Panic Situation Research Articles

Creation of a Spatiotemporal Algorithm and Application to COVID-19 Data

This study offers an in-depth analysis of the COVID-19 pandemic’s trajectory in several member countries of the European Union (EU) in order to assess similarities in their crisis experiences. We also examine data from the United States to facilitate a larger comparison across continents. We introduce our new approach, which uses a spatiotemporal algorithm to identify five distinct and recurring phases that each country underwent at different times during the COVID-19 pandemic. These stages include: Comfort Period, characterized by minimal COVID-19 activity and limited impacts; Preventive Situation, demonstrating the implementation of proactive measures, with relatively low numbers of cases, deaths, and Intensive Care Unit (ICU) admissions; Worrying Situation, is defined by high levels of concern and preparation as deaths and cases begin to rise and reach substantial levels; Panic Situation, marked by a high number of deaths relative to the number of cases and a rise in ICU admissions, denoting a critical and alarming period of the pandemic; and finally, Epidemic Control Situation, distinguished by limited numbers of COVID-19 deaths despite a high number of new cases. By examining these phases, we identify the various waves of the pandemic, indicating periods where the health crisis had a significant impact. This comparative analysis highlights the time lags between countries as they transitioned through these different critical stages and navigated the waves of the COVID-19 pandemic.

Evacuation scenario optimization in buildings with human anthropometric characteristics

Emergency evacuations are critical situations that threaten people's lives and safety, necessitating robust planning and prevention strategies. Anthropometric data, which are numerical expressions of human body measurements, play a vital role in architectural design by helping determine safe evacuation routes. This data is crucial for understanding the physical characteristics and mobility of building occupants, allowing for optimized evacuation routes that accommodate the needs of various groups, such as the elderly, children, and individuals with physical disabilities. The Social Forces Model (SFM) is an important tool used to understand the behavior and movement of crowds, modeling these aspects mathematically by considering social interactions and environmental factors. This study develops a system to enhance emergency evacuation scenarios in buildings using anthropometric data and SFM. This system analyzes the evacuation process and identifies optimal routes, contributing significantly to ensuring safety and minimizing damage during disasters. The research shows that using anthropometric data and SFM in architectural design is essential for effective emergency evacuation planning and management. Simulations that incorporate the diverse physical characteristics of people demonstrate notable improvements in evacuation times compared to those using fixed values, with up to 10.20 % improvement in single-exit scenarios and up to 13.45 % in two-exit scenarios. Furthermore, evacuation routes are optimized using SFM, and histograms are employed to identify the most preferred routes during panic situations. This data-driven approach informs the design of building and floor layouts, as well as the materials and decorations used, ensuring that evacuation routes remain clear and accessible. Removing obstacles and facilitating easy passage during emergencies significantly enhances the effectiveness of evacuations. Overall, the integration of anthropometric data and SFM in building design is shown to create faster and safer evacuation processes, ultimately improving emergency response and safety.

Review on Panic Buying Behavior during Pandemics: Influencing Factors, Stockpiling, and Intervention Strategies.

Panic buying poses significant challenges for individuals and societies. This paper provides a literature review on the process by which a pandemic crisis evolves into panic buying behavior. The review offers a comprehensive perspective on studies related to panic buying and mitigation efforts, categorizing them based on their contributions in three stages: factors influencing panic buying, the process of transforming panic into increased demand and stockpiling, and applicable intervention strategies to mitigate panic situations. The paper introduces the Socio-Economic Framework of Panic (SEFP) to illustrate the interaction between demand and supply during a panic. The review identifies a lack of quantitative models explicitly correlating influencing factors with panic and estimating panic demand. Additionally, it reveals that suggested intervention strategies often lack practical implementation guidelines. Using the SEFP, the importance of considering interventions at various stages is highlighted, ranging from controlling influencing factors and panic demands to overseeing stockpiling and supply-related activities. The paper also identifies research gaps in both qualitative and quantitative modeling, policymaking, and governance.

