In the United States, significantly more men than women were arrested for property crimes. In 2021, a total of 3,893 men and 1,190 women were arrested for arson in the United States. For property crimes in total, 483,840 men and 217,107 women were arrested in that year.

In 2022, there were slightly more female victims of violent crime than male victims in the United States, with about ********* male victims and ********* female victims. These figures are a significant increase from the previous year, when there were ********* male victims and ********* female victims. What counts as violent crime? Violent crime in the United States includes murder, rape, sexual assault, robbery, and assault. While violent crime across all areas has been steadily falling over the past few decades, the rate of aggravated assault is still relatively high, at ***** cases per 100,000 of the population. In 2021, there were more property crimes committed in the U.S. than there were violent crimes. Keep your enemies closer It is usually said that most victims know their attacker, and the data backs this up. In 2021, very few murders were committed by strangers. The same goes for rape and sexual assault victims; the majority were perpetrated by acquaintances, intimate partners, or relatives.

The General Social Survey (GSS) program gathers data on social subjects in order to monitor changes in the living conditions and well being of Canadians over time and to provide immediate information on specific social policy issues of current or emerging interest.Cycle 18 of the GSS is the fourth cycle dedicated to the topic of victimization; previous cycles were carried out in 1988, 1993, and 1999. Content from Cycle 13 on senior abuse and public perception of alternatives to imprisonment was not repeated. New topics of interest were added including stalking, use of restraining orders and social disorder. Other subjects common to all four cycles include perceptions of crime, police and courts; crime prevention precautions; and accident and crime incident reports.

This guide is for cycle 13 of the General Social Survey (GSS). Cycle 13 is the third cycle (following cycles 3 and 8) that collected information in 1999 on the nature and extent of criminal victimisation in Canada. Focus content for cycle 13 addressed two areas of emerging interest: public perception toward alternatives to imprisonment; and spousal violence and senior abuse. Other subjects common to all three cycles include perceptions of crime, police and courts; crime prevention precautions; accident and crime screening sections; and accident and crime incident reports. The target population of the GSS is all individuals aged 15 and over living in a private household in one of the ten provinces.

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Context

This dataset contains complete information about various aspects of crimes happened in India from 2001. There are many factors that can be analysed from this dataset. Over all, I hope this dataset helps us to understand better about India.

Content

1. I : Cases Reported and their Disposal by Police and Court
   1. Indian Penal Code
   2. Special & Local Laws
2. IA : SC/ST Cases Reported and their Disposal by Police and Court
   1. Crime against SCs
   2. Crime against STs

3. IB : Children Cases Reported and their Disposal by Police and Court

   1. Abetment of Suicide (Section 305 IPC)
   2. Buying of Girls for Prostitution (Section 373 IPC)
   3. Child Marriage Restraint Act, 1929
   4. Exposure and Abandonment (Section 317 IPC)
   5. Foeticide (Section 315 and 316 IPC)
   6. Infanticide (Section 315 IPC)
   7. Kidnapping & Abduction (Section 360,361,363,363-A, 363 read with Section 384, 366, 367 & 369 IPC)
   8. Murder (Section 302, 315 IPC)
   9. Other Crimes against Children
   10. Other Murder of Children (Section 302 IPC)
   11. Procuration of Minor Girls (Section 366-A IPC)
   12. Rape (Section 376 IPC)
   13. Selling of Girls for Prostitution (Section 372 IPC)
   14. Total Crimes against Children

4. II : Persons Arrested and their Disposal by Police and Court

   1. Indian Penal Code
   2. Special and Local Laws

5. IIA : SC/ST Persons Arrested and their Disposal by Police and Court

   1. Crime against SCs
   2. Crime against STs

6. IIB : Children Persons Arrested and their Disposal by Police and Court

   1. Abetment of suicide (Section 305 IPC)
   2. Buying of girls for prostitution (Section 373 IPC)
   3. Child Marriage Restraint Act, 1929
   4. Exposure and Abandonment (Section 317 IPC)
   5. Foeticide (Section 315 and 316 IPC)
   6. Kidnapping & Abduction (Section 360,361,363,363-A, 366, 367 & 369 IPC)
   7. Murder - Infanticide (Section 315 IPC)
   8. Murder - Other Murder of Children
   9. Murder (Section 302, 315 IPC)
   10. Other Crimes against Children
   11. Procuration of minor girls (Section 366-A IPC)
   12. Rape (Section 376 IPC)
   13. Selling of girls for prostitution (Section 372 IPC)
   14. Total Crimes against Children

