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Journal articles on the topic 'Crime analysis'
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1
Evtushenko, I. I. "SITUATION AND ANALYSIS OF CRIMES AGAINST PROPERTY IN THE REPUBLIC OF CRIMEA (FOR THE PERIOD FROM 2015 TO 2020)." Scientific Notes of V. I. Vernadsky Crimean Federal University. Juridical science 7 (73), no. 3 (1) (2022): 170–80. http://dx.doi.org/10.37279/2413-1733-2021-7-3(1)-170-180.
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A criminological analysis of the situation and dynamics of crime against property in the Republic of Crimea (for the period from 2015 to 2020) in comparison with all-Russian indicators and indicators of the Southern Federal District was carried out, similar features and differences were identified, an attempt was made to study the causal complex, events in the Republic of Crimea that could affect the dynamics and level of mercenary crime in different periods of time. The analysis was carried out for each type of crimes against property provided for by the Criminal Code of the Russian Federation, in their interrelation, as well as an analysis of the situation as a whole. In this connection, the author analyzed crimes against property according to two criminological indicators: the dynamics is an absolute indicator of the total number of registered acts for the period from 2015 to 2020 inclusive, and the level is a relative indicator of a particular type of crime in the overall crime structure. This approach allowed us to objectively study the criminological indicators of certain types of crimes against property and draw general conclusions, identify patterns that determine the development of the criminal situation in the field of mercenary crime in the Republic of Crimea.
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Kumrinisa, Abdurasulova. "ANALYSIS OF QUANTITATIVE AND QUALITATIVE INDICATORS OF WOMEN'S CRIME." International Journal of Law And Criminology 3, no. 12 (December 1, 2023): 16–22. http://dx.doi.org/10.37547/ijlc/volume03issue12-04.
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The article provides an analysis of the quantitative and qualitative features of female crime. The socio-psychological determinants of female criminal activity are given. The main types of crimes committed by women are considered. The emphasis is placed on the fact that preventing violent crime among women is an important factor in curbing crime in general. The crime of women differs from the crime of men in its quantitative indicators, the nature of the crimes and their consequences, the methods and instruments of commission, the role played by women,the choice of the victim of a criminal attack, the influence of family and household circumstances and accompanying circumstances on the crime.
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Swamy, Mr K. K., Mrs SRILATHA PULI, S. SWETHA, B. SHARANYA, A. ANUHYA, and J. SHREYAS. "CRIME ANALYSIS USING MACHINE LEARNING." YMER Digital 21, no. 05 (May 10, 2022): 412–16. http://dx.doi.org/10.37896/ymer21.05/44.
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Crimes are the significant threat to the humankind. as crimes are increasing at a rapid rate approach for identifying trends in crime. Our project can predict regions which have high probability for crime occurrence and can visualize crime prone areas by visual representation of data by bar graphs, pie charts etc. It speed up the classification of criminal activities by calculating the average accuracy rate .It uses crime data set and predicts the types of crimes in a particular area which help in Accurate results based on the predictive analysis of logistic regression. The objective would be train a model for prediction using logistic regression classification algorithm. Logistic regression used for classification problems and it is a predictive analysis algorithm based on concept of probability. Crime analysis project is a systematic approach for identifying trends in crime. .It uses crime data set and predicts the types of crimes in a particular area which help in Accurate results based on the predictive analysis of logistic regression.
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Lakušić, Milovan, Sofija Lolić, and Julijana Račić. "Analysis and assessment of money laundering risks." Megatrend revija 19, no. 3 (2022): 171–82. http://dx.doi.org/10.5937/megrev2202171l.
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In this paper, money laundering is primarily highlighted as a crime, the concept and essence of this crime. Due to the prevalence of this crime, at the national and international level, the chapter is dedicated to the analysis and assessment of the risk of money laundering, as something that is constantly working on government agencies and international organizations. The crime of money laundering is associated with a large number of crimes against the economy as well as certain corrupt crimes, and it is necessary to determine the degree of danger of other crimes that are committed in order to commit the crime of money laundering. As a crime whose means of execution are constantly adjusted, this crime is most often committed by organized criminal groups, and prevention is extremely important when it comes to this crime.
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Et. al., R. Ananda DhanaLakshmi,. "COMPARATIVE ANALYSIS OF CRIME TYPE PREDICTION." INFORMATION TECHNOLOGY IN INDUSTRY 9, no. 2 (April 11, 2021): 963–67. http://dx.doi.org/10.17762/itii.v9i2.437.
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Crime analysis and prediction is a logical approach for analysing and identifying different patterns, relationships and trends in crime. The system can predict the area which have high probability for crime occurrence and indicate crime prone areas. It will be useful for the law enforcement agencies to speed up the process of solving crimes with the increasing computerized systems and with the help of crime data analysts. Here we have an approach between computer science and criminal justice to develop a data mining procedure that can help solve crimes faster. Analysis of police data createawareness that lets officers track criminal activities, predict the incidents, effectively deploy resources and solve cases faster. In this paper crime analysis is done by k-means,Spectral clustering and Agglomerative clustering on the crime dataset.
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Lama, Swikar, and Sikandar Singh Rathore. "Crime Mapping and Crime Analysis of Property Crimes in Jodhpur." International Annals of Criminology 55, no. 2 (November 2017): 205–19. http://dx.doi.org/10.1017/cri.2017.11.
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AbstractThis study is based on crime mapping and crime analysis of property crimes in Jodhpur. The property crimes which were selected were house breaking, auto thefts and chain snatching. Data from police stations were used to generate the maps to locate hot spots of crimes. The profile of these hot spots was analyzed through observations supplemented with interviews of police officers and public 100 cases of house breaking and 100 cases of auto thefts were further analyzed to understand the contexts which lead to these crimes. These contexts are in consonance with situational crime prevention theories. This study may help to understand the environmental factors which may be responsible for certain places becoming hot spot areas of property crimes in Jodhpur.
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Lee, Jiyoung, Michael Leitner, and Gernot Paulus. "Spatiotemporal Analysis of Nighttime Crimes in Vienna, Austria." ISPRS International Journal of Geo-Information 13, no. 7 (July 10, 2024): 247. http://dx.doi.org/10.3390/ijgi13070247.
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Studying the spatiotemporal dynamics of crime is crucial for accurate crime geography research. While studies have examined crime patterns related to weekdays, seasons, and specific events, there is a noticeable gap in research on nighttime crimes. This study focuses on crimes occurring during the nighttime, investigating the temporal definition of nighttime crime and the correlation between nighttime lights and criminal activities. The study concentrates on four types of nighttime crimes, assault, theft, burglary, and robbery, conducting univariate and multivariate analyses. In the univariate analysis, correlations between nighttime crimes and nighttime light (NTL) values detected in satellite images and between streetlight density and nighttime crimes are explored. The results highlight that nighttime burglary strongly relates to NTL and streetlight density. The multivariate analysis delves into the relationships between each nighttime crime type and socioeconomic and urban infrastructure variables. Once again, nighttime burglary exhibits the highest correlation. For both univariate and multivariate regression models the geographically weighted regression (GWR) outperforms ordinary least squares (OLS) regression in explaining the relationships. This study underscores the importance of considering the location and offense time in crime geography research and emphasizes the potential of using NTL in nighttime crime analysis.
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Moskaleva, E. G., and N. N. Podol'naya. "CRIMINOLOGICAL ANALYSIS OF ECONOMIC CRIME." Bulletin of Udmurt University. Series Economics and Law 31, no. 1 (February 12, 2021): 117–23. http://dx.doi.org/10.35634/2412-9593-2021-31-1-117-123.
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The article defines the consequences of economic crimes, summarizes the experience of theoretical and empirical studies of crime in the Russian economy, and presents the results of the author's research in this area. The interpretation of the concept of "economic crime" is characterized by legislative, departmental and research approaches. The authors argue that it is difficult to detect crimes in the economic sphere and the high level of latency of economic crime. Data from official statistics of Rosstat and the Prosecutor General's office of the Russian Federation were selected as the empirical base of the study. The research was carried out using methods of visual representation of data, research of dynamics, structure and analysis of relationships in the whole country and in the regional context. The study revealed the main trends in the situation from the point of view of criminalization and de-criminalization of the Russian economy, consisting in slowing down the reduction in the number of crimes in the economy in the Russian Federation. The study identifies regions with an increased level of economic crime and assesses the effectiveness of measures taken to counteract economic crime. The analysis made it possible to determine the directions of countering economic crime in Russia with the mandatory involvement of digital technologies.
