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.

Predicting the Type of Crime: Intelligence Gathering and Crime Analysis

Crimes are expected to rise with an increase in population and the rising gap between society’s income levels.Crimes contribute to a significant portion of the socioeconomic loss to any society,not only through its indirect damage to the social fabric and peace but also the more direct negative impacts on the economy,social parameters,and reputation of a nation.Policing and other preventive resources are limited and have to be utilized.The conventional methods are being superseded by more modern approaches of machine learning algorithms capable of making predictions where the relationships between the features and the outcomes are complex.Making it possible for such algorithms to provide indicators of specific areas that may become criminal hot-spots.These predictions can be used by policymakers and police personals alike to make effective and informed strategies that can curtail criminal activities and contribute to the nation’s development.This paper aims to predict factors that most affected crimes in Saudi Arabia by developing a machine learning model to predict an acceptable output value.Our results show that FAMD as features selection methods showed more accuracy on machine learning classifiers than the PCA method.The naïve Bayes classifier performs better than other classifiers on both features selections methods with an accuracy of 97.53%for FAMD,and PCA equals to 97.10%.

Enhancing Cybersecurity Competency in the Kingdom of Saudi Arabia:A Fuzzy Decision-Making Approach

The Kingdom of Saudi Arabia(KSA)has achieved significant milestones in cybersecurity.KSA has maintained solid regulatorymechanisms to prevent,trace,and punish offenders to protect the interests of both individual users and organizations from the online threats of data poaching and pilferage.The widespread usage of Information Technology(IT)and IT Enable Services(ITES)reinforces securitymeasures.The constantly evolving cyber threats are a topic that is generating a lot of discussion.In this league,the present article enlists a broad perspective on how cybercrime is developing in KSA at present and also takes a look at some of the most significant attacks that have taken place in the region.The existing legislative framework and measures in the KSA are geared toward deterring criminal activity online.Different competency models have been devised to address the necessary cybercrime competencies in this context.The research specialists in this domain can benefit more by developing a master competency level for achieving optimum security.To address this research query,the present assessment uses the Fuzzy Decision-Making Trial and Evaluation Laboratory(Fuzzy-DMTAEL),Fuzzy Analytic Hierarchy Process(F.AHP),and Fuzzy TOPSIS methodology to achieve segment-wise competency development in cyber security policy.The similarities and differences between the three methods are also discussed.This cybersecurity analysis determined that the National Cyber Security Centre got the highest priority.The study concludes by perusing the challenges that still need to be examined and resolved in effectuating more credible and efficacious online security mechanisms to offer amoreempowered ITES-driven economy for SaudiArabia.Moreover,cybersecurity specialists and policymakers need to collate their efforts to protect the country’s digital assets in the era of overt and covert cyber warfare.

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.

Analysis of the Resolution of Crime Using Predictive Modeling

There has been evidence of crime in the US since colonization. In this article, we analyze the crime statistics of San Francisco and its resolution of crime recorded from January to September of the year 2018. We define resolution of crime as a target variable and study its relationship with other variables. We make several classification models to predict resolution of crime using several data mining techniques and suggest the best model for predicting resolution.

Addressing Japan’s disposal of nuclear-contaminated water from the perspective of international human rights law

The discharge of nuclear-contaminated water containing radionuclides into the ocean by Japan will lead to its integration into the entire ecosystem through processes of circulation and biomagnification,eventually entering the human body via the food chain.This poses a substantial risk of irreversible damage to both the ecosystem and human health,a situation that will worsen with the ongoing discharge of such water.The respect and protection of human rights represent an international consensus,and safeguarding fundamental human rights is a substantial obligation that states must undertake in accordance with both international and domestic law.Since the Fukushima nuclear disaster,Japan has continuously violated its international legal obligations to protect human rights in several areas,including the resettlement of disaster victims,the reduction of nuclear radiation levels,and the handling of contaminated water.Such actions have compromised and will continue to compromise the basic human rights of not only its citizens but also those of people worldwide,including environmental rights,the right to life,development rights,and food rights.In the aftermath of the Fukushima meltdown,the public and workers involved in handling nuclear contaminants have been continually exposed to high radiation levels,endangering their rights to life,development,and health.Japan’s inadequate efforts in victim resettlement and environmental restoration have jeopardized the environmental and food rights of its citizens to live healthily and access food in an environment unaffected by nuclear radiation.The release of nuclear-contaminated water poses a risk of Japan’s nuclear pollution to the people of neighboring countries and the global population at large.The principle of human rights underpins the theory of a community with a shared future for humanity,and human rights are a crucial area of China’s active participation in United Nations affairs and global governance.By voicing concerns over Japan’s potential human rights violations globally,China demonstrates its role as a responsible major country.In response to Japan’s breach of legal obligations and human rights violations,China can adopt a reasoned and beneficial approach,including calling on the international community to hold Japan criminally accountable for crimes against humanity under the Rome Statute and advancing scholarly discussions on ecocide and crimes against the marine environment.Furthermore,China should persist in seeking advisory opinions from the International Court of Justice and strive for substantive accountability,utilizing the mechanisms of international human rights organizations to make its voice heard.

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.