7. IV : Persons Arrested by Sex and Age Group

   1. Indian Penal Code
   2. Special & Local Laws

8. V : Juveniles Apprehended

   1. Indian Penal Code
   2. Special & Local Laws

9. VI : Juveniles Arrested and their Disposal

10. VII : Property Stolen & Recovered (Crime Head)

    1. Dacoity
    2. Robbery
    3. Burglary
    4. Theft
    5. Criminal Breach of Trust
    6. Other Property
    7. Total Property Stolen & Recovered

11. VIII : Property Stolen & Recovered (Nature of Property)

    1. Communation and Electricity Wire
    2. Cattle
    3. Cycle
    4. Motor Vehicles
    5. Motor Vehicles - Motor Cycle/Scooters
    6. Motor Vehicles - Motor Car/Taxi/Jeep
    7. Motor Vehicles - Other Motor Vehicles
    8. Fire Arms
    9. Explosives/Explosive Substances
    10. Electronic Components
    11. Cultural Property including Antiques
    12. Other kinds of Property
    13. Total Property Stolen & Recovered

12. IX : Police Strength (Actual & Sanctioned)

    1. A) Actual Civil Police (Incl. District Armed Police and Women Police)
    2. A) Acual Armed Police (Incl. Women Police)
    3. A) Actual Police Strength (Incl. Women)
    4. B) Acual Women Civil Police (Incl. District Armed Force)
    5. B) Actual Women Armed Police
    6. B) Actual Women Police Strength
    7. C) Sanctioned Civil Police (Incl. District Armed Police)
    8. C) Santioned Armed Police (Incl. Women Police)
    9. C) Santioned Police Strength (Incl. Women)
    10. D) Sanctioned Women Civil Police (Incl. District Armed Police)
    11. D) Sanctioned Women Armed Police
    12. D) Sanctioned Women Police Strength

13. X : Police Personnel Killed or Injured on duty

    1. Constables
    2. Head Constables
    3. Assistant Sub-Inspectos
    4. Sub-Inspectors
    5. Inspectors
    6. Gazetted Officers
    7. Total Police Killed or Injured

14. X-B : Age Profile of Police Personnel Killed on Duty

15. X-C : Natural Deaths and Suicides of Police Personnel

    1. Natural Deaths of Police Personnel (while in service)
    2. Police Personnel Committed Suicide

16. XI : Casualties under Police Firing and LathiCharge

    1. Riot Control
    2. Anti Dacoity Operations
    3. Against Extremists & Terrorists
    4. Against Others
    5. Total Casualties

17. XII : Cases Reported Value of Property Stolen under Dacoity, Robbery, Burglary and Theft by Place of Occurance

    1. Residential Premises
    2. Highways
    3. River and Sea
    4. Railways 4.1 In Running Trains 4.2 Others
    5. Banks
    6. Commercial Establishments (Shops etc.)
    7. Other Places
    8. Total

18. XIII : Particulars of Juveniles Arrested

    1. Education
    2. Economic Setup
    3. Family Background
    4. Recidivism

19. XIV : Motive/Cause of Murder ...

In 2023, approximately 50,000 cases of violence against women were reported in the city of Rio de Janeiro. With over 18,000 cases, psychological violence, such as threatening behavior, harassment, and humiliation, was the category with the most reported cases, while property damage was the least reported category with fewer than 2,200 cases.

