Theoretical literature indicates that public security spending matters to deter criminal behavior. Nevertheless, most empirical studies aiming to quantify the influence of public security spending on ...crime have largely been unable to establish a statistically significant relationship between these variables. In response to this, we introduced a novel proxy that measures the rationing of public security expenditures in each region. When testing it for crimes of homicide, robbery, and theft of vehicles through the GMM-SYS estimator, we found statistical evidence that its occurrence influences criminal behavior. We believe its inception contributes valuable evidence to the economic literature, shedding light on the debate surrounding the allocative efficiency of security spending resources.
La literatura teórica indica que el gasto en seguridad pública es importante para disuadir el comportamiento delictivo. Sin embargo, la mayoría de los estudios empíricos destinados a cuantificar la influencia del gasto en seguridad pública sobre la delincuencia no han podido establecer una relación estadísticamente significativa entre estas variables. En respuesta a esto, introdujimos un indicador novedoso que mide la asignación de los gastos de seguridad pública en cada región. Al probarlo para delitos de homicidio, robo y hurto de vehículos a través del estimador GMM-SYS, encontramos evidencia estadística de que su ocurrencia influye en la conducta delictiva. Creemos que su inclusión aporta evidencia valiosa a la literatura económica, arrojando luz sobre el debate en torno a la eficiencia en la asignación de recursos del gasto en seguridad.
Person Re-identification (Re-ID) is a crucial technique for public security and has made significant progress in supervised settings. However, the cross-domain ( i.e ., domain generalization) scene ...presents a challenge in Re-ID tasks due to unseen test domains and domain-shift between the training and test sets. To tackle this challenge, most existing methods aim to learn domain-invariant or robust features for all domains. In this paper, we observe that the data-distribution gap between the training and test sets is smaller in the sample-pair space than in the sample-instance space. Based on this observation, we propose a Generalizable Metric Network (GMN) to further explore sample similarity in the sample-pair space. Specifically, we add a Metric Network (M-Net) after the main network and train it on positive and negative sample-pair features, which is then employed during the test stage. Additionally, we introduce the Dropout-based Perturbation (DP) module to enhance the generalization capability of the metric network by enriching the sample-pair diversity. Moreover, we develop a Pair-Identity Center (PIC) loss to enhance the model's discrimination by ensuring that sample-pair features with the same pair-identity are consistent. We validate the effectiveness of our proposed method through a lot of experiments on multiple benchmark datasets and confirm the value of each module in our GMN.
Abstract
The security industry is generated by the needs of modern public security precaution. With the popularization of hardware and network technology, the amount of data in the field of security ...increases rapidly. Under such a condition, big data technology in the field of security arises. This paper discusses the current situation of the security industry, and discusses the related security problems in the application process of big data in the field of public security precaution. Taking the video image database application platform as an example, combined with the national standards 28181, 25724, 35114, this paper discusses the data security problems involved in the process of data acquisition and data transmission. Based on the Kerberos authentication mechanism of Hadoop, this paper introduces the big data security and access control technology, and forms relevant solutions in the whole process of data acquisition, data transmission and data access.
AI and computer vision are making strides every day with newer solutions to real-world problems and emerging challenges. An extremely important and useful application of computer vision is ...surveillance systems for security in open or closed spaces. This research work investigates a security application by forecasting crowd trajectories using surveillance videos. Generative Adversarial Networks(GANs) are commonly used for video processing applications like future frame synthesis. Social GAN(SGAN) is one of the recent models that has been used for crowd trajectory prediction. However, SGAN is a two stream architecture that keeps the background and foreground separate and predicts the foreground changes only, keeping the background static. In this paper, a novel GAN architecture called iSGAN is proposed for crowd trajectory prediction. The proposed model is an improvement of SGAN and it incorporates the onestream architecture of improved Video GAN (iVGAN) into SGAN. The one-stream architecture doesn't separate the backgroungd and foreground and thus allowing to captiure the dynamics of the video (camera zoom, pan, lighting change, obstacles etc.). The proposed iSGAN model has been assessed on the benchmark ETH Pedestrian dataset and it is found that the iSGAN Model outperforms other existing trajectory prediction models.
