The Windy City’s Dark Side: A Statistical Exploration of Crime in the City of Chicago

This paper presents a detailed statistical exploration of crime trends in Chicago from 2001 to 2023, employing data from the Chicago Police Department’s publicly available crime database. The study aims to elucidate the patterns, distribution, and variations in crime across different types and locations, providing a comprehensive picture of the city’s crime landscape through advanced data analytics and visualization techniques. Using exploratory data analysis (EDA), we identified significant insights into crime trends, including the prevalence of theft and battery, the impact of seasonal changes on crime rates, and spatial concentrations of criminal activities. The research leveraged a Power BI dashboard to visually represent crime data, facilitating an intuitive understanding of complex patterns and enabling dynamic interaction with the dataset. Key findings highlight notable disparities in crime occurrences by type, location, and time, offering a granular view of crime hotspots and temporal trends. Additionally, the study examines clearance rates, revealing variations in the resolution of cases across different crime categories. This analysis not only sheds light on the current state of urban safety but also serves as a critical tool for policymakers and law enforcement agencies to develop targeted interventions. The paper concludes with recommendations for enhancing public safety strategies and suggests directions for future research, emphasizing the need for continuous data-driven approaches to effectively address and mitigate urban crime. This study contributes to the broader discourse on urban safety, crime prevention, and the role of data analytics in public policy and community well-being.

基于CRIME理论的^(*)ST宜生财务舞弊案例研究

资本市场不断完善对我国经济发展起到重要的推动作用,但同时财务舞弊事件也层出不穷。上市公司财务舞弊行为严重侵害了投资者权益,扰乱了我国资本市场的正常运行,不利于社会经济健康发展。运用CRIME理论,分别从造假行为人、造假手段、造假动因、监督机制、造假结果5个方面对^(*)ST宜生财务舞弊事件进行分析,厘清了财务舞弊的来龙去脉,并针对性地从公司、会计师事务所和监管机制3个角度提供启示,希望对相关主体具有借鉴意义,减少财务舞弊行为的发生,肃清资本市场不良风气。

基于CRIME理论的康美药业财务造假分析及防范研究

随着经济的快速发展,资本市场中财务造假事件频繁发生,损害了中小股东的利益,给债权人、广大投资者乃至社会带来了巨大的损失。利用传统财务指标对舞弊手段进行识别的作用有限,提出的解决措施治标不治本。因此,需要采用系统的理论对上市公司财务舞弊进行深入分析,才能提出针对性的治理对策。本文运用CRIME舞弊行为理论,从舞弊者、舞弊手段、舞弊动机、监管机制、舞弊后果五个角度,对康美药业舞弊现象进行剖析,针对产生的问题提出了相应的预防措施,以期增强投资者的风险辨识能力。

从CRIME理论看公司财务造假

随着经济的飞速发展,我国上市公司数量逐年增加,但并不是所有的上市公司都能够保持持续盈利或者在行业中占据主导地位,财务造假严重影响着正常的经济运作规律,给社会带来巨大的危害。本文从CRIME理论五个因素出发,以中信国安公司财务造假为案例,对该公司造假者、造假手段、造假动机、监管机制、最终后果进行探究,从中寻找启示。

A Survey of Crime Scene Investigation Image Retrieval Using Deep Learning

Crime scene investigation(CSI)image is key evidence carrier during criminal investiga-tion,in which CSI image retrieval can assist the public police to obtain criminal clues.Moreover,with the rapid development of deep learning,data-driven paradigm has become the mainstreammethod of CSI image feature extraction and representation,and in this process,datasets provideeffective support for CSI retrieval performance.However,there is a lack of systematic research onCSI image retrieval methods and datasets.Therefore,we present an overview of the existing worksabout one-class and multi-class CSI image retrieval based on deep learning.According to theresearch,based on their technical functionalities and implementation methods,CSI image retrievalis roughly classified into five categories:feature representation,metric learning,generative adversar-ial networks,autoencoder networks and attention networks.Furthermore,We analyzed the remain-ing challenges and discussed future work directions in this field.

基于CRIME理论视角下东方金钰财务舞弊分析

近年来,随着资本市场的不断完善,我国经济得到了高速发展,但与此同时伴随着上市公司财务舞弊行为的频繁发生,这不仅极大损害了投资者的利益,还严重影响了资本市场的诚信机制。因此,对上市公司财务舞弊行为进行有效识别与采取防范手段极为重要。本文以东方金钰财务造假案件为例,运用CRIME理论,分别从舞弊行为人、舞弊手段、舞弊动因、监管机制、舞弊结果五个方面对东方金钰财务舞弊事件进行分析,并针对这五个方面提出有关的建议。希望对相关研究具有借鉴意义,以减少财务舞弊行为的发生。

