Hasil untuk "Crisis management. Emergency management. Inflation"

L. Comfort

Maarten P. Scholl, Mahmoud Mahfouz, Anisoara Calinescu et al.

While investment funds publicly disclose their objectives in broad terms, their managers optimize for complex combinations of competing goals that go beyond simple risk-return trade-offs. Traditional approaches attempt to model this through multi-objective utility functions, but face fundamental challenges in specification and parameterization. We propose a generative framework that learns latent representations of fund manager strategies without requiring explicit utility specification. Our approach directly models the conditional probability of a fund's portfolio weights, given stock characteristics, historical returns, previous weights, and a latent variable representing the fund's strategy. Unlike methods based on reinforcement learning or imitation learning, which require specified rewards or labeled expert objectives, our GAN-based architecture learns directly from the joint distribution of observed holdings and market data. We validate our framework on a dataset of 1436 U.S. equity mutual funds. The learned representations successfully capture known investment styles, such as "growth" and "value," while also revealing implicit manager objectives. For instance, we find that while many funds exhibit characteristics of Markowitz-like optimization, they do so with heterogeneous realizations for turnover, concentration, and latent factors. To analyze and interpret the end-to-end model, we develop a series of tests that explain the model, and we show that the benchmark's expert labeling are contained in our model's encoding in a linear interpretable way. Our framework provides a data-driven approach for characterizing investment strategies for applications in market simulation, strategy attribution, and regulatory oversight.

Qingkai Zhang, L. Jeff Hong, Houmin Yan

The rapid expansion of cross-border e-commerce (CBEC) has created significant opportunities for small- and medium-sized sellers, yet financing remains a critical challenge due to their limited credit histories. Third-party logistics (3PL)-led supply chain finance (SCF) has emerged as a promising solution, leveraging in-transit inventory as collateral. We propose an advanced credit risk management framework tailored for 3PL-led SCF, addressing the dual challenges of credit risk assessment and loan size determination. Specifically, we leverage conditional generative modeling of sales distributions through Quantile-Regression-based Generative Metamodeling (QRGMM) as the foundation for risk measures estimation. We propose a unified framework that enables flexible estimation of multiple risk measures while introducing a functional risk measure formulation that systematically captures the relationship between these risk measures and varying loan levels, supported by theoretical guarantees. To capture complex covariate interactions in e-commerce sales data, we integrate QRGMM with Deep Factorization Machines (DeepFM). Extensive experiments on synthetic and real-world data validate the efficacy of our model for credit risk assessment and loan size determination. This study explores the use of generative models in CBEC SCF risk management, illustrating their potential to strengthen credit assessment and support financing for small- and medium-sized sellers.

Hemant Purohit, Cody Buntain, Amanda Lee Hughes et al.

The work of Emergency Management (EM) agencies requires timely collection of relevant data to inform decision-making for operations and public communication before, during, and after a disaster. However, the limited human resources available to deploy for field data collection is a persistent problem for EM agencies. Thus, many of these agencies have started leveraging social media as a supplemental data source and a new venue to engage with the public. While prior research has analyzed the potential benefits and attitudes of practitioners and the public when leveraging social media during disasters, a gap exists in the critical analysis of the actual practices and uses of social media among EM agencies, across both geographical regions and phases of the EM lifecycle - typically mitigation, preparedness, response, and recovery. In this paper, we conduct a mixed-method analysis to update and fill this gap on how EM practitioners in the U.S. and Europe use social media, building on a survey study of about 150 professionals and a follow-up interview study with 11 participants. The results indicate that using social media is no longer a non-traditional practice in operational and informational processes for the decision-making of EM agencies working at both the local level (e.g., county or town) and non-local level (e.g., state/province, federal/national) for emergency management. Especially, the practitioners affiliated with agencies working at the local level have a very high perceived value of social media for situational awareness (e.g., analyzing disaster extent and impact) and public communication (e.g., disseminating timely information and correcting errors in crisis coverage). We conclude with the policy, technological, and socio-technical needs to design future social media analytics systems to support the work of EM agencies in such communication including the applications of AI.