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Maurya, Prakash, Tahir Shaikh, Imran Ahmed, Amaan Firdosi, and Prof Kiran Deshmukh. "Crime Analysis and Prediction Using Machine Learning." International Journal for Research in Applied Science and Engineering Technology 11, no. 4 (April 30, 2023): 1470–73. http://dx.doi.org/10.22214/ijraset.2023.50310.
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Abstract: The aim of this study is to develop a machine learning-based application that can analyze crime data across different districts in India and categorize them as high, moderate, or low based on the frequency of crimes. Based on the frequency of particular crimes in particular districts we will suggest necessary preventive measures and also recommend some precautions before visiting a particular crime hotspot. The methodology involved using a Logistic regression model for crime classification, followed by k-means clustering to group districts based on their crime rates. The results of the study demonstrated the efficacy of the machine learning model in accurately classifying crimes. The original contribution of this research lies in the development of an application that provides users with valuable insights into the crime rates in different districts
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Sonali Pakhmode, Vanshita Gaikwad, Bhargavee Talekar, Neha Golatkar, and Vipin Jaiswal. "Regional Crime Data Analysis and Insights Using Fb Prophet." International Research Journal on Advanced Engineering and Management (IRJAEM) 2, no. 05 (May 17, 2024): 1395–401. http://dx.doi.org/10.47392/irjaem.2024.0192.
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Crime is one of the most dominate and formidable aspect of the society. Crimes are committed daily, which has made the lives of the common people restive. Therefore, preventing the crime from occurring can be achieved through a systematic approach by recognizing and evaluating the criminal trends specific to a certain location. Data analysis can assist us to explore former criminal incidents and help us analyze the patterns and hidden correlations which can be used for prevention of crime. Our system aims to analyze crime-prone regions by using the location and time of the crime. Data visualization is a powerful tool for investigating crime rates across the country. Heat maps can be useful for determining the hotspots of crime. The proposed system analyzes the data using the FBprophet model to forecast crime rates in different regions. The Facebook Prophet library, maintained by Facebook, provides forecasting of time series data. This application uses past data and web-scraped data from various sites in order to get detailed studies of various crimes in multiple places. It also enables you to get data about crimes in many places across India by using the pin codes. Government organizations and police departments can effectively utilize it to monitor crime events within a locality.
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Srikanth, H. S. Tanvi. "Crime Pattern Analysis, Visualization and Pridiction Using Data Mining." International Journal for Research in Applied Science and Engineering Technology 9, no. VIII (August 15, 2021): 397–401. http://dx.doi.org/10.22214/ijraset.2021.37323.
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Crime against women these days has become problem of every nation around the globe many countries are trying to curb this problem. Preventive are taken to reduce the increasing number of cases of crime against women. A huge amount of data set is generated every year on the basis of reporting of crime. This data can prove very useful in analyzing and predicting crime and help us prevent the crime to some extent. Crime analysis is an area of vital importance in police department. Study of crime data can help us analyze crime pattern, inter-related clues& important hidden relations between the crimes. That is why data mining can be great aid to analyze, visualize and predict crime using crime data set. Classification and correlation of data set makes it easy to understand similarities & dissimilarities amongst the data objects. We group data objects using clustering technique. Dataset is classified on the basis of some predefined condition. Here grouping is done according to various types of crimes against women taking place in different states and cities of India. Crime mapping will help the administration to plan strategies for prevention of crime, further using data mining technique data can be predicted and visualized in various form in order to provide better understanding of crime patterns.
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Wang, Shaoxuan. "Hate Crime Analysis based on Artificial Intelligence Methods." E3S Web of Conferences 251 (2021): 01062. http://dx.doi.org/10.1051/e3sconf/202125101062.
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Hate crimes always take a toll on American citizens, which harms social security. It is essential for researchers to explore the factors, which lead to hate crimes. This research is to find out the relationship between hate crimes and factors including income inequality, median household income, race using Machine Learning methods. Machine Learning, as an important branch in Artificial Intelligence, is a good way for finding relationships between things. The research is based on a dataset of hate crimes rates in the 2016 U.S. presidential election as well as hate crimes rates in every U.S. state from 2010 to 2015. Simply linear regression and multiple linear regression are used to describe the factors that influence the crime rate and their contributions, such as share of white poverty or share of non-white residents, or the median household income. Then, K-means is applied to classify hate crimes into 5 levels according to the crime rate. Furthermore, KNearest Neighbors is used to demonstrate a prediction of hate crime. At last, a histogram is applied to indicate the variance of the hate crimes in different states. From linear regression, four highest correlation coefficients with a hate crime can be found out, which are income inequality, median household income, the share of noncitizen, and race in turn. Income inequality has the highest correlation coefficient with a hate crime. From multiple linear regression, it can be found out that only by implementing income inequality, median household income, and race can we obtain the highest R square values, which are 0.44 for 2010 to 2015 hate crimes and 0.33 for 2016 hate crimes. From the K-Nearest Neighbors method, hate crimes can be predicted with an accuracy of 40% by applying median household income. Adding the race factor, accuracy rises to 50%. In summary, income inequality, median household income, and race have a high impact on the crime rate. The median household income and the race could predict the crime rate with an accuracy of about 50%.
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Gayratovna, Kamalova Dildora. "LIABILITY FOR PREPARATION TO COMMIT A CRIME IN THE CRIMINAL LEGISLATION OF FOREIGN COUNTRIES (COMPARATIVE LEGAL ANALYSIS)." American Journal of Political Science Law and Criminology 4, no. 12 (December 1, 2022): 36–40. http://dx.doi.org/10.37547/tajpslc/volume04issue12-07.
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The article highlights the issues related to inchoate crimes, preparing for a crime, the basis of liability and punishment for it on the example of foreign countries and national legislation. The author analyzed the issue of liability for preparation of a crime from a comparative legal point of view based on the criminal law of France, the Netherlands, the FRG, Great Britain, and the USA. Based on the study of the criminal legislation of these countries, the author draws a conclusion that in terms of liability for inchoate crimes, there is no criminal liability for preparation for a crime and certain forms of preparation for a crime are considered attempts to commit a crime.
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Scott, Shelby M., and Louis J. Gross. "COVID-19 and crime: Analysis of crime dynamics amidst social distancing protocols." PLOS ONE 16, no. 4 (April 1, 2021): e0249414. http://dx.doi.org/10.1371/journal.pone.0249414.
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In response to the pandemic in early 2020, cities implemented states of emergency and stay at home orders to reduce virus spread. Changes in social dynamics due to local restrictions impacted human behavior and led to a shift in crime dynamics. We analyze shifts in crime types by comparing crimes before the implementation of stay at home orders and the time period shortly after these orders were put in place across three cities. We find consistent changes across Chicago, Baltimore, and Baton Rouge with significant declines in total crimes during the time period immediately following stay at home orders. The starkest differences occurred in Chicago, but in all three cities the crime types contributing to these declines were related to property crime and statutory crime rather than interpersonal crimes.
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Pasaribu, Juhrin. "Juridical Analysis of Criminal Sanctions for Money Laundering Proceeds of Narcotics Crimes." Enigma in Law 2, no. 1 (January 19, 2024): 55–58. http://dx.doi.org/10.61996/law.v2i1.46.