Hierarchical Restriction and Reduction of Overcriminalization of Teachers’Disciplinary Behaviors

The right to education is an important part of basic human rights. To transform from a designed vision to a reality in practice, teachers’ right to discipline, as a component of the right to education, needs tangible support from the criminal law. The criminal law cannot be absent from promoting the rule of law in education. However, in practice, teachers’ disciplinary behaviors are often ex-cessively criminalized, leading to problems such as over-expanding punishment and harming the innocent and even the malaise that en-danger substantive justice such as the tarnishing of teachers’ disci-plinary right and the imbalance of teachers’ disciplinary behaviors. Such overcriminalization has its social causes and normative crux, which is the ambiguity of regulations of teachers’ disciplinary right in terms of the pre-existing law and the unclear positioning of the jus-tification of teachers’ disciplinary behaviors in terms of the criminal law. Therefore, it is necessary to carry out a dual clarification of the chaotic parts of the two laws and determine the corresponding guiding principles, and test them one by one through the hierarchical theory of crime to make the path of exculpation clear. At the level of constituent elements, the exculpation is achieved through the normative judgment of the constituent elements;At the level of illegality, the exculpation is achieved by virtue of substantive considerations of reasons such as le-gal acts, legitimate defense, and victims’ commitments;At the level of accountability, the exculpation is achieved through the value screening of the culpability paradigm. We should reverse the trend of overcrim-inalization of teachers’ disciplinary behaviors by clearing the way of exculpation.

基于CRIME理论的财务舞弊问题研究——以Z公司为例

随着数字经济和互联网的兴起,上市公司财务舞弊现象层出不穷。本文基于CRIME理论,从财务的舞弊者、舞弊手段、舞弊动机、舞弊监管机制、舞弊结果五个方面系统分析了Z公司的财务舞弊案例,从内部防范、人员素质、外部监管三个方面提出了建议,希望对资本市场的完善有所启示。

Monitoring and Early Warning of New Cyber-Telecom Crime Platform Based on BERT Migration Learning

The network is a major platform for implementing new cyber-telecom crimes.Therefore,it is important to carry out monitoring and early warning research on new cyber-telecom crime platforms,which will lay the foundation for the establishment of prevention and control systems to protect citizens’property.However,the deep-learning methods applied in the monitoring and early warning of new cyber-telecom crime platforms have some apparent drawbacks.For instance,the methods suffer from data-distribution differences and tremendous manual efforts spent on data labeling.Therefore,a monitoring and early warning method for new cyber-telecom crime platforms based on the BERT migration learning model is proposed.This method first identifies the text data and their tags,and then performs migration training based on a pre-training model.Finally,the method uses the fine-tuned model to predict and classify new cyber-telecom crimes.Experimental analysis on the crime data collected by public security organizations shows that higher classification accuracy can be achieved using the proposed method,compared with the deep-learning method.

Temporal-spatial Distribution of Various Types of Crime in the Special Wards of Tokyo

Based on the official criminal data released by the Tokyo Metropolitan Police Department in 2019,this paper discusses the temporal-spatial distribution of various types of crimes in the special wards of Tokyo.The results show that:(1)The times of high and low incidence of different types of crime differ significantly.Although vicious crime and violent crime present no obvious monthly distribution,property crime clearly differs between the first and second half of a calendar year.(2)The month before the new year sees a surge in most types of crime.(3)Vicious crime peaks in the hours between night and early morning.Violent crime and property crime correlate positively with the frequency of human interaction and peak in the morning and evening commuting hours.(4)The spatial distribution of crime resembles the concentric circles of the three rings of the special wards of Tokyo,with a central high-incidence area,a center-peripheral low-incidence area,and a marginal high-incidence area.In addition,the center sees more personal crime than the periphery,whereas property crimes show the opposite trend.(5)A spatial autocorrelation analysis shows that the special wards of Tokyo may be grouped into the“high-high”and“low-low”agglomeration modes of different types of crime,with marked differences between the various types of crime.The crime can be divided into three types:central agglomeration,double central agglomeration,and decentralized agglomeration.

Prevalence, Pattern and Factors Associated with Psychiatric Disorders among Persons Arrested for Violent Crimes in Ife/Modakeke Area, Southwestern Nigeria

Background: Association between violence and mental disorders has contributed immensely to the stigma associated with mental illness in the society;because people erroneously see mentally ill individuals as dangerous, they will not want to associate with them. Aims: To assess the prevalence and pattern of psychiatric disorders among a sample of the violent offenders and to examine any relationship between psychiatric disorders and crimes. Method: This was a two-phase cross-sectional study in three police stations in Ile-Ife/Modakeke area of Nigeria. In the first phase, we screened 400 consecutive adults arrested for violent crimes using the General Health Questionnaire—30. In the second phase, all 36 persons with probable psychopathology were then interviewed with the Present State Examination to make a definitive diagnosis. Results: The mean age of all the subjects was 29.9 years (SD ± 7.3). The male to female ratio was 11:1. Respondents were mostly single (54%);most had secondary education or less (82%) and about 60% were currently using psychoactive substances (drugs). About 8.5% of all the subjects had a diagnosable psychiatric disorder;paranoid schizophrenia was the commonest psychiatric disorder (41.2%). Mentally ill subjects were three times more likely to commit homicidal offence than non-mentally ill subjects. Conclusion: There exists a significant but weak relationship between mental illness and violent crimes.

