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The presence of gunshot residue (GSR) in a sample can provide valuable information in forensic investigations by associating a suspect with a shooting incident. However, in order to have confidence in the integrity of the results' interpretation, the possibility of contamination by secondary transfer of GSR occurring during the transportation of a person under custody in a police vehicle should be evaluated. In order to investigate police vehicles as a source for secondary transfer of GSR particles, a total of 51 samples were collected from the rear seats of random police vehicles and used to transport arrested individuals. Results indicated that the type of upholstery of the seats plays a main role in determining the potential for secondary GSR contamination. The potential chance of coming into contact with GSR particles in police vehicles is low. GSR contamination from police vehicles is, maybe, not of a major concern but should be taken into consideration mainly when very few characteristic GSR particles are found on an analyzed sample. [ABSTRACT FROM AUTHOR]

Objectives: This study developed multivariate law enforcement officer (LEO) body models for digital simulation of LEO accommodation in police cruiser cabs. Background: Anthropometrically accurate digital LEO body models, representing the United States LEOs, for computerized LEO cruiser interface simulations are lacking. Methods: Twenty body dimensions (with and without gear combined) of 756 male and 218 female LEOs were collected through a stratified national survey using a data collection trailer that traveled across the US. A multivariate Principal Component Analysis (PCA) approach was used to develop digital LEO body models. Results: Fifteen men and 15 women representing unique body size and shape composition of the LEO population were identified. A combined set of 24 male and female models (removal of 6 redundant models for which female and male models overlapped) is suggested. Conclusions: A set of 24 digital LEO body models in 3-dimensional form, along with their anthropometric measurements, were developed to facilitate LEO cruiser cab design. Application: Digital modeling software developers can use the models and their anthropometric data to build digital avatars for simulated evaluation of LEO cruiser cab configuration, console communication-equipment fitting, and cruiser ingress/egress access arrangement. LEO vehicle and equipment designers also can use eight key body dimensions (i.e., stature, buttock-popliteal length, eye height sitting, knee height sitting, shoulder-grip length, popliteal height, sitting height, and body weight) of the body models to recruit 24 human subjects to physically evaluate their vehicle prototypes for improved vehicle and equipment design. [ABSTRACT FROM AUTHOR]

This paper addresses a real‐world multi‐period orienteering problem arising in a large Italian company that needs to patrol an area in order to provide security services to a set of customers. Each customer requires different services on a weekly basis. Some services are mandatory, while others are optional. It might be impossible to perform all optional services, and each of them is assigned a score when performed. The challenge is to determine a set of routes, one per day, that maximizes a weighted sum of the total collected score and total working time, while meeting several operational constraints, including hard time windows, maximum riding time, minimum number of services performed, and minimum time between two consecutive visits for the same service at the same customer. To solve the problem, we propose an iterated local search that invokes at each iteration an inner variable neighborhood descent procedure. Computational tests performed on a large number of real‐world instances prove that the developed algorithm is very efficient, and finds in a short time solutions that are consistently better than those produced by a mathematical model, and those in use at the company. [ABSTRACT FROM AUTHOR]

Objectives: This study investigated anthropometric changes of national law enforcement officers (LEOs) in 46 years, compared the differences between LEO data and civilian anthropometry, and identified the magnitude of differences in dimensions measured with gear versus semi-nude measurements. Background: The best available 46-year-old anthropometric dataset of LEOs has largely become outdated due to demographic changes. Additionally, anthropometric data of female LEOs and LEO measurements with gear are lacking. Method: Thirty-four traditional body dimensions and 15 with gear measurements of 756 male and 218 female LEOs were collected through a stratified national survey using a data collection trailer that traveled across the U.S. and the data were compared to the LEO anthropometric data from 1975 and existing civilian anthropometric databases. Results: LEO body size and shape have evolved over the past 46 years - an increase of 12.2 kg in body weight, 90 mm in chest circumference, and 120 mm in waist circumference for men. No previous data was available for comparison for females. Compared to civilians, both male and female LEOs have a larger upper body build. LEO gear added 91 mm in waist breadth for men and 120 mm for women, and 11 kg in weight for men and 9 kg for women. Conclusion: The study reveals that equipment design based on the existing civilian datasets or 46-year-old LEO dataset would not accommodate the current LEO population. The new data fill this gap. Application: The differences reported above are important for LEO body gear, vehicle console, and vehicle ingress/egress design. [ABSTRACT FROM AUTHOR]

