Reliable Evacuation Research Articles

Neuroendoscopic surgery for brainstem hemorrhage: Technical notes and preliminary clinical results

BackgroundBrainstem hemorrhage accounts for a relatively small proportion of spontaneous intracerebral hemorrhages (∼10 %) but tends to occur earlier in life and has poorer prognosis. Numerous studies support the therapeutic potential of minimally invasive hematoma evacuation for intracerebral hemorrhage; however, there have been few assessments of the benefits for brainstem hemorrhage. MethodsWe evaluated the safety and efficacy of a minimally invasive approach under neuroendoscopic guidance with pneumatic arm fixation for removing the hematoma in severe brainstem hemorrhage patients. 14 patients diagnosed with primary brainstem hemorrhage and treated by neuroendoscopy-assisted evacuation at Suzhou Ninth Hospital affiliated to Soochow University were included in the study. Relevant clinical and prognostic date were collected and analyzed. ResultsHematoma volume ranged from 8 to 13 mL according to preoperative CT, while GCS at admission ranged from 4 to 6. The average operative time was 157 min and average intraoperative blood loss was 86 mL. All patients achieved satisfactory hematoma evacuation (over 90 %) according to immediate postoperative CT. Postoperative intensive care unit stay averaged 9.5 days and respiratory support averaged 7.5 days. 11 patients required tracheotomy due to pulmonary infection and absence of pharyngeal reflexes. 9 patients achieved satisfactory functional recovery (GOS score of 4 and 3), while 5 remained in a vegetative state (GOS score of 2). ConclusionNeuroendoscopy provides excellent direct visualization of brainstem hematomas for safe and reliable evacuation. Patients with a new PPH score of 2 or 3 are more likely to benefit from surgical treatment. Large-scale studies are required to identify patients most likely to benefit from this technique.

Dynamic Flow Algorithm with Intermediate Storage for Emergency Evacuation Allowing Lane Reversal based on Incomplete Intuitionistic Fuzzy Preference Relation

Background Evacuation in case of disasters is of the greatest importance because of significant occurrences of natural and artificial disasters worldwide, which is why a reliable evacuation plan is always needed. However, evacuation models are difficult to develop due to various uncertain aspects that need to be considered, multiple and often conflicting criteria for evaluation and as lack of expertise regarding a specific preference of alternatives. Objective This study aims to transport the maximum number of evacuees in a dynamic network with lane reversal by a safe pattern of transportation, i.e., allowing storage at intermediate nodes. The optimal order of shelters and intermediate nodes for a reliable evacuation plan will be defined by incomplete intuitionistic fuzzy preference relation. Methods The illustrated method incorporates multiple and often conflicting criteria into a process of emergency decision-making. When evaluating evacuation alternatives, a decision-maker may hesitate and be unsure which alternative is better or not have sufficient expertise to evaluate a pair of alternatives. To model uncertainty and hesitation, intuitionistic fuzzy values are used to describe alternatives in more detail. This study relies on flow models and graph theory to simulate the movement of evacuees to safe destinations. Furthermore, fuzzy methods and their recent modifications are applied to determine the effective priority order of shelters. A case study which simulates the evacuation of aggrieved to safe destinations is presented. Results A method of evaluating the shelters and intermediate nodes for evacuation based on incomplete intuitionistic fuzzy preference relation is proposed. The method allows the missed values of experts’ assessments to be filled in regarding the evacuation alternatives and deals with intuitionistic fuzzy values, which describe experts’ hesitation. The dynamic character of flow distribution enables transit arc capacities and time factors to be processed. The contraflow technique, which is a powerful tool to decrease traffic jams and congestion on roads by reversing the movement along the unused segments, is applied to maximize the number of survivors. Conclusion The results of the method were compared to those of existing methods, and their consistency was proved. In the future, we intend to apply interval-valued intuitionistic preference relations and iterative algorithms to improve the consistency of intuitionistic preference relations to the tasks of transporting the maximum possible number of aggrieved to safe locations.