In Norway, property theft was the type of crime that had the highest number of victims among both women and men in 2023. Moreover, violence and maltreatment was the type of crime with the second-highest number of victims among both men and women. Except for sexual offenses, where there were significantly more female than male victims, men made up the highest number of victims of all types of crime in Norway that year.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. This study used secondary analysis of data from several different sources to examine the impact of increased oil development on domestic violence, dating violence, sexual assault, and stalking (DVDVSAS) in the Bakken region of Montana and North Dakota. Distributed here are the code used for the secondary analysis data; the data are not available through other public means. Please refer to the User Guide distributed with this study for a list of instructions on how to obtain all other data used in this study. This collection contains a secondary analysis of the Uniform Crime Reports (UCR). UCR data serve as periodic nationwide assessments of reported crimes not available elsewhere in the criminal justice system. Each year, participating law enforcement agencies contribute reports to the FBI either directly or through their state reporting programs. Distributed here are the codes used to create the datasets and preform the secondary analysis. Please refer to the User Guide, distributed with this study, for more information. This collection contains a secondary analysis of the National Incident Based Reporting System (NIBRS), a component part of the Uniform Crime Reporting Program (UCR) and an incident-based reporting system for crimes known to the police. For each crime incident coming to the attention of law enforcement, a variety of data were collected about the incident. These data included the nature and types of specific offenses in the incident, characteristics of the victim(s) and offender(s), types and value of property stolen and recovered, and characteristics of persons arrested in connection with a crime incident. NIBRS collects data on each single incident and arrest within 22 offense categories, made up of 46 specific crimes called Group A offenses. In addition, there are 11 Group B offense categories for which only arrest data were reported. NIBRS data on different aspects of crime incidents such as offenses, victims, offenders, arrestees, etc., can be examined as different units of analysis. Distributed here are the codes used to create the datasets and preform the secondary analysis. Please refer to the User Guide, distributed with this study, for more information. The collection includes 17 SPSS syntax files. Qualitative data collected for this study are not available as part of the data collection at this time.

This survey was conducted by the Center for Urban Affairs and Policy Research at Northwestern University to gather information for two projects that analyzed the impact of crime on the lives of city dwellers. These projects were the Reactions to Crime (RTC) Project, which was supported by the United States Department of Justice's National Institute of Justice as part of its Research Agreements Program, and the Rape Project, supported by the National Center for the Prevention and Control of Rape, a subdivision of the National Institute of Mental Health. Both investigations were concerned with individual behavior and collective reactions to crime. The Rape Project was specifically concerned with sexual assault and its consequences for the lives of women. The three cities selected for study were Chicago, Philadelphia, and San Francisco. A total of ten neighborhoods were chosen from these cities along a number of dimensions -- ethnicity, class, crime, and levels of organizational activity. In addition, a small city-wide sample was drawn from each city. Reactions to crime topics covered how individuals band together to deal with crime problems, individual responses to crime such as property marking or the installation of locks and bars, and the impact of fear of crime on day-to-day behavior -- for example, shopping and recreational patterns. Respondents were asked several questions that called for self-reports of behavior, including events and conditions in their home areas, their relationship to their neighbors, who they knew and visited around their homes, and what they watched on TV and read in the newspapers. Also included were a number of questions measuring respondents' perceptions of the extent of crime in their communities, whether they knew someone who had been a victim, and what they had done to reduce their own chances of being victimized. Questions on sexual assault/rape included whether the respondent thought this was a neighborhood problem, if the number of rapes in the neighborhood were increasing or decreasing, how many women they thought had been sexually assaulted or raped in the neighborhood in the previous year, and how they felt about various rape prevention measures, such as increasing home security, women not going out alone at night, women dressing more modestly, learning self-defense techniques, carrying weapons, increasing men's respect of women, and newspapers publishing the names of known rapists. Female respondents were asked whether they thought it likely that they would be sexually assaulted in the next year, how much they feared sexual assault when going out alone after dark in the neighborhood, whether they knew a sexual assault victim, whether they had reported any sexual assaults to police, and where and when sexual assaults took place that they were aware of. Demographic information collected on respondents includes age, race, ethnicity, education, occupation, income, and whether the respondent owned or rented their home.