Olga V. Nemerovets

Цель. Разработка и реализация комплексного подхода для моделирования процессов переполнения водохранилища, размыва грунтовой плотины и развития чрезвычайной ситуации в нижнем бьефе гидроузла. Методы. Моделирование процессов с учетом методов расчета, включающих уравнение баланса воды для оценки переполнения водохранилища, двухстадийный процесс размыва грунтовой плотины с учетом изменения формы ее профиля, а также уравнения Сен-Венана для моделирования движения воды в нижнем бьефе. Результаты. Разработан комплексный подход моделирования развития чрезвычайной ситуации на гидротехническом объекте вследствие переполнения водохранилища, перелива воды через гребень и размыва грунтового сооружения. На основании полученного гидрографа размываемых расходов в створе грунтовой плотины определены параметры волны прорыва, зоны и уровни затопления в нижнем бьефе гидроузла. Выполнена апробация разработанного комплексного подхода при разработке проектной документации на реконструкцию гидроузла в городе Ошмяны, с моделированием процессов переполнения водохранилища и определением границ затопления территорий нижнего бьефа в зависимости от различной пропускной способности водосбросного сооружения. Область применения исследований. Область применения результатов исследования охватывает несколько ключевых направлений, связанных с обеспечением безопасности гидротехнических сооружений и прогнозированием возможных аварийных ситуаций. В частности, проектирование и эксплуатация гидротехнических объектов, оценка устойчивости старых гидросооружений, предупреждение и предотвращение чрезвычайных ситуаций. Применение результатов моделирования для оценки потенциального ущерба экосистемам и населенным пунктам, расположенным в зонах риска. Результаты могут быть использованы для разработки нормативных правовых актов, стандартов и рекомендаций по безопасности гидротехнических объектов и зонированию территорий, подверженных угрозе затоплений.

Fatemeh Zaheri, alireza abdi, Mahmoud Rahmati

Telephone Cardiopulmonary Resuscitation (T-CPR), administered by Emergency Medical Dispatchers (EMDs) to bystanders at the scene of an out-of-hospital cardiac arrest (OHCA), faces significant challenges. These challenges arise when collaboration for CPR is difficult due to the bystander’s condition or when the patient’s condition is not visible. Limited research exists on T-CPR, which is why our study aims to explore the experiences of Kermanshah EMDs in providing T-CPR. This descriptive phenomenological (because there is lack of information and study about this subject in Iran and importance of a deep understanding to examine different aspect of the subject) study was conducted with 12 EMDs from a total of 20 in Kermanshah EMDs. Data were collected through in-depth, semi-structured interviews with participants selected via purposive sampling. The study was qualitative and the questionnaire was not validated. Interviews consisted of both open-ended and probing questions. This research was carried out in 2020–2021. Data were analyzed thematically using Collizi’s seven-step. Analysis of the 12 interviews conducted with dispatchers who had an average age of 28.33 years and 2.33 years of work experience resulted in the identification of 456 codes. These codes were categorized into three main themes: (1) “Perceived Nursing Care in T-CPR,” which includes sub-themes such as Ethical and Emotional Management in Care, Empathetic Care, Crisis Management and Stress Control; (2) “Professional Abilities of EMDs,” which includes sub-themes like Perceived Professional Skills and Satisfaction from Successful Performance; and (3) “Cultural Necessities Related to Telephone Resuscitation,” with sub-themes such as Challenges of Training, Communication Barriers and the Need for Public Education and Cultural Change. Participants reported that T-CPR is often unsuccessful due to factors such as non-collaboration from bystanders or improper execution, stemming from low education levels, cultural barriers and a general lack of public awareness about emergency procedures. Successful T-CPR requires dispatchers to skillfully communicate with anxious bystanders and correct misconceptions that CPR may worsen the patient’s condition. Additionally, fluency in various accents, improving public education, and implementing effective stress management strategies are essential for improving outcomes. Addressing these issues through better education and cultural change is vital for enhancing T-CPR effectiveness.

Katarzyna Czernek-Marszałek, D. Wójcik, Patrycja Juszczyk et al.

PURPOSE: Nowadays enterprises operate in a very turbulent environment characterized by frequent, significant, and often unpredictable changes. Such conditions, including crises, force enterprises to take quick actions to adapt to changing conditions. The aim of the paper is to identify chances and timing strategies used by tourism entrepreneurs in conditions of large-scale emergencies (such as COVID-19) and show how they can serve organizational resilience. METHODOLOGY: Qualitative research was conducted in the form of 12 individual in-depth interviews and 4 focus group interviews with 22 representatives of selected industries in the tourism sector. The concept of chance management and timing strategies is used to present how, according to our interviewees, changes in the environment caused by the pandemic contributed to the survival and development of their entities in the tourism market. FINDINGS: The research findings showed that changes caused by the pandemic allowed entities to identify several chances. These chances mainly concerned the introduction of changes to the offer (accelerating previously planned changes and enabling the introduction of unplanned changes). Moreover, they provided the chances to use held digital competences and time to think about the company’s development strategy, as well as establishing and developing relationships with stakeholders. Additionally, our research identified four timing strategies used by tourism entrepreneurs in the time of crisis, i.e. chance-grasping strategy, chance-entraining strategy, chance-riding strategy, and chance-creating strategy. IMPLICATIONS: Tourism enterprises are highly exposed to operating in crisis conditions. Therefore, chance management can be very useful in their activity and our research findings can be also useful regarding its theoretical and practical implications. From the theoretical point of view, we show how the concept of chance management (in particular timing strategies) can be useful for analyzing the reactions of tourism entrepreneurs to changes in times of crisis and taking advantage of opportunities arising from crisis situations. From a practical point of view, we show what strategies, depending on entrepreneurs’ subjective assessment of the current and future conditions for implementing changes, can serve organizational resilience in times of crisis. ORIGINALITY AND VALUE: This paper fills a research gap related to the use of the concepts of chance management and timing strategies from the perspective of tourist enterprises resilience, previously not used in this context and to a limited extent used in the general management literature so far.