Recent scholarship has observed how private security actors often draw upon the cultural and symbolic capital of the police in their everyday operations. This practice can range from issuing frontline private security officers with police-like uniforms and patrol cars to recruiting former senior police officers into highly visible corporate positions. Geographical variations in this dynamic are little understood, however. In this article, we identify and shed light upon one emergent pattern. In those countries where the police enjoy high levels of public trust and confidence, private security actors can be found openly and directly borrowing from the cultural and symbolic capital of this key state institution to enhance their status. By contrast, in those countries where the police are plagued by a poor reputation, these actors commonly display a far more ambiguous relationship with these forms of capital, working both through and against them, often at the same time. Focusing on the UK and Mexican cases, and drawing upon a combination of Bourdieusian frameworks, we argue that the key to understanding this pattern is the distinction between the objectified (non-human) cultural capital of the police (uniforms, vehicles, etc) and the embodied (human) cultural capital of the police (police officers themselves). While the former enjoys a symbolic value in the market for security which transcends variations in public trust and confidence in the police, the latter is far more intimtately connected to localised police traditions and practices, good or bad. This in turn leads to novel patterns in the global plural policing landscape. [ABSTRACT FROM AUTHOR]

When designing a patrol route, it is often necessary to pay more attention to locations with high crime rates. In this paper, we study a patrol routing problem for a fleet of patrol cars patrolling a region with a high-crime neighborhood (HCN) consisting of multiple hot spots. Considering the disorder and chaos in the HCN, at least one patrol car is required in the HCN at any given time during the patrol. We call this routing problem the hot spot coverage patrol problem (HSCPP). In the HSCPP, the importance of a patrol location is quantified by a prize, and the prize is collected if a patrol car visits the location. Our objective is to maximize the sum of prizes collected by the patrol cars, obeying all operational requirements. We propose mathematical formulations and develop several solution approaches for the HSCPP. The global approach consists of finding the routing solution for all patrol cars with a single integer programming (IP) formulation. The partition approach involves first partitioning the region geographically and solving the routing problem in each subregion with two IP formulations. Next, we strengthen the partition approach by developing a column generation (CG) approach in which the initial columns of the CG approach are the solutions generated from the partition approach. We conduct a detailed computational case study using instances based on real crime data from Montgomery County, Maryland. To further understand the computational tractability of our solution approaches, we also perform a sensitivity analysis using synthetic instances under various scenarios. History: Accepted by Erwin Pesch, Area Editor for Heuristic Search & Approximation Algorithms. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information (https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.0192) as well as from the IJOC GitHub software repository (https://github.com/INFORMSJoC/2022.0192). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/. [ABSTRACT FROM AUTHOR]

Copyright of Riwayat: Educational Journal of History & Humanities is the property of Riwayat: Educational Journal of History & Humanities and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Black spot identification, a spatiotemporal phenomenon, involves analysing the geographical location and time-based occurrence of road accidents. Typically, this analysis examines specific locations on road networks during set time periods to pinpoint areas with a higher concentration of accidents, known as black spots. By evaluating these problem areas, researchers can uncover the underlying causes and reasons for increased collision rates, such as road design, traffic volume, driver behaviour, weather, and infrastructure. However, challenges in identifying black spots include limited data availability, data quality, and assessing contributing factors. Additionally, evolving road design, infrastructure, and vehicle safety technology can affect black spot analysis and determination. This study focused on traffic accidents in Greek road networks to recognize black spots, utilizing data from police and government-issued car crash reports. The study produced a publicly available dataset called Black Spots of North Greece (BSNG) and a highly accurate identification method. Dataset:  https://github.com/iokarama/BSNG-dataset (accessed on 15 June 2023). Dataset License: CC-BY-NC [ABSTRACT FROM AUTHOR]