The datasert contains year-, state- and city-wise historiclally compiled data on the number of cyber crimes committed in violation of Indian Penal Code (IPC) in Indian cities with over one million population. The different types of cyber crimes covered in the dataset include Abetment of Suicide - Online, Cyber Stalking or Bullying of Women or Children, Data theft, Cheating, Forgery, Defamation or Morphing (IPC r/w Indecent Representation of Women Act), Fake Profile (IPC r/w SLL), Counterfeiting, Cyber Blackmailing or Threatening, Fake News on Social Media, Other Offences (r/w IT Act), Fabrication of False Evidence/Destruction of Electronic Records for, Evidence, Offences By or Against Public Servant, False Electronic Evidence, Destruction of Electronic Evidence, Crimes of Property or Mark such as Counterfeiting, Tampering, Currency or Stamps, Crimes of Fraud such as Crimes related to Credit or Debit Card, Any Time Machines (ATMs), Online Banking Fraud, OTP Frauds, Crimes of Criminal Breach of Trust or Fraud such as crimes of Credit or Debit card, Crimes of Counterfeiting of Currecy, Stamps and Tampering, etc.

【リソース】WHITE PAPER ON CRIME 2007 / / PREFACE / NOTES / Principal Data_1 / Reported cases and crime rate / Persons cleared / Clearance rate / Overview_1 / Homicide_1 / Robbery / Fraud, etc. / Rape and forcible indecency / Damage to property / Giving and acceptance of bribes, etc. / Organized crime / Theft_1 / Principal Data_2 / Principal Special Act Offenses / Violations of the Minor Offenses Act, etc. / Violations of the Child Welfare Act, etc. / Violations of the Stalker Control Act, etc. / Violations of the Public Offices Election Act / Offenses Related to Newly Established Acts / Trends in traffic offenses / Disposition by public prosecutors offices_1 / Disposition by courts_1 / Recent legislations_1 / Tax evasion / Economic offenses / Financial offenses / Intellectual property-related offenses / Bankruptcy-related offenses / Newly established act-related offenses / Trends in high-technology offenses / Disposition by public prosecutors offices_2 / Comparison of Crime Trends with Other Countries / Major Offenses / Homicide_2 / Theft_2 / Offenses Committed by Japanese Nationals Outside Japan / Crime Victimization of Japanese Nationals Outside Japan / Overview_2 / Prosecution / Reception of Suspected Cases / Arrest and Detention of Suspects / Dispositions by Public Prosecutors Offices_1 / Trial / Defendants with a final judgement / The first instance / Appeals / Death penalty and life imprisonment with work / Imprisonment with or without work for a definite term / Fines / Detention and Bail / Correction of Adult Offenders / Rate of imprisonment of penal institutions / Number of inmates of penal institutions / Trend in number of newly admitted sentenced inmates / Characteristics of newly admitted sentenced inmates / Overview of treatment / Work / Correctional guidance / Medical care and hygiene, etc. / Maintenance of discipline and order / Grievance systems / Cooperation from outside volunteers / Penal Institution Visiting Committee / Fine defaulters in workhouses / Treatment of Unsentenced Inmates, etc. / Enforcement of Penal and Detention Facilities Act / Countermeasures to overcrowding / New treatment systems of inmates / Rehabilitation Services / Parole_1 / Number of parole applications / Number of parolees / Percent distribution of served sentence terms before parole / Parole of life imprisonment inmates / Probation / Parole Supervision_1 / Probationers / parolees under supervision / Treatment of probationers / parolees / Measures for probationers / parolees / Termination of probation / parole supervision / Assistance during supervision and urgent aftercare of discharged offenders / Halfway houses / Pardons / Nongovernmental support organizations / Crime prevention activities / Developments leading to the reform / Major contents of the reform / Trends in International Efforts in Criminal Justice / Measures against transnational organized crimes / Measures against terrorism and money laundering / Measures against drug-related offenses / Measures against crimes involving women and children / Measures against bribery and corruption / Measures against cybercrime / Transfer of sentenced persons / The International Criminal Court / Transnational fugitives from Japan / Extradition of fugitive offenders / Assistance in investigation, etc. / Judicial assistance / Newly entering foreign nationals / Foreign nationals who are illegally overstaying / Deportation / Penal code offenses / Special act offenses / Disposition by public prosecutors offices_3 / Disposition by courts_2 / Correction_1 / Probation and parole supervision / Trends in Boryokudan Members / Penal code offenses and special act offenses / Firearm offenses / Dispositions by public prosecutors offices_2 / Correction_2 / Probation / parole supervision_2 / Stimulants Control Act violations / Narcotics and Psychotropics Control Act violations, etc. / Poisonous and Deleterious Substances Control Act violations / Seizure of stimulants, etc. / Implementation of the Act on Special Provisions for Narcotics / Disposition by public prosecutors offices_4 / Disposition by courts_3 / Correction_3 / Probation / parole supervision_3 / Trends in Crimes / Disposition by public prosecutors offices and courts / Correction_4 / Probation / parole supervision_4 / The Medical Supervision of Mentally Disordered Offenders Act / Hearings pertaining to public prosecutor's application / Medical care by hospitalization / Hearings pertaining to discharge or continuation of hospitalization / Treatment in local communities / Trends in Juvenile Delinquency / Juvenile delinquency / Juvenile delinquents / Number of juveniles cleared / Trends by attribute / Trends by type of offense / Complicity cases / Number of juveniles referred by the police / Drug offenses / Traffic offenses / Juveniles of Illegal Behavior under 14 Years of Age / Pre-delinquents / Domestic violence / Violence in schools / Bullying and delinquency / Overview_3 / Flow of procedures until referred to a family court /