M. Trbojević, Mirjana Radovanovic

Abstract The main objective of the paper is analysis and proposal of a concept for establishing an efficient system for disaster management in the Western Balkan countries. After the breakup of Yugoslavia (1992), there has been no effective system for managing emergency situations, while cross-border cooperation in this respect does not exist at all. The paper provides an overview of the situation in the field of emergency and crisis management in five countries of the region and a concept of promotion and cross-border cooperation in this field. The results of the research show that no country in the region has adequate emergency and disaster management system and that, regardless of the negative experiences, an efficient multilateral cooperation system has not been established so far in this field (there is neither regulatory framework nor proposals for the model of organization and for the procedures or technical mechanisms that would make the above possible). Therefore, the concept of establishing the Regional Center for Disaster Management in the Western Balkans territory (RCDM-WB) is proposed as a first step in handling disaster situations that arise from natural phenomena or technical and technological accidents. This is the first scientifically developed proposal of this kind for the above-mentioned region.

Yuyu Chen, Ruodu Wang

In statistical analysis, many classic results require the assumption that models have finite mean or variance, including the most standard versions of the laws of large numbers and the central limit theorems. Such an assumption may not be completely innocent, and it may not be appropriate for datasets with heavy tails (e.g., catastrophic losses), relevant to financial risk management. In this paper, we discuss the importance of infinite-mean models in economics, finance, and related fields, with recent results and examples. We emphasize that many results or intuitions that hold for finite-mean models turn out to fail or even flip for infinite-mean models. Due to the breakdown of standard thinking for infinite-mean models, we argue that if the possibility of using infinite-mean models cannot be excluded, great caution should be taken when applying classic methods that are usually designed for finite-mean cases in finance and insurance.

Matteo Cederle, Marco Fabris, Gian Antonio Susto

Autonomous intersection management (AIM) poses significant challenges due to the intricate nature of real-world traffic scenarios and the need for a highly expensive centralised server in charge of simultaneously controlling all the vehicles. This study addresses such issues by proposing a novel distributed approach to AIM utilizing multi-agent reinforcement learning (MARL). We show that by leveraging the 3D surround view technology for advanced assistance systems, autonomous vehicles can accurately navigate intersection scenarios without needing any centralised controller. The contributions of this paper thus include a MARL-based algorithm for the autonomous management of a 4-way intersection and also the introduction of a new strategy called prioritised scenario replay for improved training efficacy. We validate our approach as an innovative alternative to conventional centralised AIM techniques, ensuring the full reproducibility of our results. Specifically, experiments conducted in virtual environments using the SMARTS platform highlight its superiority over benchmarks across various metrics.

Bastien Baldacci, Philippe Bergault, Olivier Guéant

This paper introduces a novel methodology for the pricing and management of share buyback contracts, overcoming the limitations of traditional optimal control methods, which frequently encounter difficulties with high-dimensional state spaces and the intricacies of selecting appropriate risk penalty or risk aversion parameter. Our methodology applies optimized heuristic strategies to maximize the contract's value. The computation of this value utilizes classical methods typically used for pricing path-dependent options. Additionally, our approach naturally leads to the formulation of a $Δ$-hedging strategy and disentangles therefore the repurchase strategy from the hedging of the payoff.

Mingchun Luo, Yanfu Zeng, Ling-Chu Su et al.

Since the 1970s, researchers have developed semi-empirical models to describe fire smoke movement inside buildings, but there are three major issues. Firstly, several plume models are available to estimate the smoke production rate and the capacity of smoke extraction fans, but their discrepancy or accuracy is unclear. Secondly, the phenomenon of stratification affects the vertical transportation of smoke, and influences the activation time of the detectors and the efficiency of the smoke extraction system. A stratification model is available in the literature to calculate the maximum height that smoke can rise, but it cannot cover all design scenarios. Thirdly, the size of the smoke reservoir has been regulated in fire regulation. The regulation does not consider the factors that strongly affect the movement of smoke in the reservoir, such as the ceiling height, reservoir shape, smoke temperature, etc. These models are difficult to directly apply to a practical design project, and some clauses of the fire regulation do not address the requirements correctly and become a hurdle of design. This paper depicts the cases encountered during the design over the past decades and provides detailed processes of solving these issues. The approach of the design process demonstrates how fire engineers further develop the fire models and fill the gap between research and engineering practice. This paper systematically examines fire smoke models for the plume, vertical transportation of the smoke, the ceiling jet, and smoke spreading underneath the flat ceiling, and provides practical solutions for each of the smoke development stages.