Digital Forensics and Cyber Crime Datamining

Digital forensics is the science of identifying, extracting, analyzing and presenting the digital evidence that has been stored in the digital devices. Various digital tools and techniques are being used to achieve this. Our paper explains forensic analysis steps in the storage media, hidden data analysis in the file system, network forensic methods and cyber crime data mining. This paper proposes a new tool which is the combination of digital forensic investigation and crime data mining. The proposed system is designed for finding motive, pattern of cyber attacks and counts of attacks types happened during a period. Hence the proposed tool enables the system administrators to minimize the system vulnerability.

基于CRIME理论的财务舞弊案例分析——以康美药业为例

康美药业财务舞弊案作为A股史上最大的财务舞弊案,一直备受市场关注。文章基于CRIME理论,从舞弊行为人、舞弊手段、舞弊激励、监管机制、结果五个方面系统全面地分析了康美药业财务舞弊案,并从内部监管与外部监管两方面提出建议。

GIS Based Spatial and Temporal Analysis of Crimes, a Case Study of Mardan City, Pakistan

This paper is aimed to study the crime with special reference to its spatial and temporal distribution. It also tries to analyze and estimates the impact of weather on the prevalence of criminal activity in Mardan City. Studying the crimes with reference to its spatial and temporal distribution is important because information about the occurrence of crime is one of the most crucial tools in combating crime. It allows understanding how crimes are distributed through space, and hence can help in combating them. The Geographical Information System is an important tool for dealing with spatial and temporal analysis and thus fighting crime. The advent of desktop computers has significantly increased the role of computer mapping. The availability of user-friendly GIS applications has further increased the use of GIS in crime mapping. For the present study the data was collected about homicide and aggressive assaults from all the three police stations covering Mardan City. The collected data was analyzed under different scenarios. The temporal based analysis of data reveals that almost 50% crimes reported in 2009, took place from May-September (summer) compared to 32% in winter (October to February). The spatial analysis of data reveals 05 hotspots. Sikindary area was identified as the most crucial hotspot where within a 05 km radius, 11 crimes were committed in 2009 followed by Kalpani Bridge area from where a total of 10 crimes of aggressive nature were reported. Similarly police station wise the City Police Station accounts for 47% of the aggressive crimes committed in 2009.

Crime forecasting:a machine learning and computer vision approach to crime prediction and prevention

A crime is a deliberate act that can cause physical or psychological harm,as well as property damage or loss,and can lead to punishment by a state or other authority according to the severity of the crime.The number and forms of criminal activities are increasing at an alarming rate,forcing agencies to develop efficient methods to take preventive measures.In the current scenario of rapidly increasing crime,traditional crime-solving techniques are unable to deliver results,being slow paced and less efficient.Thus,if we can come up with ways to predict crime,in detail,before it occurs,or come up with a“machine”that can assist police officers,it would lift the burden of police and help in preventing crimes.To achieve this,we suggest including machine learning(ML)and computer vision algorithms and techniques.In this paper,we describe the results of certain cases where such approaches were used,and which motivated us to pursue further research in this field.The main reason for the change in crime detection and prevention lies in the before and after statistical observations of the authorities using such techniques.The sole purpose of this study is to determine how a combination of ML and computer vision can be used by law agencies or authorities to detect,prevent,and solve crimes at a much more accurate and faster rate.In summary,ML and computer vision techniques can bring about an evolution in law agencies.

A Comparative Study between the Jordanian and Omani Digital Crimes Law

The nature of crime has dramatically changed after the revolution of the new digital era. It is no longer based on violence but on the criminal computer abilities and technical expertise. This paper presents a comprehensive comparison between the Jordanian digital law 2015 and the Omani information technology digital crime law 2010. The results of this study indicate that the Jordanian Digital law requires some enhancements in order to cope with the trends of the ever-changing nature of the digital crimes.