In this study, we consider integer-valued autoregressive conditional heteroscedastic (INGARCH) time series models of counts whose conditional density follows an multiple values-inflated one parameter exponential family. We check the stationarity and ergodicity of the models and verify the consistency and asymptotic normality of the conditional maximum likelihood estimator (CMLE) under regularity conditions. Then, as an application, we consider a parameter change test using the cumulative sum (CUSUM) test based on (standardized) residuals and squares of those residuals, then subsequently derive their limiting null distributions. A simulation study is conducted focusing on the 0-1-inflated time series of counts, which affirms the validity of the proposed methods. Moreover, a real data analysis using the number of monthly drug cases in the 32nd police car beat in Pittsburgh is also provided to further strengthen the validity of our methods. [ABSTRACT FROM AUTHOR]

As the population increases, the number of motorized vehicles on the roads also increases. As the number of vehicles increases, traffic congestion occurs. Traffic lights are used at road junctions, intersections, pedestrian crossings, and other places where traffic needs to be controlled to avoid traffic chaos. Due to traffic lights installed in the city, queues of vehicles are formed on the streets for most of the day, and many problems arise because of this. One of the most important problems is that emergency vehicles, such as ambulances, fire engines, police cars, etc., cannot arrive on time despite traffic priorities. Emergency vehicles such as hospitals and police departments need to reach the scene in a very short time. Time loss is a problem that needs to be addressed, especially for emergency vehicles traveling in traffic. In this study, ambulances, fire brigades, police, etc., respond to emergencies. A solution and a related application have been developed so privileged vehicles can reach their target destination as soon as possible. In this study, a route is determined between the current location of an emergency vehicle and its target location in an emergency. Communication between traffic lights is provided with a mobile application developed specifically for the vehicle driver. In this process, the person controlling the lights can turn on the traffic lights during the passage of vehicles. After the vehicles with priority to pass passed, traffic signaling was normalized via the mobile application. This process was repeated until the vehicle reached its destination. [ABSTRACT FROM AUTHOR]

Objective: A recent study by Kidd (2022) recommended that organizations evaluating front crash prevention (FCP) systems like automatic emergency braking and forward collision warning increase speed differentials in existing test scenarios from 25 mph to 45 mph to make the tests more representative of police-reported rear-end crashes. Kidd used the posted speed limit as a proxy for the striking vehicle's travel speed prior to the crash. The current study used velocity data from event data recorders (EDRs) in rear-end crashes to evaluate this assumption. These same data were used to replicate another study (Farmer 2003) that showed the speed limit was a poor surrogate for delta-V in rear-end crashes. Method: A total of 11,199 crash records during 2017–2020 were extracted from the Crash Investigation Sampling System database. The analysis was restricted to 436 of these records that involved two vehicles with a front-to-rear manner of collision or rear-end crash configuration with EDR data from the striking vehicle. The relationships between the posted speed limit and striking-vehicle travel speed and between the speed limit and delta-V were modeled using regression. Results: On average, the speed limit overestimated striking-vehicle travel speed by 2 mph, but the relationship between the speed limit and travel speed was not linear. The speed limit reasonably approximated travel speed on roads with speed limits of 30 and 50 mph or higher. It slightly overestimated travel speed on roads with 40–45 mph speed limits and underestimated it on roads with limits of 25 mph or less. The probability that the striking vehicle's travel speed was 25 mph or less on any road was 0.09. In contrast, the probability of the striking vehicle's travel speed being 45 mph or less was 0.54 overall and 0.75 or higher for roads with a speed limit between 25 and 45 mph. As found in prior research, there was no significant relationship between the speed limit and delta-V. Conclusion: The posted speed limit was a reasonable surrogate for the striking vehicle's travel speed prior to police-reported rear-end crashes on roads with a speed limit above 25 mph. It was not a reasonable surrogate for delta-V. Travel speeds on roads with speed limits of 25 mph or less were much higher than the speed limit, which suggests that existing scenarios used to evaluate FCP system performance represent travel speeds in fewer police-reported rear-end crashes than previously thought. Increasing speed differentials in existing FCP test scenarios to 45 mph would reflect the striking vehicle's travel speed in three quarters of rear-end crashes on roads with a speed limit of 45 mph or less. [ABSTRACT FROM AUTHOR]

