Yue Liu¹, Qinglang Guo², Chunyao Yang¹, Yong Liao^1,*

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2555-2572, 2025, DOI:10.32604/cmc.2025.060318 - 16 April 2025

Abstract Processing police incident data in public security involves complex natural language processing (NLP) tasks, including information extraction. This data contains extensive entity information—such as people, locations, and events—while also involving reasoning tasks like personnel classification, relationship judgment, and implicit inference. Moreover, utilizing models for extracting information from police incident data poses a significant challenge—data scarcity, which limits the effectiveness of traditional rule-based and machine-learning methods. To address these, we propose TIPS. In collaboration with public security experts, we used de-identified police incident data to create templates that enable large language models (LLMs) to populate data More >

Qirui Zhong¹, Xiaogang Cheng^2,*, Yuxin Song³, Han Wang²

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3417-3433, 2024, DOI:10.32604/cmc.2024.049992 - 15 May 2024

Abstract This paper introduces an intelligent computational approach for extracting salient objects from images and estimating their distance information with PTZ (Pan-Tilt-Zoom) cameras. PTZ cameras have found wide applications in numerous public places, serving various purposes such as public security management, natural disaster monitoring, and crisis alarms, particularly with the rapid development of Artificial Intelligence and global infrastructural projects. In this paper, we combine Gauss optical principles with the PTZ camera’s capabilities of horizontal and pitch rotation, as well as optical zoom, to estimate the distance of the object. We present a novel monocular object distance… More >

Xu Zhu¹, Meng Xia¹, Yingzhe Hu¹, Lin Zhang^1,*, Yun Lu², Ying Zhang¹, Xudong Guo¹

International Journal of Mental Health Promotion, Vol.22, No.3, pp. 149-157, 2020, DOI:10.32604/IJMHP.2020.011097 - 14 August 2020

Abstract The purpose of the study was to investigate the mental status and psychological needs of police officers during the COVID-19 outbreak in China. The Anti-Pandemic Public Mental Status Scale and self-administered Psychological Needs Scale were administered online to police officers in Y city, a significant sub-central city of Hubei Province, where was affected by the pandemic the most seriously. A total of 5,467 valid questionnaires were collected, of which female police accounted for 17.7%. Compared with the national public and Y city public data previously measured using the Anti-Pandemic Public Mental Status Scale, this study… More >

Qingyuan Zhou^a, Jianjian Luo^b

Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 133-138, 2018, DOI:10.1080/10798587.2016.1267444

Abstract Big data is an emerging paradigm applied to datasets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time. In a Smarter City, available resources are harnessed safely, sustainably and efficiently to achieve positive, measurable economic and societal outcomes. Most of the challenges of Big Data in Smart Cities are multi-dimensional and can be addressed from different multidisciplinary perspectives. Based on the above considerations, this paper combined the PSR method, the fuzzy logic model and the entropy weight method in an empirical More >