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Money laundering proceeds of narcotics crimes is a criminal offense regulated in Law Number 8 of 2010 concerning prevention and eradication of the crime of money laundering. This crime is a serious crime that can endanger economic stability and state security. Criminal sanctions for laundering money from narcotics crimes are regulated in Article 3 of Law Number 8 of 2010. The criminal sanctions that can be imposed on perpetrators of this crime are in the form of a maximum imprisonment of 20 years and a maximum fine of IDR 10 billion. A juridical analysis of criminal sanctions for laundering money from narcotics crimes needs to be carried out to determine whether these sanctions are in accordance with the objectives of regulating this criminal act. The aim of regulating the crime of money laundering resulting from narcotics crimes is to prevent and eradicate the crime of money laundering, as well as to protect the interests of society and the national economy. Criminal sanctions for laundering money from narcotics crimes are in accordance with the objectives of regulating this crime. These criminal sanctions are preventive and repressive, so they can prevent and eradicate money laundering crimes, as well as provide a deterrent effect to perpetrators.
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Gajendra, Amshu S., Aruna S, and Malini R. "Crime Prediction and Analysis." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (June 30, 2022): 1970–74. http://dx.doi.org/10.22214/ijraset.2022.44218.
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Abstract: Crimes are treacherous social problems which are faced worldwide. It is the most serious and predominant issue of our society. It affects various key features bound to the society and an individual’s life like the quality of life, reputation, economic growth and societal safety. With the advancement of technology there is an enormous growth in the crime rate. There arelaws that have been enforced to take preventive measures but there is a need for advanced approaches for protecting the society and the individuals in the society. Hence analyzing of crime helps in detecting the patterns and trends in crime. The real time crime predictions will be a helping hand to reduce crime rate. Various visualization approaches and algorithms are used in this study to anticipate the distribution of crime in a given area. This paper's pre-processed dataset was obtained from Kaggle. After that, the system is trained using the ARIMA model. The next step is Visualization of data after which the result is predicted after analyzing the data with many machine learning calculations and modules.
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Chauhan, Ritvik, Madan Lal, and Vijay Kumar Baraik. "Geo-Information enabled crime predictive analysis model." National Geographical Journal of India 68, no. 1 (March 31, 2022): 18–40. http://dx.doi.org/10.48008/ngji.1793.
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Crime is a serious threat to society and handicaps it in its normal functioning with full potential. It also hinders the development of a society along with creating hurts of various kinds and degrees. It is, therefore, required to tackle the crime properly for its control and management. Associated with human society with its very existence, it has been evolving with the time in differing magnitudes. Especially, during the contemporary time of rapid technological and societal change, crime has got new types, forms spatial scale with the advent of globalization since 1990. However, the spatial studies on crimes are recent ones despite place plays an important role in understanding and tackling crimes. The sophisticated geospatial tools like Remote Sensing, Geographical Information System and GPS have provided vast scope to map and study crime in relation to space and other aspects of crime. This study focuses on the crime mapping for the years 2001, 2006, and 2012 covering aspects of crimes like changing patterns and trends, seasonality-diurnality, and zonation maps with identification of hotspots using the latest tools of mapping. It also attempts to work on a spatially enabled Predictive Analysis Model using various characteristics and associations. It is expected to provide a base for highlighting the importance of geographical factors in crime analysis, prediction and management for an intelligence system for the past, present and future. This study has utilized both primary as well as secondary data for the geographical analysis in assessing crime pattern in the area of study.
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Jiménez Preciado, Ana Lorena, and Cesar Gurrola Ríos. "Characterising Crime Incidence in Mexico: A Hierarchical Linkage Clustering Analysis." Jurnal Institutions and Economies 14, no. 4 (October 1, 2022): 25–54. http://dx.doi.org/10.22452/ijie.vol14no4.2.
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We aim to characterise the incidence and distribution of crime in 32 states of Mexico. A hierarchical grouping with average linkage is implemented with crime information from DataMéxico, segmented by state and type of crime from 2015 to 2020. Based on the proportional number of crimes over the population of each state, through the elbow method and the average linkage with a Cophenetic correlation coefficient, we validate the number of clusters. Subsequently, a principal component analysis (PCA) is performed to identify each state’s contribution to the clusters proposed. The main results reveal criminal activity can be characterised by three groups. Drug trafficking is the crime that leads the first group, which in turn generates subgroups of interrelated crimes, such as crimes against the family, sexual abuse and harassment, and falsehood, to name a few. These crimes are committed homogeneously in most of the states of the country. Correspondingly, domestic violence and theft lead clusters two and three, and present significant concentration levels since four states accumulate 62% and 55% of crime incidence respectively. The results also provide an overview of how a particular crime can trigger the presence of others.
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Noor, Talal H., Abdulqader M. Almars, Majed Alwateer, Malik Almaliki, Ibrahim Gad, and El-Sayed Atlam. "SARIMA: A Seasonal Autoregressive Integrated Moving Average Model for Crime Analysis in Saudi Arabia." Electronics 11, no. 23 (December 1, 2022): 3986. http://dx.doi.org/10.3390/electronics11233986.
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Crimes have clearly had a detrimental impact on a nation’s development, prosperity, reputation, and economy. The issue of crime has become one of the most pressing concerns in societies, thus reducing the crime rate has become an increasingly critical task. Recently, several studies have been proposed to identify the causes and occurrences of crime in order to identify ways to reduce crime rates. However, few studies have been conducted in Saudi Arabia technological solutions based on crime analysis. The analysis of crime can help governments identify hotspots of crime and monitor crime distribution. This study aims to investigate which Saudi Arabian areas will experience increased crime rates in the coming years. This research helps law enforcement agencies to effectively utilize available resources in order to reduce crime rates. This paper proposes SARIMA model which focuses on identifying factors that affect crimes in Saudi Arabia, estimating a reasonable crime rate, and identifying the likelihood of crime distribution based on various locations. The dataset used in this study is obtained from Saudi Arabian official government channels. There is detailed information related to time and place along with crime statistics pertaining to different types of crimes. Furthermore, the new proposed method performs better than other traditional classifiers such as Linear Regression, XGB, and Random Forest. Finally, SARIMA model has an MAE score of 0.066559, which is higher than the other models.
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Tobias, Chitani Jarves Bob, and Brave Mwanza. "Spatial and Temporal Analysis: A GIS-Based Application Tool for Crime Monitoring and Clustering in Malawi." European Scientific Journal, ESJ 20, no. 8 (March 31, 2024): 167. http://dx.doi.org/10.19044/esj.2024.v20n8p167.
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For the purposes of monitoring, evaluating, and conducting a geographical analysis of crime-related data, the study used geospatial technology to collect crime data based on spatial location and the Malawi Police Data Digest of 2019 and 2020. In a more generic sense, knowing the geographic patterns of crime in Malawi using GIS technology can help determine how to make and implement important decisions to reduce crimes in Malawi. The Malawi Police Service has established a number of database management systems to help with crime monitoring. Notwithstanding, it has not yet fully integrated Geographic Information Systems across all jurisdictions. Maps showing crime locations and crime hotspot zones are therefore not included in the crime data and statistics report provided by the Malawi Police Service. In this light, a lot of people have become victims of various forms of crimes in areas where those crimes are also prevalent. To collect, track, and analyze crime data in Malawi for this study, Geographical Information System (GIS) particularly network analysis techniques were used. Network Analysis was used to identify crime hotspots by analyzing crime data as a network of interconnected events and locations. The rationale behind this was to treat each crime event as a node in the network and the spatial relationships between the crimes as edges. By analyzing this network, patterns and relationships between crime events were revealed, allowing for the identification of crime hotspots. The study found that Lilongwe in the central region and the capital city registered the highest number of crimes seconded by Blantyre in the southern region and followed by Mangochi. Mzimba recorded high crimes in the northern region. In Malawi, the traditional systems of intelligence and criminal record keeping have failed to satisfy the demands of today's crime situation. Manual methods neither give accurate, dependable, or complete data 24 hours a day nor do they help in trend forecasting and decision assistance. It also leads to poorer productivity and inefficient workforce use. The appropriate application of information technology is the solution to this ever-increasing challenge.
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Muça, Valbona. "Domestic Crime – A Sociological Analysis." European Journal of Social Sciences Education and Research 5, no. 1 (December 30, 2015): 402. http://dx.doi.org/10.26417/ejser.v5i1.p402-407.