Resumo A política de segurança pública no Rio de Janeiro tende a ser representada pela alegoria do pêndulo, que se inclinaria predominantemente para a lógica do confronto, mas também, em curtos ...interregnos, para a lógica da aproximação. Embora as esporádicas tentativas de reversão da lógica repressiva produzam mudanças conjunturais significativas, verificamos, através de entrevistas com policiais das UPPs, que o ethos militarizado permanecia estruturando o discurso e orientando a prática cotidiana - produzindo uma condição de “crise permanente”. Procuramos, então, identificar quais fatores e percepções impactavam (negativamente) nos diversos graus de adesão e ressonância dos policiais aos princípios do “policiamento de proximidade”.
Abstract Public security policy in Rio de Janeiro tends to be represented by the pendulum allegory, which would predominantly lean towards the logic of confrontation, but also, in short intervals, to the logic of approximation. Although the sporadic attempts to reverse the repressive logic produce significant conjunctural changes, we verified, through interviews with UPP’s policemen, that the militarized ethos remained structuring the discourse and orienting daily practice - producing a condition of “permanent crisis”. We then sought to identify which factors and perceptions impacted (negatively) on the varying degrees of adherence and resonance of the police to the principles of “proximity policing”.
The development of uranyl ion detection technology has exhibited its significance in public security and environmental fields for the radioactivity and chemical toxicity of uranyl ion. The WHO ...standard of uranyl ion makes it necessary to develop highly sensitive uranyl rapid warning system in drinking water monitoring. Herein, a visualized rapid warning system for trace uranyl ion is carried out based on electrochemiluminescence (ECL) imaging technology to give an ultra-low limit of detection (LOD) and high selectivity. Amidoxime, a bi-functional group with both uranyl ion capturing and co-reactive functions, is modified on a conjugated polymer backbone with strong ECL signal to be prepared into three-in-one polymer nanoparticles (PNPs) with self-enhanced ECL property. The captured uranyl ion can enhance the ECL signal of PNPs via resonance energy transfer process to give the LOD as 0.5 ng/L, which is much lower than the known luminescent uranyl sensors. Furthermore, ECL imaging technology is introduced into realizing visualized uranyl rapid warning, and can be successfully applied on natural water samples. This study provides a novel strategy for uranyl rapid warning, and shows its potential meaning in public security and environmental fields.
A visualized strategy is developed for accurate and rapid uranium monitoring by using a three-in-one conjugated polymer with self-enhanced electrochemiluminescence behavior, which gives an ultra-low limit of detection (0.5 ng/L) and high selectivity to uranium.
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Violence in public spaces is an aspect of society that demands analysis since this affects social and economic well-being. On setting out to explore the incidence of violence in public areas, this ...paper brings a multi-methodology framework to associate the exploratory analysis of data on street robberies with a geographic information system (GIS) and a multi-criteria decision analysis (MCDA) model. Our GIS-MCDA framework is based on a Dominance-based Rough Set Approach (DRSA) and induces the decision-maker to learn and understand the spatial, social, and demographic data on crime analysis. As a result, the study area was classified into levels of vulnerability. We found that the social interaction features, bus stops and street robberies are spatially and statistically associated. From the socio-demographic perspective, makeshift houses, the number of people who can read and write and the number of inhabitants were highlighted as dimensions to be considered when associated with crime. Finally, preferences in evaluation of areas of vulnerability tend to be pessimistic. Therefore, the multi-methodology framework makes a holistic analysis of such vulnerabilities and contributes to improve knowledge on urban spaces and how this informs detecting vulnerability to crime.
•Data analysis as complementary tool in multi-criteria assessment of urban planning.•Using data analysis to overcome an isolated view point on decision making preferences.•Framework applicable for other spatial issues, considering adaptations.
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