Pre-disaster evacuation network design with uncertain demand and behavioural choices: A bi-criteria generalized cost perspective

Pre-disaster evacuation network design is critical to improving evacuation efficiency and reducing the loss of life and property caused by disasters. However, evacuation network design is complicated by the uncertainty of pre-disaster evacuation demand and the heterogeneity of evacuees’ route choices when faced with a disaster scenario. Therefore, how to design efficient evacuation networks considering these uncertainties has become an important research topic. In this paper, we study the pre-disaster flood evacuation network design problem, define a bi-criteria generalized cost metric based on Evacuation Travel Time (ETT) and Evacuation Network Congestion Degree (ENCD), and develop a model that considers uncertain demand and evacuation behavioural choices to minimize the generalized cost in the evacuation network. For the uncertain behavioural choice, we propose an Expanded Stochastic User Equilibrium (ESUE) model based on the Random Regret Minimization (RRM) principle and Boundedly Rational User Equilibrium (BRUE) conditions to describe it. For the uncertain demand, we design a Distributionally Robust Optimization (DRO) method based on Mean Absolute Deviation (MAD) to deal with this uncertain model. This paper designs an Improved Method of Successive Averages Combined with Genetic Algorithm (IMSA-GA) to solve the model and uses the Nguyen-Dupuis test network to verify the applicability and feasibility of the model and algorithm. In addition, we also conduct an evacuation network design in the Hawkesbury-Nepean region of Australia. The larger the threshold value based on the regret utility ratio, the smaller the generalized cost value, which indicates the behavioural choices of the evacuees have an impact on the evacuation network design, and the generalized cost decreases by 6.12% when the threshold value is increased from 0.1 to 0.9. In addition, the generalized cost value obtained by IMSA-GA will be 0.0025 lower than Improved Method of Successive Averages Combined with Simulated Annealing (IMSA-SA) and 0.0005 lower than Improved Method of Successive Averages Combined with Taboo Search (IMSA-TS). The theoretical contribution of this paper is to find an approach to the uncertain evacuation network design problem, especially to improve the practicality of the model by fully considering evacuation behaviour. The practical contribution is that our findings can provide insights for government authorities to design efficient and reliable evacuation networks that balance evacuation travel time and evacuation network congestion. In the future, if evacuation behavioural choices can be analysed based on actual surveys, the estimation of behavioural parameters based on survey data will be more instructive for the evacuation process.

Fast trajectory extraction and pedestrian dynamics analysis using deep neural network

Pedestrian evacuation dynamics research is crucial for safety engineering and crowd management. Accurate and fast extraction of pedestrian trajectories from experimental videos is essential for reliable evacuation data and effective strategy development. In this paper, we propose a novel method for extracting pedestrian trajectories from evacuation experiment videos based on deep learning techniques. The method consists of two modules: pedestrian detection and location prediction, which use Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks, respectively. Experimental results show that our method achieves high accuracy with short time compared to traditional methods. Furthermore, our experiments demonstrate that our method can accurately extract information on pedestrian evacuation dynamics. The proposed method provides a fast and reliable approach to extracting pedestrian evacuation dynamics information, which has the potential to be utilized by researchers, urban planners, and emergency management personnel to develop more effective evacuation strategies, improve crowd management, and ultimately enhance public safety.

A pre-evacuation study using data from evacuation drills and false alarm evacuations in a university library

Performance-based fire design can be carried out by comparing results from fire simulations and evacuation simulations. Simulating evacuation of buildings requires engineers to have access to several sets of evacuation data, including occupant travel speeds, flow rates, and pre-evacuation time. Especially in building types where people may take longer before beginning travel to the exits, pre-evacuation behaviours and times are among the most important data required for reliable evacuation simulation output.This work provides new pre-evacuation data collected in four evacuations of the same university library. Two of these evacuations were pre-planned (unannounced) drills, while the other two were unplanned evacuations due to false alarms. In this study, the pre-evacuation behaviour and times of 497 students were analysed using the CCTV videos of these four evacuations. The results illustrate that un-planned evacuations had higher pre-evacuation times. Further, the data analysis shows that the type of evacuation (pre-vs unplanned), the performance of certain actions (e.g., collecting items), evacuating in groups, and evacuees' location explain 29% of the variance of the observed pre-evacuation times.