An overview on important ethnomedicinal plants of Rajasthan with their antimicrobial properties

In era of synthesized drugs, where individuals totally depend upon the chemical formulations of medication that may have adverse effects, people should re-establish their bond with nature. The gradual increase in multidrug resistance (MDR) and antimicrobial resistance (AMR) of pathogens is a great concern of worry to the world and obviously for this purpose, novel and effective bioactive constituents from the plants should be explored to get rid of this panic situation. Researchers are searching for the favourable natural source to fight with various antimicrobial diseases. Present study deals with the importance of precious herbs and plants from the treasure of nature and also listed some important ethnomedicinal plants with their bioactive ingredients from the region of Rajasthan.

Design and Analysis of an Intelligent Fire Detection System For Cargo Compartment of Aircraft

The fire detection system and fire warning are design features of an aircraft. The fire detection system protects the aircraft and passengers in case of actual fire during flight. But spurious fire warning during flight creates a panic situation in flight crews and passengers. The conventional fire alarm system of an aircraft is triggered by false signal. The artificial neural network has capability of fault tolerance and robust in nature. Its performance is dependent on its training, which is done on the real time data collected from the aircraft. Neural network based fire detection system provides real time surveillance, monitoring and automatic alarm. An intelligent fire detection system is developed based on artificial neural network in MATLAB using three inputs such as temperature, smoke density and CO concentration. This information helps in determining the probability of three representative of fire condition which is Fire, smoke and No fire. The simulated test results show that the identification error rates are very less. This greatly reduces leak check rates and false alarms. The neural network based fire detection system uses a variety of sensor data and improves the ability of system to adapt and accurately predict fires. It sends early alarm when the fire/smoke occurs and helps to reduce the spurious fire warning.

Impact of Personality Traits on the Academic Achievement of Students at the College Level

This research aims to determine the impact of personality traits on the academic performance of students at the college level. Research questions and research objectives lead the study. Objectives were; to enumerate the different personality traits that college students display which the five-component model theory explains, to evaluate the connection between a student’s personality characteristics and academic success, to analyze many personality traits that affect students’ academic success, and to make suggestions for how to solve the issue so that more studies may be done. The survey research design was used to accomplish the objectives. The study focused on undergraduate students from Government colleges of District Rahim Yar Khan. 400 ADP students were chosen from a target population of 7 Government colleges (girls & boys) in Sadiqabad, Khanpur, and Rahim Yar Khan by using the simple random technique. A five-point Likert scale i.e. SD, D, UD, A, SA self-structured questionnaire was used to collect data from the participants. The collected data were analyzed by using SPSS software with descriptive statistics (percentage, mean, and standard deviation). On the basis of the conclusion, there is a significant relationship between panic situation and personality; task handling and efficiency; skills and social situation with a positive correlation at α=0.05

Airport evacuation under panic conditions: a microsimulation modeling applied at Ottawa International Airport

This study develops a framework of pedestrian evacuation microsimulation modeling that considers pedestrians’ social-physiological behavior in assessing an airport evacuation. The study implements social force model within a simulation platform enabling the articulation of stochastic pedestrian walking behavior realistically and reliably. It performs a sensitivity analysis of pedestrian behavior parameters to identify the candidate parameters required to capture pedestrian behavior under different levels of panic conditions. The study considers the case study of the Ottawa International Airport and tests and evaluates contrasting evacuation scenarios under low panic, medium panic, and high panic situations. Results indicate that under the low panic evacuation scenario, the pedestrians yield their movements with an increase in network bottleneck, potentially exhibit cooperative behavior, and control their speed with the rise of crowd density. On the contrary, individuals in high panic evacuation scenarios exhibit aggressive behavior indicated by their average speed, which is approximately 1.15 and 3.5 times the average compared with medium panic and low panic evacuation scenarios, respectively. Results suggest that it takes 5.38 min to evacuate 1300 passengers under high panic conditions compared with 9.75 min for a low panic evacuation scenario. However, in the case of a high panic evacuation scenario, the average speed keeps increasing even with the increase in crowd density. This framework can develop and evaluate strategies for safely evacuating the airport in the case of an emergency.

