Analyzing floor-stair merging flow based on experiments and simulation

In most situations,staircase is the only egress to evacuate from high-rise buildings.The merging flow on the stair landing has a great influence on the evacuation efficiency.In this paper,we develop an improved cellular automaton model to describe the merging behavior,and the model is validated by a series of real experiments.It is found that the flow rate of simulation results is similar to the drills,which means that the improved model is reasonable and can be used to describe the merging behavior on stairs.Furthermore,some scenarios with different door locations and building floor numbers are simulated by the model.The results show that(i)the best door location is next to the upward staircase;(ii)the total evacuation time and the building floor number are linearly related to each other;(iii)the pedestrians on upper floors have a negative influence on the evacuation flow rate.

An Error-Correcting Code-Based Robust Watermarking Scheme for Stereolithographic Files

Stereolithographic(STL)files have been extensively used in rapid prototyping industries as well as many other fields as watermarking algorithms to secure intellectual property and protect three-dimensional models from theft.However,to the best of our knowledge,few studies have looked at how watermarking can resist attacks that involve vertex-reordering.Here,we present a lossless and robust watermarking scheme for STL files to protect against vertexreordering attacks.Specifically,we designed a novel error-correcting code(ECC)that can correct the error of any one-bit in a bitstream by inserting several check digits.In addition,ECC is designed to make use of redundant information according to the characteristics of STL files,which introduces further robustness for defense against attacks.No modifications are made to the geometric information of the three-dimensional model,which respects the requirements of a highprecision model.The experimental results show that the proposed watermarking scheme can survive numerous kinds of attack,including rotation,scaling and translation(RST),facet reordering,and vertex-reordering attacks.

Experiment and simulation study of emergency evacuation during violent attack in classrooms

In recent years,as a disaster,terrorist attacks have occurred throughout the world.However,emergency evac-uation behaviors during these incidents were not clear,and the traditional emergency plans were not suitable for such incidents.In this paper,evacuation behaviors under armed assault attack in a classroom were studied based on evacuation experiments.A total of 103 participants took part in three experiments.In each experiment,the attacker’s attacking route was set differently to study the impact of the attacking route on evacuation be-haviors.Pre-evacuation delay,panic of the evacuees,exit choices,evacuation time,and evacuees’trajectories in the experiments were all analyzed.The results of the experiments showed that when a terrorist attack occurs,there is a long delay before evacuation,and most of the evacuees were in the state of“observation”before they moved.When one of the participants started to evacuate or shout,other participants would begin to recognize the danger and escape quickly.These three experiments showed that the route of the attacker had a significant impact on the routes and exit choices of the evacuees.Rather than searching for the nearest exit,the primary purpose of evacuees was to keep a safe distance from the attacker.The average speed of the evacuees in these three experiments was 1.07 m/s,0.81 m/s,and 0.84 m/s,respectively.The density distribution during the crowd evacuation process was uneven,with the highest density occurring at the area from the seats to the aisles.The research can provide data support for the design of emergency plans and the computer simulation of the armed assault attack.

Microwave-assisted in situ synthesis of fluorescent gold nanoclusters with BSA/montmorillonite and application on latent fingermark imaging