Intelligent robot-assisted evacuation: A review

Mass gathering in places such as shopping mall, concerts, sport events etc. is a necessity but may pose threat to the occupants during emergency. This paper presents a review of the different approaches of the crowd evacuation problems which can be classified into classical and modern methods. The classical methods have been widely used which basically depends on prior evacuation warnings or human in assisting an emergent evacuation scenario. Nonetheless, with the lack of important information such as the location of the safest exit, the consequence can be catastrophic. As a result, classical evacuation method becomes tough even though many people might able to assist the evacuees during such situation. Overcoming this, researchers have developed intelligent robots-assisted evacuation systems as a modern approach to manage crowds more systematically and simultaneously during emergency, which will be reviewed in this paper. Finally, this review paper aims to give a broad scope of the reliable evacuation system management to ensure the safety of the evacuees during emergency evacuation.

Capacitated Refuge Assignment for Speedy and Reliable Evacuation

When a large-scale disaster occurs, each evacuee should move to an appropriate refuge in a speedy and safe manner. Most of the existing studies on the refuge assignment consider the speediness of evacuation and refuge capacity while the safety of evacuation is not taken into account. In this paper, we propose a refuge assignment scheme that considers both the speediness and safety of evacuation under the refuge capacity constraint. We first formulate the refuge assignment problem as a two-step integer linear program (ILP). Since the two-step ILP requires route candidates between evacuees and their possible refuges, we further propose a speedy and reliable route selection scheme as an extension of the existing route selection scheme. Through numerical results using the actual data of Arako district of Nagoya city in Japan, we show that the proposed scheme can improve the average route reliability among evacuees by 13.6% while suppressing the increase of the average route length among evacuees by 7.3%, compared with the distance-based route selection and refuge assignment. In addition, we also reveal that the current refuge capacity is not enough to support speedy and reliable evacuation for the residents.

The Variation of Pre-movement Time in Building Evacuation

In order to provide a reliable evacuation design assessment, data showing the variation in pre-movement time is of vital importance. The pre-movement time is in many cases regarded as the main time period during an evacuation assessment. Therefore, forty unannounced evacuation experiments for six different occupancies were analysed to quantify pre-movement time during building evacuation, i.e., the time taken between receiving the first cue and initiation of movement towards an exit during evacuation. The occupancies were office, cinema theatres, restaurants, department stores and night clubs. The occupancies were equipped with different types of evacuation alarm systems. The study resulted in 2486 data points for the pre-movement time. The pre-movement times were matched to statistical distributions to describe the variation. It was found that the pre-movement times in most cases could be represented with a lognormal or loglogistic distribution typically having a rapid initial increase representing the phase when people start reacting, which is followed by a less steep decrease representing the phase when some people linger before evacuating. Most reliable data are provided for the cinema theatre experiments which included 1954 data points from 30 experiments. The paper also presents a structure for performing an assessment of video recorded evacuation experiment determining actions, relevant time data and fitting a statistical distribution to the data. The new information provided in the paper can help fire safety professionals to more accurately predict the time to evacuate different premises.

A robust chance constraint programming approach for evacuation planning under uncertain demand distribution

This study focuses on an evacuation planning problem where the number of actual evacuees (demand) is unknown at the planning phase. In the context of mass evacuation, we assume that only partial information about the demand distribution (i.e., moment, support, or symmetry) is known as opposed to the exact distribution in a stochastic environment. To address this issue, robust approximations of chance-constrained problems are explored to model traffic demand uncertainty in evacuation networks. Specifically, a distributionally robust chance-constrained model is proposed to ensure a reliable evacuation plan (start time, path selection, and flow assignment) in which the vehicle demand constraints are satisfied for any probability distribution consistent with the known properties of the underlying unknown evacuation demand. Using a path-based model, the minimum clearance time is found for the evacuation problem under partial information of the random demand. Numerical experiments show that the proposed approach works well in terms of solution feasibility and robustness as compared to the solution provided by a chance constrained programming model under the assumption that the demand distribution follows a known probability distribution.

