Violent and murderous juvenile delinquency born of the phenomenon of young people organized in gangs commonly called “microbes”, has become a real security problem for Ivorian society. It is in this context that thi...Violent and murderous juvenile delinquency born of the phenomenon of young people organized in gangs commonly called “microbes”, has become a real security problem for Ivorian society. It is in this context that this study has set itself the main objective of depicting the psychopathic behavior of a young “microbe” delinquent who has committed several violent crimes. It was a monographic study of the correlational-explanatory type that mobilized observation and semi-directive interviews for the production of data. The method of phenomenological analysis permits to detect traits of psychopathy in a 21-year-old youth through family history and accounts of criminal acts committed. The results of the study showed, on the one hand, a family dysfunction that gave the bed of behaviors such as the lack of empathy, the absence of remorse and the superficiality of the affects, thus translating a deficit on the level of the affective dimension. We also noted the presence of antisocial behavior such as living on the streets or in smoking rooms consuming and selling drugs. There were further implications such as theft, physical aggression and intentional homicide. According to the psychopathy literature, emotional insensitivity juxtaposed with behavior disorder was a primary combination of characteristics that help identify adolescents who exhibit psychopathic traits. Faced with this reality, this study pleads for the establishment of a special aid program to better control the deadly violence of these people.展开更多
Background: Given the scale of juvenile delinquency in Benin, families, judicial bodies and the society seemed overwhelmed. The objective was to study the epidemiological and psychosocial profile of delinquent childre...Background: Given the scale of juvenile delinquency in Benin, families, judicial bodies and the society seemed overwhelmed. The objective was to study the epidemiological and psychosocial profile of delinquent children and adolescents under court order (DCAUCO) in Benin civil prisons in 2015. Methods of study: It was a descriptive and cross-sectional study which involved 117 children aged 11 to 18 years, recruited from 6<sup>th</sup> May to 10<sup>th</sup> September 2015 in nine Civil Prisons and a Child and Adolescent Care Center in Benin. Data were collected through face-to-face interview between the interviewer and the interviewee in addition to ASSIST-WHO, Family Assessment Device and ParentalAcceptance and Rejection Scale. Results: The average age was 16.1 ± 1.1 years, ranging from 11 to 18 years. Sex ratio M/F was 22.4. School dropout rate was 76.9%. Orphans represented 53.9%. The proportion of juvenile offenders coming from broken families was 30.8%. Theft (46.2%) and rape (19.7%) were the main offenses committed. 99.1% had no criminal records and the judge requested for all of them a detention warrant. Psychoactive substance consumption records (46.2%) were found, including: alcohol (46.2%), tobacco (23.9%), and cannabis (10.3%). They felt maternal and paternal absence respectively in 48.7% and 44.4% cases and pleaded guilty in 71.8%. Pleading guilty was a resilience factor on which the counseling would have to rely for their rehabilitation and social reintegration.展开更多
The increasing rate of insecurity in Nigeria, especially the southwest requires a paradigm shift from popular approach to crime hotspots detection. This study employed geospatial technologies to integrate spatio-tempo...The increasing rate of insecurity in Nigeria, especially the southwest requires a paradigm shift from popular approach to crime hotspots detection. This study employed geospatial technologies to integrate spatio-temporal crime, social media and field observation data from the communities in all the six states in the southwest to develop crime hotspots that can serve as preliminary information to assist in allocating resources for crime control and prevention. Historical crime data from January 1972 to April, 2021 were compiled and updated with rigorous field survey in September, 2021. The field data were encoded, input to the SPSS 17 and analyzed using descriptive statistics and multivariate analysis. A total 936 crime locations data were geolocated and exported to ArcGIS 10.5 for spatial mapping using point map operation and further imported to e-Spatial web-based and QGIS for the generation of hotspot map using heatmap tool. The results revealed that armed robbery, assassination and cultism were more pronounced in Lagos and Ogun States. Similarly, high incidences of farmers/herdsmen conflicts are observed in Oyo and Osun States. Increasing incidences of kidnapping are common in all the south-western states but very prominent in Ondo, Lagos and Oyo States. Most of the violent crime incidents took place along the highways, with forests being their hideouts. Violent crimes are dominantly caused by high rate of unemployment while farmer/herdsmen conflicts were majorly triggered by the scarcity of grazing fields and destruction of arable crops. The conflicts have resulted in the increasing cases of rape and disruption of social group, intake of hard drugs, cult-related activities, low income and revenue generation, and displacement of farmers and infrastructural damages. The study advocates regular retraining and equipping of security agents, establishment of cattle ranch, and installation of sophisticated IP Camera at the crime hotspots to assist in real-time crime monitoring and management.展开更多