Comparison of Model Performance for Basic and Advanced Modeling Approaches to Crime Prediction

A good machine learning model would greatly contribute to an accurate crime prediction. Thus, researchers select advanced models more frequently than basic models. To find out whether advanced models have a prominent advantage, this study focuses shift from obtaining crime prediction to on comparing model performance between these two types of models on crime prediction. In this study, we aimed to predict burglary occurrence in Los Angeles City, and compared a basic model just using prior year burglary occurrence with advanced models including linear regressor and random forest regressor. In addition, American Community Survey data was used to provide neighborhood level socio-economic features. After finishing data preprocessing steps that regularize the dataset, recursive feature elimination was utilized to determine the final features and the parameters of the two advanced models. Finally, to find out the best fit model, three metrics were used to evaluate model performance: R squared, adjusted R squared and mean squared error. The results indicate that linear regressor is the most suitable model among three models applied in the study with a slightly smaller mean squared error than that of basic model, whereas random forest model performed worse than the basic model. With a much more complex learning steps, advanced models did not show prominent advantages, and further research to extend the current study were discussed.

Organized Crime＇s Engagement in Democratic Politics： Strategies for Prevention and Mitigation

Criminal networks erode the legitimacy of democratic politics, affecting regions as diverse as Latin America （Briscoe, Perdomo, ＆ Uribe Burcher, 2014）, the Baltic States （Villaveces-Izquierdo ＆ Uribe Burcher, 2013）, and West Africa （Aning ＆ Edu-Afful, 2013a; 2013b）. Contemporary research on this topic describes various factors that might increase the vulnerability of political actors, institutions, and processes to organized crime （Uribe Burcher, 2017）. In addition, there is a need to identify strategies to strengthen those political actors, institutions, and processes, making them resilient against criminal influence. Drawing from extensive field research conducted in Latin America, Africa, and West Asia in 2015-2016 （Perdomo ＆ Uribe Burcher, 2016; Hunter ＆ Reitano, 2016; Briscoe ＆ Goff, 2016a; 2016b）, as well as additional desk research conducted during the same period, this paper maps a set of 28 actions that may increase these institutions＇ and actors＇ resilience to the influence of organized crime networks based on documented global experiences implementing such measures. The paper also reflects some of the findings from a pilot experience to assess the threat of nexus between organized crime in democratic politics in Peru conducted in 2015-2016, which used some of the proposed action points to build a prevention and mitigation plan.

Assessing the Threat of Nexus Between Organized Crime and Democratic Politics： Mapping the Factors

In recent years, increased attention from the media, the international community and policy makers has highlighted the destabilizing effects criminal networks have on the legitimacy of democratic politics, as well as the capacity of democratic systems to deliver basic services. Indeed, the Organization for Economic Co-operation and Development highlighted in 2014 how illicit financial flows drain the state from resources needed to provide basic services （OECD, 2014）. While this problem affects not only developing and fragile states, these countries are particularly affected as this phenomenon tends to exacerbate inequality （Briscoe, Perdomo ＆ Uribe Burcher, 2014）. Mapping the factors that make politics vulnerable to the influence of organized crime is a key element in the effort to implement adequate strategies to prevent and mitigate this phenomenon. This paper explores 21 threat factors identified, understood as some of the conditions that may contribute to the likelihood that political corruption linked to organized crime takes place. These threat factors underline institutional weaknesses--including those related to illicit political fmance---and organized crime activities, which create opportunities for illicit networks to penetrate democratic political systems. The paper also discusses how these institutional weaknesses interrelate to specific criminal markets and networks. The paper draws from extensive desk research in 2015, which complements previous desk and field research on the same topic carded out in 2011-2014 in the Baltic States, Latin America and West Africa.

Revisiting History Through Crime Fiction： Shiono Nanami＇s Scarlet Venice in The Renaissance Trilogy of Murder

The paper explores an ambiguous intersection between history and fiction in Scarlet Venice （Hi no Venezia, in original） （1988） by Japanese novelist and historiographer, Shiono Nanami （1937-）. As a prominent transnational writer who has worked on the Italian Renaissance and the Roman antiquity for about 40 years, Shiono fictionalizes the political culture of 16th century Venice in the context of the Eastern Mediterranean history. Based on her The Tales of the Sea Capital （1981）, historiography par excellence, the novel portrays the political maneuver of the Republic of Venice from viewpoints of diplomacy. With this thematic approach to history, the novel centers on the life and death of Alvise Gritti （1480-1534）, an illegitimate son of famed Venetian Doge, Andrea Gritti. In the metaphorical/metafictional structure of historical crime fiction, the novel unveils the austerity of Venetian polity, while contrasting it with the liberalism fostered in Sultan Suleiman＇s Ottoman court. In conclusion, the author interprets that Alvise Gritti is a victim of the political intricacy with which Venice was wrestling, implying that the republic is the metaphorical murderer. Whereas Alvise＇s death commemorates a drastic step taken by Venice for political negotiation, Shiono＇s recent writings suggest that Japan should model the rigid pragmatism in Venetian politics, along with its effective use of intelligence in diplomacy