Immediacy and Journalistic Authority For Reporting Environmental Disasters: Case Study Of 2022 Floods Of Pakistan

Real-time journalism is informing the public about the pace of the event that is happening. The story changes as time passes. It is playing with the nerves of the people as at that time the media is the only source of information and people are compelled to believe it. In the case of flood reporting and the reporting of the flood-affected areas makes the people of that area attentive and ready to take action upon the instructions of the media. In such a situation, as and when any single news channel tries to break the news of any emergency. Panic has been created in the target area and the people of that particular area try to escape from that area because they don’t know the volume of water coming in in such a situation many lives have expired due to the panic situation. The more dangerous is that the other news channels also follow the first line and start exaggerating the activity of that area and this becomes more dangerous because the people of target areas get frightened, and this makes their lives miserable. For this research, we have selected five Pakistani news channels during the 2022 flood in Pakistan. We will analyze the one-month highly flood season news reporting of these channels i.e. July 16 to August 15, 2022, how much news they break, and whether there was a need to flash that news as breaking news.

Kontroversi Hacker Bjorka: Analisis Isi Kuantitatif Strategi Pemulihan Citra

Cyber Crime in Indonesia in 2022 had a significant increase. One of the cybercrimes was the Bjorka Hacker case. The background of this research is a cybercrime incident committed by Hacker Bjorka against the information security system of the Indonesian government. Hacker Bjorka claimed to have personal data and information of individuals as well as several national organizations. It creates a panic situation among the public. The alleged leak of information makes the Ministry of Communication and Information Technology in the spotlight to be responsible for responding to that crisis situation. Finally, the response of Kominfo becomes very important in this controversy. In order to describe the Kominfo strategy, this research uses quantitative descriptive methods. The population is the statements from Kominfo in response to the Bjorka controversy, that are published in the online media kompas.com in September 2022. The sample is taken by using a purposive sampling method. The results showed that the statements made by Kominfo published by kompas.com were proven to use several strategies for image improvement. The strategies used by Kominfo are denial, corrective action, defeasibility, and minimization. The strategy that is not used is mortification or apologizing.

TURBULENCE IN DISGUISE IN THE BANKING SECTOR CREATE PANIC WITHDRAWAL OF MONEY IN BANGLADESH

Bankers may find it difficult to get deposits from households as a result of financial market turmoil. Negative returns on bank assets cause creditors to worry about financial stability, causing them to exaggerate the possibility of a bank failure in the future and withdraw money from banks in a panic. This article provides a simplified alternative for building beliefs about panic withdrawal. By lowering asset prices and raising the cost of bank borrowing, banks’ balance sheet positions deteriorated, which caused worries for the depositors, who became panicked. This article discusses potential bank panic scenarios in Bangladesh due to several internal causes that vary countercyclically. Although the major issue confronting the banks was not illiquidity but rather insolvency due to a high percentage of nonperforming loans, bank supervisory authorities may respond to this panic situation by offering liquidity support, government policy intervention, ensuring good governance, limiting the number of withdrawals, and so on.