each model adjusted for age, race, education, income, marital status, stratum.*model of factors associated with having done theft or robbery 3+ times.

Real-world Anomaly Detection in Surveillance Videos

Surveillance videos are able to capture a variety of realistic anomalies. In this paper, we propose to learn anomalies by exploiting both normal and anomalous videos. To avoid annotating the anomalous segments or clips in training videos, which is very time consuming, we propose to learn anomaly through the deep multiple instance ranking framework by leveraging weakly labeled training videos, i.e. the training labels (anomalous or normal) are at video-level instead of clip-level. In our approach, we consider normal and anomalous videos as bags and video segments as instances in multiple instance learning (MIL), and automatically learn a deep anomaly ranking model that predicts high anomaly scores for anomalous video segments. Furthermore, we introduce sparsity and temporal smoothness constraints in the ranking loss function to better localize anomaly during training. We also introduce a new large-scale first of its kind dataset of 128 hours of videos. It consists of 1900 long and untrimmed real-world surveillance videos, with 13 realistic anomalies such as fighting, road accident, burglary, robbery, etc. as well as normal activities. This dataset can be used for two tasks. First, general anomaly detection considering all anomalies in one group and all normal activities in another group. Second, for recognizing each of 13 anomalous activities. Our experimental results show that our MIL method for anomaly detection achieves significant improvement on anomaly detection performance as compared to the state-of-the-art approaches. We provide the results of several recent deep learning baselines on anomalous activity recognition. The low recognition performance of these baselines reveals that our dataset is very challenging and opens more opportunities for future work.

Problem & Motivation

One critical task in video surveillance is detecting anomalous events such as traffic accidents, crimes or illegal activities. Generally, anomalous events rarely occur as compared to normal activities. Therefore, to alleviate the waste of labor and time, developing intelligent computer vision algorithms for automatic video anomaly detection is a pressing need. The goal of a practical anomaly detection system is to timely signal an activity that deviates normal patterns and identify the time window of the occurring anomaly. Therefore, anomaly detection can be considered as coarse level video understanding, which filters out anomalies from normal patterns. Once an anomaly is detected, it can further be categorized into one of the specific activities using classification techniques. In this work, we propose an anomaly detection algorithm using weakly labeled training videos. That is we only know the video-level labels, i.e. a video is normal or contains anomaly somewhere, but we do not know where. This is intriguing because we can easily annotate a large number of videos by only assigning video-level labels. To formulate a weakly-supervised learning approach, we resort to multiple instance learning. Specifically, we propose to learn anomaly through a deep MIL framework by treating normal and anomalous surveillance videos as bags and short segments/clips of each video as instances in a bag. Based on training videos, we automatically learn an anomaly ranking model that predicts high anomaly scores for anomalous segments in a video. During testing, a longuntrimmed video is divided into segments and fed into our deep network which assigns anomaly score for each video segment such that an anomaly can be detected.