Using unmanned aerial vehicle (UAV) real-time remote sensing to monitor diseased plants or abnormal areas of orchards from a low altitude perspective can greatly improve the efficiency and response speed of the patrol in smart orchards. The purpose of this paper is to realize the intelligence of the UAV terminal and make the UAV patrol orchard in real-time. The existing lightweight object detection algorithms are usually difficult to consider both detection accuracy and processing speed. In this study, a new lightweight model named Swin-T YOLOX, which consists of the advanced detection network YOLOX and the strong backbone Swin Transformer, was proposed. Model layer pruning technology was adopted to prune the multi-layer stacked structure of the Swin Transformer. A variety of data enhancement strategies were conducted to expand the dataset in the model training stage. The lightweight Swin-T YOLOX model was deployed to the embedded platform Jetson Xavier NX to evaluate its detection capability and real-time performance of the UAV patrol mission in the orchard. The research results show that, with the help of TensorRT optimization, the proposed lightweight Swin-T YOLOX network achieved 94.0% accuracy and achieved a detection speed of 40 fps on the embedded platform (Jetson Xavier NX) for patrol orchard missions. Compared to the original YOLOX network, the model accuracy has increased by 1.9%. Compared to the original Swin-T YOLOX, the size of the proposed lightweight Swin-T YOLOX has been reduced to two-thirds, while the model accuracy has slightly increased by 0.7%. At the same time, the detection speed of the model has reached 40 fps, which can be applied to the real-time UAV patrol in the orchard. [ABSTRACT FROM AUTHOR]

Copyright of Cuestiones Políticas is the property of Revista Cuestiones Politicas and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article discussed about ambush attacks of police in patrol vehicles. Topics include history of Ambushes of Law Enforcement Officers; history of anti-ambush drills, in which deputies were put through the worst training situations; and police traning utilization of both handgun and rifle in countering an ambush or sudden attack upon the student officer or officers in a police vehicle.

Much research explores the correlates of clearing fatal shooting incidents. It is suggested that common investigative resources and tactics, such as the number of detectives and witness interviews, may be associated with clearing both fatal and non-fatal shooting cases. This study examines the effect of a standardized list of investigative tools in the clearing of non-fatal shooting incidents. For this study, detectives from the Buffalo Police Department's Gun Violence Unit completed an "Investigative Checklist" for non-fatal shootings that occurred between November 2019 and December 2020 (N = 234 usable cases). Bivariate correlation analysis shows a strong association between uncooperative victims and a detective conducting multiple canvases as part of the investigation. Logistic regression shows that examining a suspect's social media information, and detectives accessing patrol car reports, contributed to successfully clearing a non-fatal shooting case. An uncooperative victim was negatively associated with clearing a case. Police practitioners should be aware, based on the findings of this and other research, that a small number of investigative techniques contribute to non-fatal shooting case clearance rates. It may be necessary for police agencies to construct detective units, and focus on a narrow set of investigative tactics, in a way that improved clearance rates in non-fatal shootings. [ABSTRACT FROM AUTHOR]

Problem definition: We consider the case of prescriptive policing, that is, the data-driven assignment of police cars to different areas of a city. We analyze key problems with respect to prediction, optimization, and evaluation as well as trade-offs between different quality measures and crime types. Academic/practical relevance: Data-driven prescriptive analytics is gaining substantial attention in operations management research, and effective policing is at the core of the operations of almost every city in the world. Given the vast amounts of data increasingly collected within smart city initiatives and the growing safety challenges faced by urban centers worldwide, our work provides novel insights on the development and evaluation of prescriptive analytics applications in an urban context. Methodology: We conduct a computational study using crime and auxiliary data on the city of San Francisco. We analyze both strong and weak prediction methods along with two optimization formulations representing the deterrence and response time impact of police vehicle allocations. We analyze trade-offs between these effects and between different crime types. Results: We find that even weaker prediction methods can produce Pareto-efficient outcomes with respect to deterrence and response time. We identify three different archetypes of combinations of prediction methods and optimization objectives that constitute the Pareto frontier among the configurations we analyze. Furthermore, optimizing for multiple crime types biases allocations in a way that generally decreases single-type performance along one outcome metric but can improve it along the other. Managerial implications: Although optimization integrating all relevant crime types is theoretically possible, it is practically challenging because each crime type requires a collectively consistent weight. We present a framework combining prediction and optimization for a subset of key crime types with exploring the impact on the remaining types to support implementation of operations-focused smart city solutions in practice. [ABSTRACT FROM AUTHOR]