Panic buying in the second wave of COVID-19: the moderating effect of past buying experience

PurposeWith the advent of the second wave of COVID-19 pandemic, there is a need to analyse the scenario of panic buying (PB) behaviour of the customers which was evident in the first wave. This paper aims to examine the PB scenario as well as the moderating effect of past buying experience (PBE) on PB in the second wave of the COVID-19 pandemic.Design/methodology/approachThis study is based on the theories of stimulus–organism–response model and the competitive arousal model. Based on these theories, this paper investigates how panic situation created by external stimuli such as perceived scarcity (PS), perceived risk (PR), news in media (NM) and social learning affect the perceived arousal (PA) among people which in turn influence the PB behaviour of customers. Data were collected from 253 customers from different parts of India. Structural equation modelling is used to analyse the moderating effect of PBE on the PB in the second wave of COVID-19 pandemic.FindingsThe results indicate that the PS, PR and NM continue to be strong predictors of a buyer for PA. However, the PB is not reinforced by the moderation effect of PBE.Research limitations/implicationsThis paper investigates the consumers’ PB behaviours in the wake of third wave of COVID-19 pandemic which add to the existing literature of COVID-19 pandemic. Moreover, this study also examines how previous buying experience can moderate the PB behaviour of the customers in subsequent phases of COVID-19 pandemic. This supports the potential effectiveness of self-regulation as an intervention strategy for reducing PB behaviours during the COVID-19 pandemic.Practical implicationsThis study emphasises the impact of external stimuli like PS, PR and media coverage on PB behaviour, marketers and policymakers should manage to avoid triggers. Although PBE may not moderate PB during a pandemic, it can play a significant role in future buying behaviour. Anticipating potential triggers and designing effective marketing strategies that cater to customers' needs can help manage PB behaviour during disasters or pandemics. In addition, promoting conscious consumption awareness and self-regulation practices among customers can help manage PB behaviour, benefit the environment and society and make customers more responsible buyers.Originality/valueTo the best of the authors’ knowledge, this study examines the PB behaviour of customers during the second wave of COVID-19 pandemic for the first time. This study also investigates the moderating effect of PBE on the PB behaviour of customers during a pandemic which is new and significant that extends the literature on PB behaviour during a pandemic.

IoT Based Military Task Force Health Parameters and GPS Position Tracking System using Raspberry PI

In this project we present an Internet of Things based Soldier Health Status Detection and Location Tracking System using Internet of Things for the safety purpose of the soldier. The soldier is the critical unit of the nation and their life is valuable. Lot of soldiers are facing many problems such as communication with the control room and no proper medical help at a proper time which leads to the death of the soldier. To minimize such cases, we have proposed a continuous alert system to track location and monitor the health of the soldier. The proposed system is very useful in detecting location of the soldier in real time using GPS and communicating the health status parameter continuously using GSM module embedded in microcontroller. The tiny sensors can be fixed to the Soldier body or dress of the soldier to detect body parameter and transmit the information to the control room and other solider when there is a low body rate or when it falls than the defined threshold value. The soldier can send an alert message to the guardian and control room for the help in the panic situation using an application. The control room/guardian also uses android application to request the location of the solider automatically in the panic situation. The soldier can also request for the nearest hospital information in the emergency.

How Covid-19 literacy influences fear, protective behaviour, and conspiracy beliefs among university students in Pakistan?

BackgroundCovid-19 literacy, a social vaccine, is crucial to cope pandemic situations as it helps individuals to manage panic situations, adopt health preventive behaviours and adapting to the new normal. ObjectivesThis research examined the effects of Covid-19 literacy on fear, protective behaviour, and conspiracy beliefs of university students using an online questionnaire. MethodsA cross-sectional survey was conducted at two universities from Lahore with permission from concerned authorities. A total of 301 received responses were analyzed by applying descriptive as well as inferential statistics in SPSS. ResultsThe results indicated that Covid-19 literacy appeared to predict negatively fear of Covid-19 and conspiracy beliefs and positively health-protective behaviours. In other words, the university students with better Covid-19 literacy appeared to have less fear of Covid-19, more likely to adopt health-protective behaviours and believe less in conspirative information. ConclusionsThese results demonstrated the potential benefits of Covid-19 literacy to respond proactively to the fear caused by the Covid-19 pandemic, managing infodemic and adoption of health-protective behaviours. These results would be useful for policymakers, NGOs, health professionals, and university librarians in planning health education and promotion for not only university students but also for general public. This research contributed to the existing research on health literacy related to the Covid-19 pandemic in general and Covid-19 literacy in particular as limited studies have been published so far.