Geographical risk analysis based path selection for automatic, speedy, and reliable evacuation guiding using evacuees’ mobile devices

It has been highly expected to achieve speedy and reliable evacuation guiding under large scale disasters. As for the speedy evacuation, an automatic evacuation guiding scheme has been proposed, which is a reactive approach based on implicit interactions among evacuees, their mobile devices, and networks. In this scheme, an evacuation route is given by the shortest path, which may not be safe. In this paper, we propose a speedy and reliable path selection based on the geographical risk map for the existing automatic evacuation guiding, which is a proactive approach that allows evacuees to evacuate speedily while avoiding encounters with blocked road segments as much as possible. First, the proposed scheme enumerates candidates of short paths from the evacuee’s current location to the refuge. Then, it selects the most reliable one from the candidates by taking into account road blockage probabilities, each of which is an estimated probability that the corresponding road is blocked under a certain disaster. Through simulation experiments, we show that the proposed scheme can improve the safety of evacuation in terms of the number of encounters with blocked road segments while keeping both the average and maximum evacuation times unchanged, compared with the shortest path selection. We further demonstrate how the proactive function, i.e., geographical risk analysis, and the reactive function, i.e., information sharing, contribute to the system performance.

Sharp probability inequalities for reliable evacuation planning

This paper contributes to the literature by providing new techniques to determine optimal evacuation routes when limited information is known about the evacuation demand and road capacities. Specifically, this research complements prior work by requiring only their first and second moments to be known. The inclusion of an optional symmetry assumption is rigorously shown to further reduce the evacuation time. Finally, we demonstrate that the probability inequalities that serve to ensure the confidence level of the evacuation plan are sharp. A case study illustrates the core idea of demand inflation and supply deflation in obtaining reliable evacuation plans.

The Investigation of Launching Parameters on the Motion Pattern of Freefall Lifeboat Using FSI Analysis

The freefall lifeboats have been designed to be fast and reliable evacuation system. Once the occupants have gone onboard, the lifeboat is simply sliding from a skid before the freefall. Some second after the water impact, the propulsion system can be started and the lifeboat can sail away from parent vessel. During the launching process, trajectories of freefall lifeboats can be divided into such categories, depending on the headway and advance speed after water entry and surfacing of the lifeboats. The aim of the paper is investigating the influence of the launching parameters such as, sliding distance, angle of skid and the falling height on the motion pattern of the freefall lifeboats by using Fluid Structure Interaction (FSI) analysis. The fluid structure interaction analysis is simulated using penalty coupling algorithm. The fluid is treated on a fixed mesh using a Single Material Arbitrary Lagrangian Eulerian formulation and the lifeboat structure on a rigid shell element mesh using a Lagrangian formulation. The results of the numerical simulations provide the magnitude of launching parameters for safely launching of the freefall lifeboat.

Bites, stings, and rigors: clinical considerations in African operations.

The natural health threats in Africa pose daunting clinical challenges for any provider, as evidenced by the current Ebola epidemic in West Africa, but the threat is multiplied for the Special Operations provider on the continent who faces these challenges with limited resources and the tyranny of distance. The majority of operationally significant health risks can be mitigated by strict adherence to a comprehensive force health protection plan. The simplest, yet most effective, technique for preventing mosquito-borne diseases is the prevention of mosquito bites with repellent, bed nets, and appropriate clothing in addition to chemoprophylaxis. Some of the more likely or lethal infectious diseases encountered on the continent include malaria, Chikungunya, dengue, human immunodeficiency virus, and Ebola. Venomous snakes pose a particular challenge since the treatment can be as deadly as the injury. Providers supporting African operations should educate themselves on the clinical characteristics of possible envenomations in their area while promoting snake avoidance as the primary mitigation measure. To succeed in Africa, the Special Operations provider must consider how to meet these challenges in an environment where there may not be reliable evacuation, hospitalization, or logistics channels.