Hourly Wage and the Likelihood of Stealing an Item

Researchers have extensively explored the impact of wages on individuals’ decisions to engage in property crimes. While most of these studies in the past have relied on macro-level data to investigate the relationship between crime rates and hourly wages, this paper takes a novel approach by utilizing micro-level data to examine the influence of hourly wages on the likelihood of stealing an item valued at least $50. The results obtained from the estimations reveal that an increase in hourly wage leads to a decrease in the probability of theft, all other factors being held constant. Further estimation by gender revealed that hourly wages given to both male and female have no bearing on the decision to steal. Additionally, the analysis of the differences in theft probabilities across gender and race demonstrates that males consistently exhibit a higher likelihood of engaging in theft when compared to females across various racial groups.

Committing a Crime with the Employment of a Toxic Substance

Poisons are harmful chemicals of all sorts. They are detrimental to health and can have deadly effects on the organism. Many poisonous substances have been used for poisoning others, deliberately. This had been done throughout the ages. In comparison to visibly violent and traumatic crimes involving bloodshed, acts involving poisons have occurred in more subtle methods and accordingly been preferred by actors somehow suitable for indirect and concealed modus operandi. （Doping in sports or horse racing being a lesser form of offense, it is beyond the scope of this text）.

The Influences of CPTED on Fear of Crime and Sense of Community

Fear of crime varies considerably depending on its attitude towards environmental conditions. Sense of community and CPTED （crime prevention through environmental design） are believed to have an influence on fear of crime. This paper investigates the hypotheses of influences of CPTED on FOC （fear of crime） and SOC （sense of community）. A total of 171 respondents from the designated residential areas were involved in this study. The structural equation modeling technique was employed and the results indicate that CPTED has a direct influence on fear of crime and sense of community. However, no significant relationship was found between SOC and FOC.

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

Empirical Analysis of the Effect of Higher Education on Reducing Crime Rate

The theory of pedagogy tells us that the process of the formation of individual moral character is the process of socialization. In social life, especially in the stage of school education of all types and at all levels, individuals through school education and observational learning, role playing, grasp the moral knowledge, moral conduct and specification, and will them into their own beliefs as well as forming the stable moral consciousness and finally to moral behavior, moral quality can be built up. The criminal psychology school explains the criminal behavior by Freud＇ s theory of personality structure. Freud said： ＂I＂ is the most primitive part of personality, ＂self＂ is ＂my＂ in the social environment with the development of the ＂super-me＂ is the moral of the ＂self＂ , it Guide the ＂self＂ to limit the ＂I＂ psychological impulses. ＂Super me＂ is the highest level of personality structure. Under this basis, this paper proposes the empirical analysis on the relationships. In the future, more related research will be finalized.

Perfection of the legislation of the crimes by the Chinese elderly

The nineteenth session of the Standing Committee of the Eleventh National People＇s Congress in February 25, 2011 approved the ＂PRC Criminal Law Amendment （eight）＂, which for the first time added the provision of the lenient punishment for the elderly crimes. The provision filled the legislative blank of the criminal responsibility of this special group of the old people in the criminal law of our country. But at the same time, we should also clearly see the deficiencies of the amendment （eight）. This paper attempts to sort out the rationality of the lenient application of the punishment on the older people from the aspect of the criminal policy oftemperingjustice with mercy and other aspects, and to construct and perfect the specific legislative proposals that the amendment （eight） puts forward.

Reconstructing the Data Crime Governance Model from the Perspective of Criminal Compliance

With the advent of the risk society and the era of big data,criminal law must respond to data crime in a more proactive manner.The traditional way of conviction and sentencing adopted by the current criminal law for data crime can no longer meet the requirements of the times.Compliance should be introduced into criminal law to improve the governance system of data crime.There are three ways to incorporate compliance into criminal law:(1)as the exemption cause of enterprise crime;(2)as the general circumstances of sentencing in the General Provisions of Criminal Law of the People’s Republic of China;(3)as the special circumstances of sentencing in the Specific Provisions of Criminal Law of the People’s Republic of China.The latter two approaches are more suited to China’s national conditions.

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.

Modeling the criminal's location choices in urban areas

With the method of dynamic programming, two spatial variables,the expected utility and the probability of success of each crime, are used to model the criminal's location choices in urban areas in this paper.The modeling results show that a criminal optimizes his crime locations according to the expected utility and the success probability during his planned period A criminal usually commits his first offense in the district that has the highest probability of success but a lower expected utility, and commits his last crime in the district where the expected utility is the highest and success probability is lower.If a location has both an expected utility and a higher probability of success, the criminal might commit all his offenses in thes place. The model also suggests that crime prevention measures should be adopted in accordance with local conditions. 'Covering' measures, such as patrolling, should be taken in the poor residential districts or juvenile delinquency districts, while more sophisticated and advanced measures should be introduced in the richer districts or the districts where professional criminals haunt.

The dynamics of poverty and crime

Poverty and crime are two maladies that plague metropolitan areas. The economic theory of crime[1]demonstrates a direct correlation between poverty and crime. The model considered in this study seeks to examine the dynamics of the poverty-crime system through stability analysis of a system of ordinary differential equations in order to identify cost-effective strategies to combat crime in metropolises.

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.

Quantitative Analysis of Crime Incidents in Chicago Using Data Analytics Techniques

In this paper we aim to identify certain social factors that influence,and thus can be used to predict,the occurrence of crimes.The factors under consideration for this analytic are social demographics such as age,sex,poverty,etc.,train ridership,traffic density and the number of business licenses per community area in Chicago,IL.A factor will be considered pertinent if there is high correlation between it and the number of crimes of a particular type in that community area.