Recent Events Of Invasive And Migratory Pests And Lessons Learnt

In the increasing globalisation era, movement of goods and planting materials between countries being carried out at ease, are potential factors of introduction of invasive alien insects, diseases, and weeds in India. Infested fruits carried by international travellers, cargo / sea shipments of wood logs, food trade, and accidental introduction through air travels were the potential ways of entry of invasive alien insects into any country. The entry of alien invasive pest causes huge economic damage by way of direct crop loss. In addition, the panic situation to save the crops results in indiscriminate use of chemical insecticides that is harmful to applicator, farmer and consumer. Frequent application of insecticides leads to reduction in natural enemies and pollinators there by having an adverse impact on the ecosystem. The present paper critically reviewes the existing plant quarantine regulations in India, recent invasive and migratory insect pest problems and way forwards to safeguard Indian Agriculture.

Accident Prevention Mechanism In Vehicles

The road accidents are recently increasing at a fast rate. Most of them happen because of the carelessness of the driver of the vehicles on the road. THE ACCIDENT PREVENTION MECHANISM IN VEHICLES is an attempt to reduce such road accidents by implementing some extra features on the vehicles which can be controlled by software. This project is developed on the basis of certain assumptions. 1.Most of the accidents are happened due to the carelessness or the drowsiness of the driver. 2.The driver may not detect the obstacle which comes in front of the Vehicles, from a safe distance. 3.The different light systems of the vehicles are not properly used whenever needed. This project tries to minimize the accidents which may be caused by the inability of the driver to take sudden actions in a panic situation. If the driver does not respond properly within a time slot, then the vehicle automatically steers to a safe space and continues the journey safely. This system automatically switches on the different types of lights in the vehicle such as head light, hazard lights, brake lights and indicators whenever needed. It includes a special wearable spectacle to detect the drowsiness of the driver. It provides the safety mechanism by invoking the buzzer and safe parking, when it identifies that the driver is asleep by analyzing the eye blink. This paper relates to the system for preventing accidents which contains IR sensors, Ultrasound sensors, LDR sensors and works according to a logically developed safe program which is imprinted on the microcontroller using Arduino IDE. This system is developed to overcome the inability of the vehicles to detect the obstacle from the front side and the drowsiness of the driver and do the necessary safe actions thus, reducing the road accidents.

Impact of COVID-19 Pandemic on Pregnant Mothers

Introduction: The COVID pandemic has detrimental impact on physical and psychological wellbeing of expectant mothers. Fear and worry during pregnancy amplifies risks and can have negative physical and psychological consequences for mother and newborn outcomes. So this study intended to assess the impact of COVID-19 pandemic on pregnant mothers during pregnancy. Methods: Descriptive cross-sectional study design was applied among 123 pregnant mothers who visited antenatal OPD of Tribhuvan University Teaching Hospital. Data were collected through non-probability purposive sampling technique by using interview schedule. Descriptive statistic and inferential statistics were used to analyze the collected data. Results: Pregnant mothers faced difficulties to maintain physical wellbeing, 84 (68.3%) did not perform any physical exercise, 96 (78%) were physically inactive, 107(87%) stated absence of sound sleep during pregnancy. Majority i.e. 111 (90.2%) of pregnant mothers perceived fear on outcome of newborn. Likewise, 11(8.9%) had severe impact on their psychological wellbeing during COVID-19 pandemic. Place of residence, number of children and trimester of pregnancy were found to be the strong predictors of psychological impact among pregnant women. Conclusion: The impact was seen on exercise, sleep, physical wellbeing whereas pregnant mothers seemed more attentive on healthy diet. They expressed more fear on obstetric or newborn outcome and uncertainty on mode of delivery with this panic situation.