성능위주 피난안전설계를 위한 한국인 대상 유출계수 측정 실험

최근 건축물이 고층 복합화 됨에 따라 화재발생 시 많은 인적피해발생의 우려가 높아지고 있다. 이에 선진국에서는 건축물 특성에 따라 성능기반 피난안전설계를 실시하고 있는데, 이를 위해서는 해당 건축물 및 이용하는 재실자의특성을 파악할 필요가 있다. 특히 유출계수는 피난에 필요한 시간을 결정에 하는데 중요한 피난요소로서 국외의 경우에는 축적된 화재사고 경험과 다양한 실험분석을 통해 유출계수 기준 및 절차를 제시하고 있지만 국내에는 최근에야 성능기반 소방설계가 도입되어 국내피난상황을 고려한 연구 및 기준이 미흡한 상태이다. 또한 국외기준을 그대로 적용하기에는 국내 재실자의 피난특성(피난행동, 신체적 크기, 사회문화적 상황)이 달라 신뢰성 있는 피난용량을 확보하기에는 한계가 있다. 이에 보다 안전하고 효율적인 국내 건축물 피난안전성 확보를 위해서는 국내 재실자의 피난특성을 고려한 실험과 관련연구가 선행되어야 할 것이다. 따라서 본 연구에서는 국내 건축물 피난안전설계 확립을 위하여 피난요소 중 유출계수에 대해 실험세트를 제작해 국내 연령별 유출계수 실험을 실시하였다. 이러한 유출계수실험은 향후 성능기반 피난안전설계분야의 유출계수 정립에 기초자료로 활용될 것으로 판단된다. In recent times, high rise and complex buildings have raised concerns about fire damage. In most developed countries, the performance basis evacuation safety design is established by the characteristics of the buildings and their' occupants. Especially, the run-off coefficient is the major evacuate factor in determining the time required in case of fire and, the foreign countries suggest the standard and the process of the run-off coefficient through accumulated fire accident experiences and experimental analysis. However, performance based fire protection design is recently introduced to domestic and, the studies and standards inthe emergency situation are insufficient. In addition, it is limited to secure the reliable evacuation capacity when applying the international standards due to the different evacuation characteristics of the domestic occupants (escape behavior, physical size and socio-cultural situation). Precedent studies on the domestic occupants' evacuation characteristics are required to secure the safer and more efficient domestic buildings evacuation safety. Therefore, in this study, the experiment set was builtto obtain the run off coefficients in the evacuation elements to establish the domestic building evacuation safety design and run-off coefficient experiments with the domestic age-categorized groups were conducted. These experiment scan be used as a basis for establishing the run-off coefficients of performance evacuation safety design in future.

Reliable evacuation planning via demand inflation and supply deflation

This paper presents an evacuation route planning model that both accounts for demand uncertainty (i.e. the number of evacuees) as well as capacity uncertainty (i.e. the road capacities). To ensure reliability, the model plans for more evacuees (i.e. demand inflation) and less road capacity (i.e. supply deflation). A major contribution is that we provide a framework to determine the amount of demand inflation/supply deflation necessary to ensure a user-specified reliability level. The model is shown to be a natural generalization of previously proposed evacuation models. A small numerical case study reveals the key characteristics of the model.

A spatio‐temporal population model to support risk assessment and damage analysis for decision‐making

The aim of this research is to develop and implement a simple spatio‐temporal model of population location that might improve risk assessment and damage analysis for decision‐making in both the Finnish Fire and Rescue Services and the Finnish Defence Forces. The motivation for the research is that present risk models do not take into account the temporal variation in population location during different times of the day. We use spatio‐temporal modelling methods to model the population dynamics, and visualization techniques to represent the model outcomes. In addition, we apply the developed model to a damage‐analysis application. The case study site is located in the centre of Helsinki. The model uses a basic population and workplace dataset maintained by the Helsinki Metropolitan Area Council. By means of this model, we intend to advance risk assessment, which considers the consequences of accidents. This model has the potential to help decision‐makers evaluate their plans in several application areas—such as achieving better preparedness by having more reliable evacuation plans and resource allocation. In addition to the application‐related technological research, a more generic framework about decision‐making supported by spatio‐temporal knowledge and visualization is presented.

The button cecostomy for management of fecal incontinence.

The antegrade continence enema (ACE), administered through a continent cutaneous appendicocecostomy, has been used to successfully achieve reliable evacuation and fecal continence in patients with myelomeningocele. However, as originally described, it is not suitable in patients without an appendix or those requiring urologic reconstruction with appendix. We report the use of a standard gastrostomy button in the cecum to create a continent cecostomy in five patients with fecal incontinence. Four underwent simultaneous urologic reconstruction, including two artificial urinary sphincter (AUS) implantations. At a mean of 28 months' follow-up, all five patients are continent of stool. One ACE button has been converted to an ileal Malone cecostomy at the patient's request. Complications included one appendiceal phlegmon requiring exploration and three superficial wound infections, one at a cecostomy site, responsive to antibiotics and local care. There were no AUS infections. The button cecostomy is an effective alternative to standard ACE procedures. It is particularly useful in those who require creation of an appendicovesicostomy for attainment of urinary continence.