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After ‘90 years we have often heard and read in social networks for different cases of domestic violence, which in most cases have ended with the murder of one of the couple. Mostly, women are victims of domestic violence. Murder cases have increased, where parents murder their child or the opposite. Different researchers and as a sociologist, psychologist and criminologist or have attempted to study the nature of crime in the Albanian family, have given their opinions to explain the increase of crimes. This article will reflect an explanation of the causes of factors leading to crime to one spouse. It also reflects the way in which treated and protected by law, which in different societies treatments are different laws. Crimes in pairs which can occur because of jealousy, passion or for crimes for honor issues are not peculiar only in Albanian society but are prevalent in all societies.
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신, 재헌. "An Analysis on Foreigner Committed Crimes Covered in Media." Korean Society of Culture and Convergence 44, no. 9 (September 30, 2022): 435–46. http://dx.doi.org/10.33645/cnc.2022.9.44.9.435.
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The purpose of this paper is to analyze the cases of foreigner committed crime covered in media and introduce the seriousness of the crimes committed by foreigners. According to the violent crime analysis results, the violent crimes committed by foreigners were brutal and cruel and involved revenge motive. In addition, the foreign criminals often used weapons, committed crimes in groups, and involved sexual violence crime in the violent form. In case of property crimes, the foreigners committed the property crimes in various forms including voice phishing, illegal overseas remittance, illegal loan business, and job scam. The property crimes targeted both Koreans and foreigners. Unlike other crimes, the property crimes committed by foreigners are often hidden without getting reported. Other crimes committed by foreigners included various cases including production, distribution, consumption of illicit drugs, ID card rental, illegal brokerage, and trafficking of cultural property.
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Smirniotis, Colette, Michael Henderson, Barbara A. Bailey, and Rose M. C. Kagawa. "Crime and Building Rehabilitation or Demolition: A Dose-Response Analysis." International Journal of Environmental Research and Public Health 19, no. 20 (October 11, 2022): 13065. http://dx.doi.org/10.3390/ijerph192013065.
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Thousands of buildings in Cleveland, Ohio were demolished or rehabilitated since the Great Recession in the 2000s. Recent evidence suggests removing vacant and decaying buildings reduces violent and firearm-involved crime. This study examines the dose-response relationship between demolitions, rehabilitations, and crime. We use Bayesian spatiotemporal models to estimate the association of interest for five types of crime outcomes: violent crimes, violent crimes involving a firearm, drug crimes, and crimes often associated with building vacancy. We estimate associations in quarterly time periods from 2012 through 2017 in 569 hexagons approximately the size of a neighborhood (2000 feet, approximately 610 m, in diameter), stratified by vacancy level. Across vacancy levels, the majority of our models do not identify statistically significant associations between demolition and rehabilitation dose and crime incidence. However, in some cases, we identify positive associations between demolition and crime. These associations generally appeared at higher levels of demolition (2 or 3 or more demolitions) in areas characterized by medium to high levels of vacancy. We also find that the presence of a property rehabilitation is associated with an increase in drug crimes in areas with medium levels of vacancy.
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Pleshakov, Vladimir A. "ANALYSIS OF SITUATIONAL CRIME FACTORS." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 7/3, no. 139 (2023): 198–203. http://dx.doi.org/10.36871/ek.up.p.r.2023.07.03.022.
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The article analyzes the factors of situational crime. It is indicated that the main cause of all crimes is the motivation of the individual to commit a crime. A new concept is introduced in the mechanism of individual criminal behavior – opportunities. The concept of subjective and objective possibilities is given. It is indicated that the result of the interaction of these types of opportunities is the “trigger” of criminal encroachment. The place of possibilities in the mechanism of a criminal act is shown. Based on the results of the study, the subjective and objective possibilities of situational criminals are analyzed. At the same time, their interrelation forms a set of situational crime factors. It is indicated that only in situational crime, external factors can form a motive and a decision to commit a crime.
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Kumar, Ayush. "Critical Analysis of the Law Relating to Cyber Crime." International Journal for Research in Applied Science and Engineering Technology 10, no. 11 (November 30, 2022): 2081–82. http://dx.doi.org/10.22214/ijraset.2022.47771.
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Abstract: The Cyber Crime is most popular Crime in the world the Cyber Criminals Crimes are the Committed day by day .This Crime commit the Computer and Internet in this Crime Criminals are hacking the Computer system, Mobile like that Hacking virus ,Worm attacks, DOS attack etc. The personal data are Theft Like that Bank account detail, e-mail, Mobile messages .The computer as a weapon using the computer system to commit real world Crimes like Cyber terrorism, IPR(Intellectual property infringing) contravention, credit card frauds, EFT (Electronic fund transfer) Frauds, Pornography etc. The Cyber Criminals activities to the internet are termed as Cyber Crimes with the increasing popularity of online activity like that online banking and online Sopping In this term hearing the news day by day. The Cyber Crime law of The Cyber Criminals can involves the Crimes activity like that Theft, fraud, forgery, scandal and mischief all of which are the object to the IPC. The Abuse of the computer has also given birth to a scale of new generation Crimes that are addressed by the information technology .The Cyber law is a term used to explain legal issues affined to use of communications technology, particularly cyberspace the Internet.
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Shafique, Iqra, Syeda Ambreen Zahra, Tuba Farid, and Madiha Sharif. "Role of GIS in Crime Mapping & Analysis." Sukkur IBA Journal of Computing and Mathematical Sciences 1, no. 2 (December 31, 2017): 39. http://dx.doi.org/10.30537/sjcms.v1i2.30.
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In most recent years, crime analysis has turned into a broad- spectrum term that needs a considerable measure of research on crime investigation and crime mapping. Study about crime with respect to its spatial and temporal distribution is important because data about crime incident is one of the most urgent need to fight against crime. Crime mapping and analysis plays an integral role in essentially advanced form of crime representation, visualization and respond satisfactorily to the problem of criminality. It also let the analysts to figure out how crimes are spread evenly over the zone. GIS plays an effective role in mapping of crime. This paper puts on the diverse utilities of GIS to recognize the hotspots in addition to encourage the advancement of investigation inclination strategy for policing. The functional approach in the present investigation for crime mapping can be successfully applied for improvement of user-interfaces stage for the advancement of safe city strategies.
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Hola, Barbora, Catrien Bijleveld, and Alette Smeulers. "Punishment for Genocide – Exploratory Analysis of ICTR Sentencing." International Criminal Law Review 11, no. 4 (2011): 745–73. http://dx.doi.org/10.1163/157181211x587193.
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AbstractThe sentencing practice of the International Criminal Tribunal for Rwanda (ICTR) is a relatively neglected topic in academic discussions. The few empirical studies on sentencing of international crimes have focused primarily on the sentencing practice of its 'sister court', the International Criminal Tribunal for the Former Yugoslavia (ICTY). Unlike ICTY defendants, almost all ICTR defendants have been convicted of and sentenced for genocide – arguably the most serious international crime. This empirical study examines the sentencing practice of the ICTR and analyses the relationship between sentence severity and the primary consideration in sentencing – crime gravity. The relevant principles stemming from ICTR case law are reviewed, followed by an examination of the interrelationship between sentence severity and factors relating to crime gravity, such as category of crime, scale of crime and the form and degree of a defendant's involvement in the crime. The ICTR judges appear in most cases to follow the main principles emphasized in their case law, with sentences gradated in line with the increasing seriousness of defendants' crimes and their culpability.
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KA, Kyei, Tshisikhawe TH, and Dube LM. "Different Crime Types in Western Cape Province: Principal Component Analysis." Journal of Economics and Behavioral Studies 8, no. 5(J) (October 30, 2016): 18–26. http://dx.doi.org/10.22610/jebs.v8i5(j).1428.