In the era of the 5G network, the rapid development of information technology has made UAV technology widely used in many fields. UAVs have the characteristics of small size, lightweight, easy operation, flexibility, and so on. Drones can well solve the current problems of the insufficient police force, slow evidence collection, and harsh on-site environment. However, the existing police drones are often affected by objective conditions, such as the ground and weather when shooting, the signal is easily interrupted, and the accuracy and stability are not enough. In order to solve these problems, this article integrates the Fourier fast transform algorithm into the police unmanned aerial vehicle technology and improves the police unmanned aerial vehicle technology. By testing the police drones from four aspects of positioning and navigation, communication strength, shooting quality, and satisfaction, it can be observed how the police drones with the Fourier fast transform algorithm are optimized. Statistical experimental results show that the positioning and navigation accuracy of police drones has been improved. The communication strength command execution speed increased by 2.6%, the shooting quality increased by 6.7%, and the satisfaction rate increased by 7.3%. The Fourier fast transform algorithm makes police drones better, promotes the development of drone technology, and greatly improves the efficiency of police officers. [ABSTRACT FROM AUTHOR]

Objectives: To examine how the practice of daily proactivity affects and responds to changes in crime at micro geographic and temporal scales. Methods: Police calls for service and automated vehicle location data from a large suburban jurisdiction were used to create comprehensive measures of police proactivity. Panel data and the generalized method of moments framework were applied to tease out the endogenous relationships between crime and police proactivity and understand the unique impact of proactive patrol and crime upon one another. Results: Daily police proactivity in this locality was highly stable at micro places, although police did intensify their activities very briefly in response to recent changes in crime. In turn, increases in proactive patrol generated immediate increases in crime reporting, followed by fleeting residual deterrent effects that were weaker and less robust. The patterns remained relatively consistent when varying the units of analysis or focusing on hot spots with different profiles of proactivity, but the deterrent effects appeared more sensitive to model specification. Of all measures of proactivity, patrols of medium length and non-traffic enforcement activities were associated with stronger evidence of crime reduction effects. Conclusions: Short-term adjustments in hot spot patrols appear to produce both reporting effects and temporary residual deterrent effects as measured through calls for service and police vehicle location data. Police could potentially enhance and prolong their deterrence by adopting more deliberate strategies with their daily proactive behaviors, including making their proactive activities more targeted and sustained. [ABSTRACT FROM AUTHOR]

This article analyzes the winning films at Indonesia's 2019 Police Movie Festival "Together We Are Strong." This film festival was organized by the Public Relations of the Indonesian National Police, which is allegedly one of the police's efforts to control the media. We argue that the festival became the vehicle for police to build positive images since the media published some violent cases perpetrated by the police against civilians; or negative sentiment toward the police because several police officers held strategic positions in government. In order to find out the positive image raised by the police, we analyze the police figures in these film festival winners. The analyses include the basic ideas, characters, setting, iconography, and narrative events of the police figures. The results show that the film festival winners portrayed police as patriotic heroes who defend the country from crimes that threaten the nation's integrity through genre analysis. According to the discursive practice in film, police's images as patriotic heroes become an attempt by the police to perform their power in socio-political life, especially in Indonesia. [ABSTRACT FROM AUTHOR]

In many cases, the effects of road accidents have significant impact on human health. This translates directly into society, in both material and emotional terms. The severity of the injury in a road event depends largely on the speed of the vehicles. Excessive vehicle speed is of particular concern in incidents involving vulnerable road users. As confirmed by literature analysis and research, in most cases drivers do not respect the speed limits introduced by the road signs. Existing solutions allow to introduce permanent or temporary speed control. This paper investigates speeding and driver behaviour in built-up areas near schools and pedestrian crossings. The aim of the research described in the paper is to determine the influence of the effectiveness of police actions on speed reduction and improvement of road safety. [ABSTRACT FROM AUTHOR]