Method

Our proposed approach (summarized in Figure 1) begins with dividing surveillance videos into a fixed number of segments during training. These segments make instances in a bag. Using both positive (anomalous) and negative (normal) bags, we train the anomaly detection model using the proposed deep MIL ranking loss. https://www.crcv.ucf.edu/projects/real-world/method.png

UCF-Crime Dataset

We construct a new large-scale dataset, called UCF-Crime, to evaluate our method. It consists of long untrimmed surveillance videos which cover 13 realworld anomalies, including Abuse, Arrest, Arson, Assault, Road Accident, Burglary, Explosion, Fighting, Robbery, Shooting, Stealing, Shoplifting, and Vandalism. These anomalies are selected because they have a significant impact on public safety. We compare our dataset with previous anomaly detection datasets in Table 1. For more details about the UCF-Crime dataset, please refer to our paper. A short description of each anomalous event is given below. Abuse: This event contains videos which show bad, cruel or violent behavior against children, old people, animals, and women. Burglary: This event contains videos that show people (thieves) entering into a building or house with the intention to commit theft. It does not include use of force against people. Robbery: This event contains videos showing thieves taking money unlawfully by force or threat of force. These videos do not include shootings. Stealing: This event contains videos showing people taking property or money without permission. They do not include shoplifting. Shooting: This event contains videos showing act of shooting someone with a gun. Shoplifting: This event contains videos showing people stealing goods from a shop while posing as a shopper. Assault: This event contains videos showing a sudden or violent physical attack on someone. Note that in these videos the person who is assaulted does not fight back. Fighting: This event contains videos displaying two are more people attacking one another. Arson: This event contains videos showing people deliberately setting fire to property. Explosion: This event contains videos showing destructive event of something blowing apart. This event does not include videos where a person intentionally sets a fire or sets off an explosion. Arrest: This event contains videos showing police arresting individuals. Road Accident: This event contains videos showing traffic accidents involving vehicles, pedestrians or cyclists. Vandalism: This event contains videos showing action involving deliberate destruction of or damage to public or private property. The term includes property damage, such as graffiti and defacement directed towards any property without permission of the owner. Normal Event: This event contains videos where no crime occurred. These videos include both indoor (such as a shopping mall) and outdoor scenes as well as day and night-time scenes. https://www.crcv.ucf.edu/projects/real-world/dataset_table.png https://www.crcv.ucf.edu/projects/real-world/method.png

In 2023, there were 91.23 criminal offenses reported per 1,000 inhabitants in Finland. Despite a decreasing trend until recent years, 2020 saw a considerable increase in the number of crimes, having reached a high of 98.2 per 1,000 population. Finland has one of the lowest incarceration rates in Europe In general, Finland is known as a safe country, with crime levels being comparable to those of other Nordic countries. Traffic offenses, along with property offenses, are the most common types of crime. In terms of imprisonment, Finland has one of the lowest incarceration rates in Europe. Currently, Finland has several closed and open prisons, which a focus on rehabilitation and reintegration into society. This “softer” approach to punishing crime has also been linked to falling recidivism rates. Sexual and domestic violence most often affects women Women constituted almost 67.8 percent of domestic violence victims in Finland in 2023. Furthermore, the number of female, as well as male, victims was higher than in the previous year. The Finnish government is addressing this problem by promoting sexual and reproductive health and the rights of women and girls, along with placing the human rights of women as one of its priorities.

Context

The creation of this dataset was inspired by some of the extremely tragic deaths of young women in the name of dowry in the recent past in India.

Dowry is the term for an illegal transaction of valuable property (currency, land, gold, vehicle etc.) between the bride's family and the groom and his family. This practice even though illegal since 1961 has been quite prevalent in India.

In the past, since it was not common for women to be earning members of the family, it was common for the bride's family to provide financial support to the groom. Even though it has been abolished, it is not uncommon for the family of the groom to explicitly ask for a particular sum in cash, a certain amount of gold, real estate or any other valuables.

Relationships based on such transactions can turn sour quite quickly. Especially if the groom or his family is dissatisfied with the amount they received which leads to abuse (mental and physical) and then finally murder or suicide.

Content

The data was downloaded from the Open Government Data Platform India. The files contain data from the years 2001 to 2014.

Each data point represents state-wise dowry-related deaths.