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South Africa has a very high crime rate compared to most countries. Crime affects the society, business and psychology of the people. It compels people to move out or come into a particular area. It is most prevalent in the urban areas where poverty gap is conspicuous. Western Cape and Gauteng Provinces are the best developed provinces in the country and therefore have higher crime levels. But the question is: what types of crime are prevalent in the Western Cape Province? And what are the major causes of these crimes? The purpose of this paper is to identify the different types of crimes committed in the Western Cape Province which are prominent. Principal Component analysis (PCA) has been use in this study to gauge the patterns of crime and the distinct important factors affecting the level of crime. Secondary data from a website have been used in the analysis. The results show that violence and vehicle thefts are the most committed crimes in the province. The areas where crime occurs most frequently are Bellville, Cape Town Central, Gugulethu, Harare, Khayelisha, Mitchells Plain, Nyanga and Parow. Firearms have been identified as major means for committing crime. The paper recommends that attempts be made by the provincial government to clamp down unlicensed fire arm holders/dealers. Amnesty should be granted to encourage holders of unlicensed fire arms to surrender without punishment and the public should report to the police all those dealing in unlicensed firearms in order to root out crime in the province.
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Song, Byung Ho, and Sang Cheul Han. "Efficiency plan for building a safe city through crime analysis: Facusing Pyeongtaek-si, south Gyeonggi-do." Korean Association of Criminal Psychology 18, no. 2 (June 30, 2022): 81–98. http://dx.doi.org/10.25277/kcpr.2022.18.2.81.
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This study is a study on the construction of a crime-safe city as a countermeasure by analyzing the occurrence of crimes due to the new urban concentration in the outskirts of the city in order to escape the urban concentration phenomenon. The subject of this study is Pyeongtaek, south Gyeonggi-do. In 2020, the number of crimes nationwide was 1,611,906, 3,108.7 per 100,000 people, and the Gyeonggi Nambu Provincial Police Agency had 379,794 crimes, which was 3,877.5 per 100,000, while Pyeongtaek City had 28,270, which was 5,510.4 per 100,000. This is more than 2,000 cases higher than the national crime rate per 100,000 people, and 1,500 cases higher than the crime rate in Gyeonggi-do. In other words, the study began with the need for an alternative for the safety and order maintenance and risk prevention of Pyeongtaek citizens due to crime. As a result, the problem with the occurrence of crimes in Pyeongtaek City is First, the occurrence of crimes due to insufficient security conditions. Second, there is a lack of CCTV, an infrastructure for crime prevention. Third, it is the deterioration of crime prevention activities through people-to-people cooperation, which is one of the police activities of the local community, which is outside the traditional police activities. Based on these problems, suggestions were made on how to increase the efficiency of the construction of a crime-safe city. First, the factors vulnerable to crime and improvement of the environment. Second, the strengthening of police patrol power in response to crime. Third, crime prevention is the duty of the police.
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Thanuja, B. "Machine Learning Based Crime Rate Analysis Using Python." International Journal for Research in Applied Science and Engineering Technology 10, no. 11 (November 30, 2022): 1312–16. http://dx.doi.org/10.22214/ijraset.2022.47574.
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Abstract: Crime is obvious that the rate of crimes were increasing day by day in all societies in world, but we personally do believe that there are a lot which can be done by both the governments and the individuals to reduce the crimes in communities. Crime analysis is a well-organized way of detecting and examining patterns and trends in crime. We should give utmost importance to study the reasons behind the crimes, so that we can prevent various crimes occurring and we can be able to find suitable solutions to prevent them. When people cannot find work, they have all the free time in the world. They think of crimes as a shortcut to obtaining and processing the riches of life, without any hardwork. To my mind, the overwhelming majority of people tend to participate in activities assisting the government to keep the society a safe place for their own families and the others and for all age groups. Our main aim of this project is to distinguish various crimes using clustering techniques based on the occurrences and regularity. In this project, the crime data is classified using the Support Vector Machine, Decision Tree, Random Forest Algorithm. This proposed system can indicate the areas which has more probability of occurring crimes so that we can easily identify the crimes based on the previous history and we can take measures to prevent the occurrences of crimes.
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Haeri, Mahmoud. "Analysis of Jurisprudence - Legal of Compulsion and Duress in Adultery." Journal of Politics and Law 9, no. 2 (March 31, 2016): 89. http://dx.doi.org/10.5539/jpl.v9n2p89.
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<p>Criminal responsibility is communicative ring and bridge of two important institutions of criminal law, crime and punishment and therefore is one of the most important issues of criminal law.<br />On the other hand, one of the conditions of obligation and criminal responsibilities is authority and freedom of action that a person could be required to preserve and respect for life, property and dignity of the people that in the actions is autonomous and free.<br />Although our legislator is considered to this issue in discretionary (Tazir) punishments crimes and life retribution explicitly and in the Haddi crimes are pointed to the lack of coercive responsibility, however, coercive criminal responsibility isn't specified in all instances of mentioned crimes, while in the discretionary (Tazir) punishments crimes, coercion is spiritual steward and is responsible for criminal responsibility due to the force committed crime and in the crime led to the death, in some cases crime is attributable to the duress, in the crimes included Hadd, coercing isn't considered spiritual steward.<br />In this paper, the mentioned issue is discussed in terms of legal and regulatory concerning the crime of adultery.</p>
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Kyei, Kwabena A. "Analysis of Crime Data in the Limpopo Province." Journal of Economics and Behavioral Studies 9, no. 3(J) (July 20, 2017): 19–27. http://dx.doi.org/10.22610/jebs.v9i3(j).1743.
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South Africa has a very high rate of murders, assaults, rapes and other crimes compared to most countries. Most South Africans who immigrate to other countries cite crime as the major reason. Crime has become a concern for all, the police, private security industry, real estate developer, car manufacturers, businessmen, etc. There is a high demand for crime prevention; and this calls for a continuous use of new, advanced and reliable methods to prevent crime. How bad is the level of crime in Limpopo and what are the major crime types? This study uses secondary data from the 2011 Census conducted by Statistics South Africa; and tries to look at the composition of crime in the province and the variables that influence crime, in order to propose measures to tackle and minimize crime in the province. Multivariate statistical analysis has been employed, and the study shows that the following variables; the population size, number of households, youth unemployment, growth rate, and dependency ratio; have a positive influence in the occurrence of crime. The study recommends the slowing down of population growth rate, decrease in household size and the reduction of youth unemployment to curb crime in the province.
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Kyei, Kwabena A. "Analysis of Crime Data in the Limpopo Province." Journal of Economics and Behavioral Studies 9, no. 3 (July 20, 2017): 19. http://dx.doi.org/10.22610/jebs.v9i3.1743.
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South Africa has a very high rate of murders, assaults, rapes and other crimes compared to most countries. Most South Africans who immigrate to other countries cite crime as the major reason. Crime has become a concern for all, the police, private security industry, real estate developer, car manufacturers, businessmen, etc. There is a high demand for crime prevention; and this calls for a continuous use of new, advanced and reliable methods to prevent crime. How bad is the level of crime in Limpopo and what are the major crime types? This study uses secondary data from the 2011 Census conducted by Statistics South Africa; and tries to look at the composition of crime in the province and the variables that influence crime, in order to propose measures to tackle and minimize crime in the province. Multivariate statistical analysis has been employed, and the study shows that the following variables; the population size, number of households, youth unemployment, growth rate, and dependency ratio; have a positive influence in the occurrence of crime. The study recommends the slowing down of population growth rate, decrease in household size and the reduction of youth unemployment to curb crime in the province.
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Druchek, O. V. "INTOLERANCE CRIMES AND HATE CRIMES: CONCEPT ANALYSIS." Scientific journal Criminal and Executive System: Yesterday. Today. Tomorrow 2022, no. 2 (August 15, 2023): 35–46. http://dx.doi.org/10.32755/sjcriminal.2022.02.035.
