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。

Detection and Mapping of Violent Crime Hotspots in Southwestern Nigeria

The increasing rate of insecurity in Nigeria, especially the southwest requires a paradigm shift from popular approach to crime hotspots detection. This study employed geospatial technologies to integrate spatio-temporal crime, social media and field observation data from the communities in all the six states in the southwest to develop crime hotspots that can serve as preliminary information to assist in allocating resources for crime control and prevention. Historical crime data from January 1972 to April, 2021 were compiled and updated with rigorous field survey in September, 2021. The field data were encoded, input to the SPSS 17 and analyzed using descriptive statistics and multivariate analysis. A total 936 crime locations data were geolocated and exported to ArcGIS 10.5 for spatial mapping using point map operation and further imported to e-Spatial web-based and QGIS for the generation of hotspot map using heatmap tool. The results revealed that armed robbery, assassination and cultism were more pronounced in Lagos and Ogun States. Similarly, high incidences of farmers/herdsmen conflicts are observed in Oyo and Osun States. Increasing incidences of kidnapping are common in all the south-western states but very prominent in Ondo, Lagos and Oyo States. Most of the violent crime incidents took place along the highways, with forests being their hideouts. Violent crimes are dominantly caused by high rate of unemployment while farmer/herdsmen conflicts were majorly triggered by the scarcity of grazing fields and destruction of arable crops. The conflicts have resulted in the increasing cases of rape and disruption of social group, intake of hard drugs, cult-related activities, low income and revenue generation, and displacement of farmers and infrastructural damages. The study advocates regular retraining and equipping of security agents, establishment of cattle ranch, and installation of sophisticated IP Camera at the crime hotspots to assist in real-time crime monitoring and management.

Spatial Pattern and Distribution of Crime in Suleja Lga, Niger State, Nigeria

The study examines the Spatial Pattern and Distribution of Crime in Suleja LGA, Niger State, Nigeria. The study used GIS and statistical methods to analyse the pattern and distribution of crime incidence in the study area. The records of each crime incidence were geocoded. Microsoft Excel was used to collate and organise the crime entries before they were imported into the ArcGIS Pro 2.0 environment. A geodatabase was created where the spatial and aspatial data were encoded and geospatial analysis was performed. The study reveals that the crime distribution pattern is generally clustered with a Global Moran’s I index of 0.097, a Z-score of 1.87, and a P-value < 0.06. Furthermore, the study reveals that armed robbery (61), kidnapping (40), car theft (33), culpable homicide (31), rape (29), and robbery (13) cases rank the highest in crime rate. Equally, findings of the study show that Chaza, Kwamba, Madalla, Suleja central, and Gaboda are the major crime hotspot zones at 90% confidence, as analysed using the Getis-Ord Gi* (Hot spot analysis) spatial statistics tool in ArcGIS Pro 2.0. The research therefore recommends that more effort be put into fighting crime, especially in areas where there are low-security formations, as they mostly have the highest record of crimes committed. Also, the patrol units should be equipped with GPS for better surveillance and real-time tracking of criminal activities.

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。

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.

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.

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。

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.

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.

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%.

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.

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.

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.

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.

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.

Practice and Thinking of Grid Management to Promote Crime Prevention and Control in Urban Community

Practice and Thinking of Grid Management to Promote Crime Prevention and Control in Urban

Preliminary Study on Crime Prevention of Left-behind Children in Rural China

In the process of social and economic development in China,there appears the inevitable problem of crime of left-behind children.Extensive researches and disputes prove that it is,to a greater extent,a social phenomenon resulted from social factors. It is recommended to improve the treatment of migrant workers and solve the problem of school admission for their children,provide effective legal education for those left-behind children whose problem can not be solved in a short term,and supplement the guardianship role to control the crime rate of leftbehind children. Another more effective method is to resume effective control of people's social life through the rural cultural tradition,to fundamentally prevent crime of left-behind children.

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.