Iam a judge, working on cases of juvenile delinquency since September 1987. At the same time, I am a mother. Not only my own children call me "mother," but also many of the youngsters whom I have tried and s...Iam a judge, working on cases of juvenile delinquency since September 1987. At the same time, I am a mother. Not only my own children call me "mother," but also many of the youngsters whom I have tried and sentenced. As a mother, I’m sympathetic towards these youngsters who have taken a misstep in life. As a judge,展开更多
Every day,the media reports tons of crimes that are considered by a large number of users and accumulate on a regular basis.Crime news exists on the Internet in unstructured formats such as books,websites,documents,an...Every day,the media reports tons of crimes that are considered by a large number of users and accumulate on a regular basis.Crime news exists on the Internet in unstructured formats such as books,websites,documents,and journals.From such homogeneous data,it is very challenging to extract relevant information which is a time-consuming and critical task for the public and law enforcement agencies.Keyword-based Information Retrieval(IR)systems rely on statistics to retrieve results,making it difficult to obtain relevant results.They are unable to understandthe user’s query and thus facewordmismatchesdue to context changes andthe inevitable semanticsof a given word.Therefore,such datasets need to be organized in a structured configuration,with the goal of efficiently manipulating the data while respecting the semantics of the data.An ontological semantic IR systemis needed that can find the right investigative information and find important clues to solve criminal cases.The semantic system retrieves information in view of the similarity of the semantics among indexed data and user queries.In this paper,we develop anontology-based semantic IRsystemthat leverages the latest semantic technologies including resource description framework(RDF),semantic protocol and RDF query language(SPARQL),semantic web rule language(SWRL),and web ontology language(OWL).We have conducted two experiments.In the first experiment,we implemented a keyword-based textual IR systemusing Apache Lucene.In the second experiment,we implemented a semantic systemthat uses ontology to store the data and retrieve precise results with high accuracy using SPARQL queries.The keyword-based system has filtered results with 51%accuracy,while the semantic system has filtered results with 95%accuracy,leading to significant improvements in the field and opening up new horizons for researchers.展开更多
The objective of crime prediction,one of the most important technologies in social computing,is to extract useful information from many existing criminal records to predict the next process-related crime.It can aid th...The objective of crime prediction,one of the most important technologies in social computing,is to extract useful information from many existing criminal records to predict the next process-related crime.It can aid the police in obtaining criminal information and warn the public to be vigilant in certain areas.With the rapid growth of big data,the Internet of Things,and other technologies,as well as the increasing use of artificial intelligence in forecasting models,crime prediction models based on deep learning techniques are accelerating.Therefore,it is necessary to classify the existing crime prediction algorithms and compare in depth the attributes and conditions that play an essential role in the analysis of crime prediction algorithms.Existing crime prediction methods can be roughly divided into two categories:those based on conventional machine learning and those based on contemporary deep learning.This survey analyses the fundamental theories and procedures.The most frequently used data sets are then enumerated,and the fundamental procedures of various algorithms are also analyzed in this paper.In light of the insufficient scale of existing data in this field,the ambiguity of data types used to predict crimes,and the absence of public data sets that have a significant impact on the research of algorithm models,this survey proposes the construction of a machine learning-based big data research model to address these issues.Future researchers who will enter this field are provided with a guide to the direction of future research development.展开更多
The study examines the Spatial Pattern and Distribution of Crime in Suleja LGA, Niger State, Nigeria. The study used GIS and statistical methods to analyse the pattern and distribution of crime incidence in the study ...The study examines the Spatial Pattern and Distribution of Crime in Suleja LGA, Niger State, Nigeria. The study used GIS and statistical methods to analyse the pattern and distribution of crime incidence in the study area. The records of each crime incidence were geocoded. Microsoft Excel was used to collate and organise the crime entries before they were imported into the ArcGIS Pro 2.0 environment. A geodatabase was created where the spatial and aspatial data were encoded and geospatial analysis was performed. The study reveals that the crime distribution pattern is generally clustered with a Global Moran’s I index of 0.097, a Z-score of 1.87, and a P-value < 0.06. Furthermore, the study reveals that armed robbery (61), kidnapping (40), car theft (33), culpable homicide (31), rape (29), and robbery (13) cases rank the highest in crime rate. Equally, findings of the study show that Chaza, Kwamba, Madalla, Suleja central, and Gaboda are the major crime hotspot zones at 90% confidence, as analysed using the Getis-Ord Gi* (Hot spot analysis) spatial statistics tool in ArcGIS Pro 2.0. The research therefore recommends that more effort be put into fighting crime, especially in areas where there are low-security formations, as they mostly have the highest record of crimes committed. Also, the patrol units should be equipped with GPS for better surveillance and real-time tracking of criminal activities.展开更多