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A general theoretical analysis of the concepts of “crimes motivated by intolerance”, “hate crimes” and related concepts (such as “genocide”, “prejudice”, “xenophobia”) is provided in the article. The origin and meaning of the mentioned terms, their normative consolidation and practice of use in national legislation and international legal acts are analyzed. It has been proven that the concepts of “crimes motivated by intolerance” and “hate crimes” are close in meaning. As a legal category, crimes based on intolerance are a classification of a special type of crimes against a person caused by the feeling of intolerance felt by the subject of the crime towards a victim, a representative of another race, nationality, sex, religion, sexual orientation, gender identity, etc. It was found out that the basic structure of crimes motivated by impatience consists of two mandatory points: 1) the specified action is a crime according to the criminal law; 2) the motive for such an action is prejudice, that is, a false opinion formed about someone in advance, without familiarization, and the associated corresponding attitude. The signs of hate crimes have been substantiated and revealed: a) it is an action caused by prejudice, which is recognized as a crime according to international and national criminal legislation; b) such crimes have a significant public danger, are an extreme form of discrimination; c) these are crimes in which the victim, the object or the target of the crime were chosen based on their real or imagined belonging to a certain vulnerable group, connection with it; d) such imaginary or real grouping can be based on any socially relevant features or characteristics. It has been found out that the unifying feature of crimes motivated by intolerance is always a motive – a prejudiced or real feeling of hatred, hostility, intolerance towards the “other”, a representative of an imaginary or real “not their” social group. The need to bring the national legislation in line with international legal norms regarding the use of the term “hate crime” and the need to legislate the specified definition are substantiated. Key words: crimes motivated by intolerance, hate crimes; genocide, prejudice, xenophobia, national, racial, religious enmity, criminal law qualification.
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Pambabay-Calero, Johny, Sergio Bauz-Olvera, Rubén Flores-González, and Carlos Piña-García. "Multivariate analysis and characterization of low impact crime in Mexico City." F1000Research 10 (December 21, 2021): 1299. http://dx.doi.org/10.12688/f1000research.72990.1.
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Background: Multivariate analysis is fast becoming a key instrument that can be used to address crimes or incidents. It may be helpful to assess government policies on crime prevention. Methods: To distinguish between the 25 official crime categories reported in Mexico City (Jan 2019 - Jun 2019), principal coordinates analysis was used to determine the quality of a characteristic in this context. This study used cluster analysis via K-means and Biplot based on time and location in terms of crime occurrence. Results: The results obtained from this preliminary analysis indicates that around 70% of crime occurrence is shown in the following boroughs: Cuauhtémoc, Iztapalapa, Gustavo A. Madero, Benito Juárez, Álvaro Obregón, Coyoacán, and Miguel Hidalgo. Conclusion: There are two factors that contribute to the difficulties in crime analysis in Mexico City, namely, the lack of people’s trust in authorities and the insufficiency of tools for data analysis. The latter is an integral part in achieving justice for the victims of crimes because it impedes the process of observing patterns and predicting the perpetrators’ next actions, which may help in solving a number of types of crimes. It is then imperative for law enforcement to utilize data analysis tools that aid in identifying crime patterns and trends, such that the occurrences of crime show a downward trend and consequentially increase the people’s trust in law enforcement agencies.
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Tyagi, Deepika, and Dr Sanjiv Sharma. "AN APPROACH TO CRIME DATA ANALYSIS: A SYSTEMATIC REVIEW." International Journal of Engineering Technologies and Management Research 5, no. 2 (April 27, 2020): 67–74. http://dx.doi.org/10.29121/ijetmr.v5.i2.2018.615.
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In the current era, number of crimes occurs in the society and this criminal rate increase day by day. There is tremendous growth of criminal data. Crime has negatively influenced the societies. Crime control is essential for the welfare, stability and development of society. Law enforcement agencies are seeking for the system to target crime structure efficiently. The intelligent crime data analysis provides the best understanding of the dynamics of unlawful activities, discovering patterns of criminal behavior that will be useful to understand where, when and why crimes can occur. There is a need for the advancements in the data storage collection, analysis and algorithm that can handle data and yield high accuracy. This paper demonstrates the data mining technologies which are used in criminal investigation. The contribution of this paper is to highlight the methodology used in crime data analytics. This paper summarizes the challenges arising during the analysis process, which should be removed to get the desired result.
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Tariq, Haseeb, Muhammad Kashif Hanif, Muhammad Umer Sarwar, Sabeen Bari, Muhammad Shahzad Sarfraz, and Rozita Jamili Oskouei. "Employing Deep Learning and Time Series Analysis to Tackle the Accuracy and Robustness of the Forecasting Problem." Security and Communication Networks 2021 (March 31, 2021): 1–10. http://dx.doi.org/10.1155/2021/5587511.
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Crime is a bone of contention that can create a societal disturbance. Crime forecasting using time series is an efficient statistical tool for predicting rates of crime in many countries around the world. Crime data can be useful to determine the efficacy of crime prevention steps and the safety of cities and societies. However, it is a difficult task to predict the crime accurately because the number of crimes is increasing day by day. The objective of this study is to apply time series to predict the crime rate to facilitate practical crime prevention solutions. Machine learning can play an important role to better understand and analyze the future trend of violations. Different time-series forecasting models have been used to predict the crime. These forecasting models are trained to predict future violent crimes. The proposed approach outperforms other forecasting techniques for daily and monthly forecast.
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Bao, Yingyu. "Statistics and Characteristics Analysis of China’s Intellectual Property Crimes." MATEC Web of Conferences 228 (2018): 05013. http://dx.doi.org/10.1051/matecconf/201822805013.
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By collecting, comparing and analyzing the data of intellectual property crime cases officially published, it is found that there is a big contrast between the quantity and the actual situation. Such crimes have the possibility of the existence of large-scale crime black numbers, the expansion of the scope of real-world crime objects, and the difficulty of eradicating criminal objects in virtual worlds. It should be given priority in the legal framework to reduce the phenomenon of intellectual property crime.
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Ekici, Niyazi, Huseyin Akdogan, Robert Kelly, and Sebahattin Gultekin. "A meta-analysis of the impact of community policing on crime reduction." Journal of Community Safety and Well-Being 7, no. 3 (September 15, 2022): 111–21. http://dx.doi.org/10.35502/jcswb.244.
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Over the last few decades, many studies have been conducted to understand whether community policing (CP) has an impact on reducing crime rates. Yet there is still substantial controversy surrounding the question of the impact of CP on crime rates. Despite the broad understanding of CP, various types of measurement of crime statistics have led research- ers to conduct meta-analyses of the phenomenon. This study combines two previous meta-analyses of CP and Turkish and English online searches. We used the Comprehensive Meta-Analysis (CMA 3.0) statistical program to calculate the effect sizes of previous studies. We employed odds ratio (OR) as the effect size, since it is one of the most appropriate methods for proportions. We found no evidence suggesting that CP has an impact on reducing disorders, drug sales, or property crime, but it does have an impact on reducing crimes such as burglary, gun use, drug use, Part I crimes, and robbery, as well as fear of crime. Depending on crime type, CP can be a promising policing strategy to reduce crimes. und a statistically significant, positive impact of CP, despite the limitations of including only Turkish- and English-language studies.
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Utarov, Kanat, Kurmangaly Sarykulov, Akmeir Beisembayeva, Gulmira Meirkulova, and Sholpan Sartayeva. "Economic crime in the new Kazakhstan – a comparative analysis of the criminal legislation of EAEU member states." Scientific Herald of Uzhhorod University Series Physics, no. 55 (December 21, 2023): 1123–33. http://dx.doi.org/10.54919/physics/55.2024.112gd3.
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Relevance. Economic criminal offences are a factor in slowing a country's development. The number of such crimes is growing rapidly around the world, and the methods of committing them are becoming increasingly sophisticated, which determines the relevance of establishing new methods of countering economic crime and reforming legislation in this area, including in the member states of the Eurasian Economic Union. Purpose. The purpose of this article is to explore the essence, characteristics and features of economic crime, as well as the grounds for criminal liability for economic crimes in the Eurasian Economic Union countries. Methodology. The methodological basis of the study was dialectical and comparative methods, case study, abstraction, methods of system-structural and logical analysis, methods of registration and ranking, method of generalisation, which allowed to clarify the concepts and characteristics of economic crime; to consider available definitions of economic crime and individual provisions of the regulatory framework of Eurasian Economic Union member states on the regulation of economic crime; to characterise the legal nature of economic crime; to analyse the main scientific and methodological developments in this area. Results. The types of economic crimes in the member states of the Eurasian Economic Union were compared; to compare types of economic crime in the Eurasian Economic Union member states; to identify current trends in economic crime within the Eurasian Economic Union; to find out the main advantages of each Eurasian Economic Union member state's national legislation to combat economic crime; to classify possible economic crimes; and to determine the number of economic crimes committed and record their rates in each Eurasian Economic Union state; to characterise the specifics of countering economic crime in the Eurasian Economic Union. Conclusions. The significance of the research results is to provide practical recommendations for improving the legal regulation of relations in the sphere of economic crime, as well as in the process of implementing policies and taking public management decisions in the field of countering economic crime in the Eurasian Economic Union states.
