espectacularidad, que tienen un fuerte impacto mediático, encuentran altos índices de aprobación de la ciudanía y generan fáciles réditos electorales. Este análisis revisa la correlación entre la inseguridad ciudadana, la insatisfacción de la ciudadanía latinoamericana con el funcionamiento de la democracia, y el apoyo a esta forma de gobierno. Como principal reflexión se concluye que solo el abordaje multisectorial y multidisciplinar permitirá la identificación y el diseño de políticas de seguridad democráticas enmarcadas en el Estado de derecho, sin las que no es posible pensar en la renovación del contrato social en América Latina.