文摘Violent and murderous juvenile delinquency born of the phenomenon of young people organized in gangs commonly called “microbes”, has become a real security problem for Ivorian society. It is in this context that this study has set itself the main objective of depicting the psychopathic behavior of a young “microbe” delinquent who has committed several violent crimes. It was a monographic study of the correlational-explanatory type that mobilized observation and semi-directive interviews for the production of data. The method of phenomenological analysis permits to detect traits of psychopathy in a 21-year-old youth through family history and accounts of criminal acts committed. The results of the study showed, on the one hand, a family dysfunction that gave the bed of behaviors such as the lack of empathy, the absence of remorse and the superficiality of the affects, thus translating a deficit on the level of the affective dimension. We also noted the presence of antisocial behavior such as living on the streets or in smoking rooms consuming and selling drugs. There were further implications such as theft, physical aggression and intentional homicide. According to the psychopathy literature, emotional insensitivity juxtaposed with behavior disorder was a primary combination of characteristics that help identify adolescents who exhibit psychopathic traits. Faced with this reality, this study pleads for the establishment of a special aid program to better control the deadly violence of these people.
文摘Background: Given the scale of juvenile delinquency in Benin, families, judicial bodies and the society seemed overwhelmed. The objective was to study the epidemiological and psychosocial profile of delinquent children and adolescents under court order (DCAUCO) in Benin civil prisons in 2015. Methods of study: It was a descriptive and cross-sectional study which involved 117 children aged 11 to 18 years, recruited from 6<sup>th</sup> May to 10<sup>th</sup> September 2015 in nine Civil Prisons and a Child and Adolescent Care Center in Benin. Data were collected through face-to-face interview between the interviewer and the interviewee in addition to ASSIST-WHO, Family Assessment Device and ParentalAcceptance and Rejection Scale. Results: The average age was 16.1 ± 1.1 years, ranging from 11 to 18 years. Sex ratio M/F was 22.4. School dropout rate was 76.9%. Orphans represented 53.9%. The proportion of juvenile offenders coming from broken families was 30.8%. Theft (46.2%) and rape (19.7%) were the main offenses committed. 99.1% had no criminal records and the judge requested for all of them a detention warrant. Psychoactive substance consumption records (46.2%) were found, including: alcohol (46.2%), tobacco (23.9%), and cannabis (10.3%). They felt maternal and paternal absence respectively in 48.7% and 44.4% cases and pleaded guilty in 71.8%. Pleading guilty was a resilience factor on which the counseling would have to rely for their rehabilitation and social reintegration.
文摘The increasing rate of insecurity in Nigeria, especially the southwest requires a paradigm shift from popular approach to crime hotspots detection. This study employed geospatial technologies to integrate spatio-temporal crime, social media and field observation data from the communities in all the six states in the southwest to develop crime hotspots that can serve as preliminary information to assist in allocating resources for crime control and prevention. Historical crime data from January 1972 to April, 2021 were compiled and updated with rigorous field survey in September, 2021. The field data were encoded, input to the SPSS 17 and analyzed using descriptive statistics and multivariate analysis. A total 936 crime locations data were geolocated and exported to ArcGIS 10.5 for spatial mapping using point map operation and further imported to e-Spatial web-based and QGIS for the generation of hotspot map using heatmap tool. The results revealed that armed robbery, assassination and cultism were more pronounced in Lagos and Ogun States. Similarly, high incidences of farmers/herdsmen conflicts are observed in Oyo and Osun States. Increasing incidences of kidnapping are common in all the south-western states but very prominent in Ondo, Lagos and Oyo States. Most of the violent crime incidents took place along the highways, with forests being their hideouts. Violent crimes are dominantly caused by high rate of unemployment while farmer/herdsmen conflicts were majorly triggered by the scarcity of grazing fields and destruction of arable crops. The conflicts have resulted in the increasing cases of rape and disruption of social group, intake of hard drugs, cult-related activities, low income and revenue generation, and displacement of farmers and infrastructural damages. The study advocates regular retraining and equipping of security agents, establishment of cattle ranch, and installation of sophisticated IP Camera at the crime hotspots to assist in real-time crime monitoring and management.