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Sung, Hyeyeon. "Analysis on Research Trend of Recidivism of Sex Crimes using Keyword Network Analysis." Correction Welfare Society of Korea 79 (August 31, 2022): 59–89. http://dx.doi.org/10.35422/cwsk.2022.79.59.
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The purpose of this study is to suggest the direction of future studies on the prevention of sexual recidivism by analyzing the trend in research related to the recidivism of sexual crime for the last 20 years. To achieve this purpose, this study analyzed publication trends in research related to the recidivism of sexual crime by utilizing 139 studies published between 2000 and 2021 and conducted a keyword network analysis by using keywords extracted from these studies. The main results are as follows. First, results of publication trend by research area show that research related to the recidivism of sexual crimes was conducted in 11 areas order of 43.9% in law, 23.0% in public administration, and 17.9% in psychological science. Second, results of frequency analysis in keywords appeared in 139 studies show that the frequency was high in the following order; ‘sexual crime’, ‘prevention of recidivism’, ‘electronic monitoring system’, ‘risk of recidivism’, ‘child sex crime’, ‘medication treatment for sexual impulse’, and ‘personal information disclosure of sexual offender’. Third, results of degree centrality analysis using keywords show that the degree centrality was high in the following order; ‘sexual crime’, ‘prevention of recidivism’, ‘electronic monitoring system’, ‘recidivism of sexual crime’, ‘medication treatment for sexual impulse’, ‘risk of recidivism’, and ‘child sex crime’. Fourth, results of CONCOR cluster analysis with keywords show that research related to the recidivism of sexual crime was classified into nine clusters, and a major cluster was ‘study of electronic monitoring system’. Based on these results, this study suggests the directions of future studies on the prevention of recidivism from sexual crime.
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Zinovjev, Igor Feliksovich, and Viktor Evgenievich Reutov. "DYNAMICS OF ECONOMIC CRIME MARKERS OF THE REPUBLIC OF CRIMEA." Scientific Bulletin: finance, banking, investment., no. 2 (51) (2020): 190–200. http://dx.doi.org/10.37279/2312-5330-2020-2-190-200.
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Considering economic crimes (CEC), as a characteristic of the relationship between the factors of the socio-economic life of the territory with crime (reflecting the dynamics of the gap between the needs of the population of the region and the degree of their actual satisfaction), it becomes possible to start modeling the predictive dynamics of emerging and realized trends in the structure of economic crime in the Republic. Crimea. Revealing the territorial specifics of CEC in the region will make it possible to plan measures to concentrate measures of state influence on the sphere of factors that predetermine the predicted dynamics of economic crime and to prevent direct material damage from a possible negative state, functioning and development of the Crimean society. The criminological analysis of quantitative indicators of the dynamics of economic crime (with all the reservations about the incompleteness of the provided statistical data for PES and their distortions) does not allow (with the demanded depth of consideration) to distance the problems of various aspects of accounting for crime in this area and the factors that predetermine its specificity in the region. In order to increase the validity and information richness of the analysis of the territorial specifics of CEC, the author’s calculated «markers» were proposed that reflect one or another aspect of economic crime, as well as dynamic trends in its structure and / or nature. Based on the analysis of marker indicators, a characteristic of the region’s economic crime was compiled and a forecast scenario for the development of trends in the CEC of the Republic of Crimea was proposed.
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Yu, Danlin, and Chuanglin Fang. "How Neighborhood Characteristics Influence Neighborhood Crimes: A Bayesian Hierarchical Spatial Analysis." International Journal of Environmental Research and Public Health 19, no. 18 (September 10, 2022): 11416. http://dx.doi.org/10.3390/ijerph191811416.
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Urban crimes are a severe threat to livable and sustainable urban environments. Many studies have investigated the patterns, causes, and strategies for curbing the occurrence of urban crimes. It is found that neighborhood socioeconomic status, physical environment, and ethnic composition all might play a role in the occurrence of urban crimes. Inspired by the recent interest in exploring urban crime patterns with spatial data analysis techniques and the development of Bayesian hierarchical analytical approaches, we attempt to explore the inherently intricate relationships between urban assaultive violent crimes and the neighborhood socioeconomic status, physical environment, and ethnic composition in Paterson, NJ, using census data of the American Community Survey, alcohol and tobacco sales outlet data, and abandoned property listing data from 2013. Analyses are set at the census block group level. Urban crime data are obtained from the Paterson Police Department. Instead of examining relationships at a global level with both non-spatial and spatial analyses, we examine in depth the potential locally varying relationships at the local level through a Bayesian hierarchical spatially varying coefficient model. At both the global and local analysis levels, it is found that median household income is decisively negatively related to urban crime occurrence. Percentage of African Americans and Hispanics, number of tobacco sales outlets, and number of abandoned properties are all positively related with urban crimes. At the local level of analysis, however, the different factors have varying influence on crime occurrence throughout the city of Paterson, with median household income having the broadest influence across the city. The practice of applying a Bayesian hierarchical spatial analysis framework to understand urban crime occurrence and urban neighborhood characteristics enables urban planners, stakeholders, and public safety officials to engage in more active and targeted crime-reduction strategies.
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Jang, Hyunseok. "Spatial Regression Analysis on the Determinants of Drug Crime Levels by Administrative Dong: Focusing on Crime Pattern Theory." Korea CPTED Association 14, no. 3 (December 31, 2023): 121–54. http://dx.doi.org/10.26470/jcssed.2023.14.3.121.
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The severity of drug-related crimes in Korean society is increasing, yet there is a relative lack of research on the local distribution of drug crimes and the factors influencing their distribution in the society. In contrast to the United States, where studies indicate a concentration of drug crimes in certain crime-prone locations, domestic criminological research on the geographical distribution of drug crimes is insufficient. This study, grounded in the crime pattern theory, set alcohol-selling entertainment establishments as potential locations for drug crimes and investigated whether the number of such establishments has a significant impact on the occurrence of drug crimes using crime occurrence data at the administrative dong level in Seoul.
Drawing on previous research on the geographical distribution of crime, this study incorporated variables such as the presence of police substations, CCTV ratios, the proportion of foreigners, the foreign floating population, the local floating population, population density, and migration ratios into a spatial regression analysis model.
The analysis revealed that the number of alcohol-selling entertainment establishments had a significant positive impact on the occurrence of drug crimes, supporting the hypothesis of crime pattern theory in the geographical distribution of drug crimes. Additionally, areas with a higher local floating population showed significantly higher crime grades. It was observed that administrative dongs with police substations tended to have significantly lower grades for drug crime occurrence, suggesting the presence of police facilities as a deterrent factor.
Based on the research findings, policy recommendations were provided, and the limitations of the study were discussed.
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Khurramovich, Khudaykulov Feruzbek. "INTERRELATIONSHIP OF SIGNS OF THE OBJECTIVE SIDE OF CRIME IN CRIMINAL LAW: GENERAL PRINCIPLES, PROBLEMS, ANALYSIS AND SOLUTIONS." International Journal of Advance Scientific Research 4, no. 1 (January 1, 2024): 123–36. http://dx.doi.org/10.37547/ijasr-04-01-20.