Column Details:

1. State - The name of the state
2. Year - The year the case was reported
3. Cases Pending Investigation from Previous Year a. Cases that were reported in the previous year, but its status is still pending
4. Cases reported during the year a. Cases reported
5. No. of cases withdrawn by the Govt. during investigation
6. Cases not investigated or in which investigation was refused
7. Cases declared false on account of mistake of fact or of law
8. Cases in which chargesheets were laid - According to the Law Times Journal, ‘As per section 174 of the Code of Criminal Procedure, 1973, a report which is made by the police officers after completion of the final investigation is known as the chargesheet. The report is related to the crime which is held against the plaintiff by the accused in order to collect the evidence. This report includes all the procedures from the time a crime is reported to the place where the crime has happened. This report has to be submitted in the court of law for starting a criminal procedure against the accused.’
9. Cases in which charge-sheets were not laid but final report submitted during the year a. The number of cases in which a final report of the investigation has been submitted but chargesheet has not been laid
10. Total cases (Chargesheeted + Final Report submitted)
11. Cases pending investigation at the end of the year
12. Cases pending trial from the previous year
13. Cases sent for trial during the year
14. No. of cases withdrawn by the Govt.
15. Total cases for trial during the year
16. Cases compounded or withdrawn
17. Cases in which trials were completed
18. Cases convicted
19. Cases acquitted or discharged
20. Cases pending trial at the end of the year

Acknowledgements

The data collected from the Open Government Data Platform India.

In 2023, around 633 of 100,000 females in Germany aged 14 to 18 years were victims of crimes against sexual self-determination in Germany. The data show both attempted and completed criminal acts.

Among all criminal offenses recorded in Germany in 2023, simple theft had the highest share at 19.7 percent. Fraud and aggravated theft rounded up the top three.

In 2024, the number of sexual assault arrests in South Korea amounted to around 20,320 cases, showing a decrease from the previous two years. The figures have been fluctuating in the past few years. Increase in sex crimes in South Korea Sexual assault refers to a range of physical and psychological violations that occur without the explicit consent of the victim, which includes serious offenses such as rape and attempted rape, as well as various forms of indecent acts carried out through coercion. In recent years, South Korea has witnessed a spike in these crimes, despite the country scoring relatively high on the order and security index within the Asia-Pacific region. This increase is particularly alarming with regard to molka, a term referring to illegal secret filming, commonly involving hidden cameras used to capture non-consensual images and videos of individuals in private settings. Government policies and law enforcement The issue of sexual violence resonates deeply within South Korean society, with a significant number of women identifying it as one of the most critical social challenges. Despite this acknowledgment, the legal framework surrounding sexual offenses remains comparatively lenient by international standards. Many sex offenders receive punishments that do not adequately reflect the severity of their crimes. A recent survey found that nearly 70 percent of South Koreans expressed dissatisfaction with the government's crime prevention policies.

In 2024, there were 301,623 cases filed by the National Crime Information Center (NCIC) where the race of the reported missing person was white. In the same year, 17,097 people whose race was unknown were also reported missing in the United States. What is the NCIC? The National Crime Information Center (NCIC) is a digital database that stores crime data for the United States, so criminal justice agencies can access it. As a part of the FBI, it helps criminal justice professionals find criminals, missing people, stolen property, and terrorists. The NCIC database is broken down into 21 files. Seven files belong to stolen property and items, and 14 belong to persons, including the National Sex Offender Register, Missing Person, and Identify Theft. It works alongside federal, tribal, state, and local agencies. The NCIC’s goal is to maintain a centralized information system between local branches and offices, so information is easily accessible nationwide. Missing people in the United States A person is considered missing when they have disappeared and their location is unknown. A person who is considered missing might have left voluntarily, but that is not always the case. The number of the NCIC unidentified person files in the United States has fluctuated since 1990, and in 2022, there were slightly more NCIC missing person files for males as compared to females. Fortunately, the number of NCIC missing person files has been mostly decreasing since 1998.

The city states of Berlin, Hamburg and Bremen were the states with the three highest crime rates in Germany in 2020, while the federal state of Bavaria had the lowest. Urban areas generally have higher crime rates than rural ones, making it difficult to compare Germany's three city states with the much larger federal states, which typically cover quite large areas. The federal state with the highest crime rate was Saxony-Anhalt at 7996 crimes per 100 thousand people, compared with the German average of 6209.