文摘Iam a judge, working on cases of juvenile delinquency since September 1987. At the same time, I am a mother. Not only my own children call me "mother," but also many of the youngsters whom I have tried and sentenced. As a mother, I’m sympathetic towards these youngsters who have taken a misstep in life. As a judge,
文摘Every day,the media reports tons of crimes that are considered by a large number of users and accumulate on a regular basis.Crime news exists on the Internet in unstructured formats such as books,websites,documents,and journals.From such homogeneous data,it is very challenging to extract relevant information which is a time-consuming and critical task for the public and law enforcement agencies.Keyword-based Information Retrieval(IR)systems rely on statistics to retrieve results,making it difficult to obtain relevant results.They are unable to understandthe user’s query and thus facewordmismatchesdue to context changes andthe inevitable semanticsof a given word.Therefore,such datasets need to be organized in a structured configuration,with the goal of efficiently manipulating the data while respecting the semantics of the data.An ontological semantic IR systemis needed that can find the right investigative information and find important clues to solve criminal cases.The semantic system retrieves information in view of the similarity of the semantics among indexed data and user queries.In this paper,we develop anontology-based semantic IRsystemthat leverages the latest semantic technologies including resource description framework(RDF),semantic protocol and RDF query language(SPARQL),semantic web rule language(SWRL),and web ontology language(OWL).We have conducted two experiments.In the first experiment,we implemented a keyword-based textual IR systemusing Apache Lucene.In the second experiment,we implemented a semantic systemthat uses ontology to store the data and retrieve precise results with high accuracy using SPARQL queries.The keyword-based system has filtered results with 51%accuracy,while the semantic system has filtered results with 95%accuracy,leading to significant improvements in the field and opening up new horizons for researchers.
文摘The objective of crime prediction,one of the most important technologies in social computing,is to extract useful information from many existing criminal records to predict the next process-related crime.It can aid the police in obtaining criminal information and warn the public to be vigilant in certain areas.With the rapid growth of big data,the Internet of Things,and other technologies,as well as the increasing use of artificial intelligence in forecasting models,crime prediction models based on deep learning techniques are accelerating.Therefore,it is necessary to classify the existing crime prediction algorithms and compare in depth the attributes and conditions that play an essential role in the analysis of crime prediction algorithms.Existing crime prediction methods can be roughly divided into two categories:those based on conventional machine learning and those based on contemporary deep learning.This survey analyses the fundamental theories and procedures.The most frequently used data sets are then enumerated,and the fundamental procedures of various algorithms are also analyzed in this paper.In light of the insufficient scale of existing data in this field,the ambiguity of data types used to predict crimes,and the absence of public data sets that have a significant impact on the research of algorithm models,this survey proposes the construction of a machine learning-based big data research model to address these issues.Future researchers who will enter this field are provided with a guide to the direction of future research development.
文摘The study examines the Spatial Pattern and Distribution of Crime in Suleja LGA, Niger State, Nigeria. The study used GIS and statistical methods to analyse the pattern and distribution of crime incidence in the study area. The records of each crime incidence were geocoded. Microsoft Excel was used to collate and organise the crime entries before they were imported into the ArcGIS Pro 2.0 environment. A geodatabase was created where the spatial and aspatial data were encoded and geospatial analysis was performed. The study reveals that the crime distribution pattern is generally clustered with a Global Moran’s I index of 0.097, a Z-score of 1.87, and a P-value < 0.06. Furthermore, the study reveals that armed robbery (61), kidnapping (40), car theft (33), culpable homicide (31), rape (29), and robbery (13) cases rank the highest in crime rate. Equally, findings of the study show that Chaza, Kwamba, Madalla, Suleja central, and Gaboda are the major crime hotspot zones at 90% confidence, as analysed using the Getis-Ord Gi* (Hot spot analysis) spatial statistics tool in ArcGIS Pro 2.0. The research therefore recommends that more effort be put into fighting crime, especially in areas where there are low-security formations, as they mostly have the highest record of crimes committed. Also, the patrol units should be equipped with GPS for better surveillance and real-time tracking of criminal activities.