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The article widely uses logical, inductive, deductive, systematic, logical-legal, comparative-legal research methods. In particular, it was noted that the qualification of the act, the relationship between the signs of the objective side of the crime and the method of committing the crime can be classified as follows: 1) from the point of view of manifestation of the method of committing a crime as a form of a specific socially dangerous act (reflected in a specific socially dangerous act): a) the relationship between the method of committing a crime and the weapon of committing a crime; b) the relationship between the method of crime and the place of crime; 2) from the point of view of the fact that the method of committing a crime is not reflected in a specific socially dangerous act, but as a necessary sign of the nature of the crime: a) the relationship between the method of committing the crime and the method as an aggravating (qualifying) sign of responsibility; b) the relationship between the method of crime and the place of crime. The method of committing a crime in individual cases makes it possible to distinguish one or another crime objectively (that is, to distinguish crimes from each other), and gives the presence (or not) of a socially dangerous act, socially dangerous consequence andother elements of the crime, as well as the optional characteristics of another objective aspect of the crime. At the same time, the doctrine of criminal law and existing scientific research were analyzed, and reasonable theoretical recommendations were developed in this regard.
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Zhao, Yunfeng. "Analysis and examination of terrorism crime legislation." Legal Science in China and Russia, no. 4 (September 16, 2021): 170–79. http://dx.doi.org/10.17803/2587-9723.2021.4.170-179.
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In the past 10 years, China’s legislation on terrorist crimes has undergone great changes, which not only responds to the inherent requirements stipulated in the international conventions, but also refl ects the policy governing terrorist crimes. The legislation of terrorist crime presents new dimensions, specifi cally for the preventive strengthening, the increase of severity, the increase of rigour. Under the background of risk society, the legislation of terrorism crime has positive social signifi cance, which is embodied in the combination of punishment after the event and prevention before the event, the unity of behavior harm and personal danger. In the future criminal legislation, it is necessary to enhance the foresight of legislation, promote the scientifi c nature of legislation, and strengthen the effective connection between criminal law and anti-terrorism security law, which should be the development direction of terrorism crime legislation
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Smetanina, Nataliia Volodumurivna, and Kateryna Dmitryevna Kulyk. "Cost of crime in Ukraine: an empirical analysis." Journal of Criminological Research, Policy and Practice 6, no. 2 (February 28, 2020): 97–109. http://dx.doi.org/10.1108/jcrpp-10-2019-0065.
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Purpose This paper aims to analyze the cost of crime as understood in Ukrainian and foreign criminology, investigating both the direct and indirect damage caused by crime, its social consequences and Ukrainians’ attitudes toward its costs. Design/methodology/approach From January 2018 to May 2019, data were gathered using an online questionnaire from 717 respondents between 14 and 65 years of age residing in all regions of Ukraine. Findings Results suggest a high level of concern among Ukrainian citizens regarding security and crime. Latent criminality, crime rates and mistrust of law enforcement are high in Ukraine. It was found that the total cost of crime to the respondents (losses from crimes) reached UAH2m, and 69.3 per cent reported fear of becoming a victim of crime, with 26.2 per cent indicating that they had already been victims. Practical implications The knowledge of the cost of crime obtained in this study is vital for understanding crime in Ukraine. The results could be effectively leveraged to develop effective and cost-efficient means of combating crime. They could also be used to forecast crime rates, and thus, optimize future responses to the challenges of crime. Originality/value This is the first comprehensive study of the cost of crime in Ukraine and it indicates both the tangible and intangible costs of the damage it inflicts. Notwithstanding the country-specific case-study context, the results could inform discussions and decisions at a broader international scale, subject to the usual caveats.
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Xu, Dingjiang. "Application and Feasibility Analysis of Network Models and Data Analysis in Combating Organized Crime." Lecture Notes in Education Psychology and Public Media 37, no. 1 (January 15, 2024): 185–93. http://dx.doi.org/10.54254/2753-7048/37/20240538.
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This article discusses and analyzes in detail the development potential and application of big data mining and network visualization analysis in combating organized crime. Firstly, the article emphasizes the importance of combating criminal gangs and organized crime in modern society, comparing them to the foundation of stable national development and the cornerstone of national progress. Then it explores the security challenges faced by modern society and more issues related to organized crime, including the problem of crime caused by the wealth gap caused by urbanization and economic development, as well as the outdated technology for cracking down on existing security crimes. This article provides a detailed introduction to the potential of big data mining and network visualization, as well as the advantages of these technologies in practical applications. It covers the collection, processing, sharing, and application of data. At the same time, network visualization is used to visualize crime data, helping decision-makers better understand the current situation and problems of public security and organized crime. The article also discusses the application of artificial intelligence and mobile internet technology in combating organized crime. And the potential of big data in improving urban governance. Finally, this article looks ahead and emphasizes that big data mining and network visualization analysis will continue to play an important role in optimizing social security, indicating the broad prospects of these technologies in the future transportation field.
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Oh, Ha-Neul, Seok-Jin Kang, and Gun-won Lee. "An Analysis of Crime Status and Influence Factors of New town in Capital Region of Korea." Korea CPTED Association 14, no. 3 (December 31, 2023): 91–120. http://dx.doi.org/10.26470/jcssed.2023.14.3.91.
Full textAbstract:
The purpose of this study is to analyze the status of crime in new town in the Capital Region of Korea and analyze the physical factors that affect crime. The spatial scope of the study is Bundang, Ilsan, Dongtan, and Pangyo, which are representative of the first and second new cities, and the temporal range was set from 2010 to 2014, and after analyzing the crime status of four new cities, the characteristics of major hotspots were confirmed through field surveys from a micro perspective, and the factors influencing crime were identified through spatial regression analysis from a macro perspective.
The main results obtained through this study are as follows. First, as a result of the analysis of the crime status of the new city, it was found that the rate of theft and violence was high in the first new city. In particular, theft crimes occur relatively frequently, and sex crimes occur less frequently, but they have been confirmed to occur steadily. The second new city varies greatly from region to region, with relatively many violent crimes occurring in general, and the incidence of violent crimes such as sex crimes and robbery crimes was relatively higher than that of the first new city.
Based on the analysis of the five major crime hotspots, the crime impact factors from a micro perspective were analyzed through field surveys at major points, but the use of buildings in the area was similar to commercial facilities, apartments, multi-family and multi-family houses, row houses, and multi-use facilities.
As a result of analyzing crime impact factors from a macro perspective through spatial regression analysis in Bundang New Town, it was found that other housing (+), entertainment/lodging (+), exercise facilities (+), and CCTV (+) had the most significant impact on total crime. Theft was the most significant variable for other dwellings (+), entertainment/lodging (+), and exercise facilities (+). Single-family houses (+), general restaurants (+), exercise facilities (+), and CCTV (+) had the most significant impact on violence. Finally, single-family houses (+), general restaurants (+), exercise facilities (+), and CCTV (+) had the most significant impact on sex crimes.
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Amoako, Esther Akoto. "A spatial Analysis of Crime and Neighborhood Characteristics in Detroit Census Block Groups." Proceedings of the ICA 4 (December 3, 2021): 1–8. http://dx.doi.org/10.5194/ica-proc-4-5-2021.
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Abstract. Crime has an inherent geographical quality and when a crime occurs, it happens within a particular space making spatiality essential component in crime studies. To prevent and respond to crimes, it is first essential to identify the factors that trigger crimes and then design policy and strategy based on each factor. This project investigates the spatial dimension of violent crime rates in the city of Detroit for 2019. Crime data were obtained from the City of Detroit Data Portal and demographic data relating to social disorganization theory were obtained from the Census Bureau. In the presence of spatial spill over and spatial dependence, the assumptions of classical statistics are violated, and Ordinary Least Squares estimations are inefficient in explaining spatial dimensions of crime. This paper uses explanatory variables relating to the social disorganization theory of crime and spatial autoregressive models to determine the predictors of violent crime in the City for the period. Using GeoDa 1.18 and ArcGIS Desktop 10.7.1 software package, Spatial Lag Models (SLM) and Spatial Error Models were carried out to determine which model has high performance in identifying predictors of violent crime. SLM outperformed SEM in terms of efficiency with (AIC:5268.52; Breusch-Pagan test: 9.8402; R2: 16% & Log Likelihood: −2627.26) > SEM (AIC: 5275.24; Breusch-Pagan test: 9.7601; R2: 15% & Log Likelihood: −2630.6194). Strong support is found for the spatial disorganization theory of crime. High percent ethnic heterogeneity (% black) and high college graduates are the strongest predictors of violent crime in the study area.