Model considering panic emotion and personality traits for crowd evacuation

Panic is a common emotion when pedestrians are in danger during the actual evacuation, which can affect pedestrians a lot and may lead to fatalities as people are crushed or trampled. However, the systematic studies and quantitative analysis of evacuation panic, such as panic behaviors, panic evolution, and the stress responses of pedestrians with different personality traits to panic emotion are still rare. Here, combined with the theories of OCEAN (openness, conscientiousness, extroversion, agreeableness, neuroticism) model and SIS (susceptible, infected, susceptible) model, an extended cellular automata model is established by the floor field method in order to investigate the dynamics of panic emotion in the crowd and dynamics of pedestrians affected by emotion. In the model, pedestrians are divided into stable pedestrians and sensitive pedestrians according to their different personality traits in response to emotion, and their emotional state can be normal or panic. Besides, emotion contagion, emotion decay, and the influence of emotion on pedestrian movement decision-making are also considered. The simulation results show that evacuation efficiency will be reduced, for panic pedestrians may act maladaptive behaviors, thereby making the crowd more chaotic. The results further suggest that improving pedestrian psychological ability and raising the standard of management can effectively increase evacuation efficiency. And it is necessary to reduce the panic level of group as soon as possible at the beginning of evacuation. We hope this research could provide a new method to analyze crowd evacuation in panic situations.

A Classification of Misbehavior Detection Schemes for VANETs: A Survey

In today’s era, thinking of Vehicular Ad-hoc Network as a midrib for the leaf of academic, social, corporate, and economic activities will not be erroneous. To avoid any panic situations like road accidents, heavy traffic jams, etc., the timely availability of correct information is obligatory. The presence of malicious nodes within the network will ruin the dream of establishing a safe, secure, and accident-free vehicular network. This objective can be fulfilled only when malicious nodes within the network are identified correctly, and respective actions are taken at the right time. Therefore, there is a great requirement for efficient and intelligent misbehavior detection techniques to deal with such situations. Vehicular networks are very prone to numerous attacks, such as Sybil attacks, unauthorized access, etc. due to their dynamic nature. The main goal of this study is to discuss and bundle various available misbehavior detection schemes and respective solutions to cope with harmful attackers in the network. We have categorized different misbehavior detections on the criteria of architecture, approach, node-centric, and data-centric. The subcategorization is also given within the paper. One section of this paper focuses on the role of machine learning techniques in misbehavior detection as an emerging foot strap for further enhancement. A comparative analysis of various misbehavior detection schemes is also conducted based on performance measures like accuracy, False Positive Rate, Recall, Precision and F-measurement. Finally, the paper concluded by discussing open issues and various research challenges associated with misbehavior detection in the Vehicular Ad-hoc Network.

Monitoring Panic Situations in Students and Alerting Using Artificial Intelligence

Monitoring Panic Situations in Students and Alerting Using Artificial Intelligence

Panic Attacks are Frequent

Panic is a state of extreme fear of actual or assumed danger to life. Panic is a behavior that occurs in dangerous and crisis situations, leading to crowds and panic situations. A panic attack is a sudden onset of inconspicuous, brief periods of marked discomfort or fear, accompanied by somatic or cognitive symptoms. Panic disorder is the occurrence of recurrent panic attacks, typically accompanied by fear of future attacks or behavioral changes that can avoid situations that create susceptibility to attacks. The diagnosis is made clinically. Isolated panic attacks do not have to be treated. Panic disorder is treated with pharmacotherapy and psychotherapy or both. Panic attacks are frequent and affect as many as 10% of the population in one year. Most people recover without treatment; some get panic disorder. Panic disorder is rare, affecting 2-3% of the population over a 12-month period. It usually starts late in adolescence or young adulthood and affects women 2 to 3 times more often than men.