A method for in situ preparation of fluorescent gold nanoclusters(Au NCs) with bovine serum albumin/montmorillonite composite powder(Au NC-BSA/MMT) was developed, and the products were used to detect latent fingermarks. In this work, Au NCs were "grown" both inside and on the surface of BSA/MMT clay using one-step reduction of HAu Cl4 by BSA. The as-prepared Au NC-BSA/MMT nanocomposites emit intensive red fluorescence under the excitation of UV-visible light and show stable chemical features and low toxicity. The obtained fluorescent powders were characterized by UV-visible absorption spectroscopy,fluorescence spectroscopy, infrared spectroscopy, transmission electron microscopy/high-resolution transmission electron microscopy, scanning electron microscopy, X-ray photoelectron spectroscopy and X-ray diffraction to depict their sizes, structural information and optical features. Given their environmentally friendly preparation, simple operation, low cost, efficient UVvisible radiation-dependent photoluminescence and good affinity with finger residues, the in situ synthesized Au NC-BSA/MMT nanocomposite powders were used as an alternative fluorescent developing reagent for developing latent fingermarks deposited on various object surfaces(such as glass, aluminum foil, painted metal, plastic products and weighing papers) for individual identification. As results, the developed fingermarks with clear patterns and satisfactory level-2(minutiae points) and level-3(sweat pores) ridge details were obtained. Notably, treated prints could be excited by red light and emitted near infrared fluorescence, which was beneficial to avoid background interference and reduce the damage caused by UV light. With the advantages of the simple preparation process and good enhancement performance for latent fingermarks, the proposed method might be used in the preparation of various fluorescent probes for detecting trace evidence in forensic sciences.

Intermediate symmetric construction of transformation between anyon and Gentile statistics

Gentile statistics describes fractional statistical systems in the occupation number representation.Anyon statistics researches those systems in the winding number representation.Both of them are intermediate statistics between Bose–Einstein and Fermi–Dirac statistics.The second quantization of Gentile statistics shows a lot of advantages.According to the symmetry requirement of the wave function and the property of braiding,we give the general construction of transformation between anyon and Gentile statistics.In other words,we introduce the second quantization form of anyons in an easier way.This construction is a correspondence between two fractional statistics and gives a new description of anyon.Basic relations of second quantization operators,the coherent state and Berry phase are also discussed.

Padéapproximant approach to singular properties of quantum gases:the ideal cases

In this paper,we show how to recover the low-temperature and high-density information of ideal quantum gases from the high-temperature and low-density approximation by the Padéapproximant.The virial expansion is a high-temperature and low-density expansion and in practice,often,only the first several virial coefficients can be obtained.For Bose gases,we determine the BEC phase transition from a truncated virial expansion.For Fermi gases,we recover the low-temperature and high-density result from the virial expansion.

Multimodal Biometric Fusion Algorithm Based on Ranking Partition Collision Theory

Score-based multimodal biometric fusion has been shown to be successful in addressing the problem of unimodal techniques’vulnerability to attack and poor performance in low-quality data.However,difficulties still exist in how to unify the meaning of heterogeneous scores more effectively.Aside from the matching scores themselves,the importance of the ranking information they include has been undervalued in previous studies.This study concentrates on matching scores and their ranking information and suggests the ranking partition collision(RPC)theory from the standpoint of the worth of scores.To meet both forensic and judicial needs,this paper proposes a method that employs a neural network to fuse biometrics at the score level.In addition,this paper constructs a virtual homologous dataset and conducts experiments on it.Experimental results demonstrate that the proposed method achieves an accuracy of 100%in both mAP and Rank1.To show the efficiency of the proposed method in practical applications,this work carries out more experiments utilizing real-world data.The results show that the proposed approach maintains a Rank1 accuracy of 99.2%on the million-scale database.It offers a novel approach to fusion at the score level.

Forensic Automatic Speaker Recognition Based on Likelihood Ratio Using Acoustic-phonetic Features Measured Automatically

Forensic speaker recognition is experiencing a remarkable paradigm shift in terms of the evaluation framework and presentation of voice evidence.This paper proposes a new method of forensic automatic speaker recognition using the likelihood ratio framework to quantify the strength of voice evidence.The proposed method uses a reference database to calculate the within-and between-speaker variability.Some acoustic-phonetic features are extracted automatically using the software VbiceSauce.The effectiveness of the approach was tested using two Mandarin databases:A mobile telephone database and a landline database.The experimenfs results indicate that these acoustic-phonetic features do have some discriminating potential and are worth trying in discrimination.The automatic acoustic-phonetic features have acceptable discriminative performance and can provide more reliable results in evidence analysis when fused with other kind of voice features.