Donwe Choi, Keon-Hyung Lee, Jongsun Park

Purpose Despite the unprecedented challenges caused by the COVID-19 pandemic, nonprofit organizations (NPOs) continued providing services, thereby contributing to overcoming the pandemic. What enabled NPOs to sustain their service provision during this global emergency? This study attempts to answer this question by focusing on one of the essential pillars supporting the operation of NPOs: volunteers. More specifically, we aim to investigate how person–organization (P–O) fit and generation, particularly the Millennial generation, are related to engagement in voluntary activities during the COVID-19 pandemic. Methods We collected data through an online survey conducted in March 2021. This US national survey was completed by 2307 respondents, yielding the US Census balanced data regarding gender, age, race, education, and income. To analyze the data, we employed the two-stage Heckman selection model. Results Relying on P-O fit theory and generational theory, the study identifies what led existing volunteers to continue engaging in volunteer activities at their NPO during the COVID-19 pandemic despite the risks. We found that P-O fit mattered in volunteers’ decision to continue engaging. In addition, our study uncovered that when existing volunteers were Millennials, the relationship between P-O fit and engagement in voluntary activities strengthened during the pandemic. Conclusion This study contributes to expanding the explanatory power of the P–O fit theory by testing it in an emergency and extends the generational theory by clarifying under what conditions Millennials (aka Generation Me) transform themselves into Generation We. In addition, linking NPO management and emergency management, this study provides NPO managers with practical implications for securing reliable volunteers who will sustain the capacity of the NPO in a crisis.

Marc Velay, Bich-Liên Doan, Arpad Rimmel et al.

Deep Reinforcement Learning approaches to Online Portfolio Selection have grown in popularity in recent years. The sensitive nature of training Reinforcement Learning agents implies a need for extensive efforts in market representation, behavior objectives, and training processes, which have often been lacking in previous works. We propose a training and evaluation process to assess the performance of classical DRL algorithms for portfolio management. We found that most Deep Reinforcement Learning algorithms were not robust, with strategies generalizing poorly and degrading quickly during backtesting.

Hanqi Su, Jay Lee

In the field of Prognostics and Health Management (PHM), recent years have witnessed a significant surge in the application of machine learning (ML). Despite this growth, the field grapples with a lack of unified guidelines and systematic approaches for effectively implementing these ML techniques and comprehensive analysis regarding industrial open-source data across varied scenarios. To address these gaps, this paper provides a comprehensive review of ML approaches for diagnostics and prognostics of industrial systems using open-source datasets from PHM Data Challenge Competitions held between 2018 and 2023 by PHM Society and IEEE Reliability Society and summarizes a unified ML framework. This review systematically categorizes and scrutinizes the problems, challenges, methodologies, and advancements demonstrated in these competitions, highlighting the evolving role of both conventional machine learning and deep learning in tackling complex industrial tasks related to detection, diagnosis, assessment, and prognosis. Moreover, this paper delves into the common challenges in PHM data challenge competitions by emphasizing data-related and model-related issues and evaluating the limitations of these competitions. The potential solutions to address these challenges are also summarized. Finally, we identify key themes and potential directions for future research, providing opportunities and prospects for next-generation ML-PHM development in PHM domain.

Вадим Александрович Кудряшов, Сергей Сергеевич Ботян, Станислав Сергеевич Коба et al.

Цель. На основании анализа технических решений, применяемых для устройства огнестойких подвесных потолков с использованием гипсовых негорючих плит, разработать типовой образец фрагмента для натурных испытаний с воздействием огня снизу (со стороны помещения). Провести огневые испытания и определить огнестойкость экспериментального образца, получить температурно-временные зависимости для локальных точек испытываемого фрагмента, наиболее подверженных разрушениям и деформациям в результате нагрева. Методы. Анализ результатов существующих исследований и методов для достижения целей исследований. Разработка типового образца для испытаний согласно требованиям СТБ EN 1363-1-2009, СТБ EN 1364-2-2009. Разработка методики определения температурно-временных зависимостей при нагреве для локальных точек образца огнестойкого подвесного потолка. Экспериментальные огневые исследования. Результаты. Огнестойкий подвесной потолок с применением гипсовых негорючих плит является наиболее простым и распространенным решением для увеличения предела огнестойкости горизонтальных элементов перекрытий и покрытий. Для подтверждения технических решений, применяемых для устройства огнестойких подвесных потолков с применением гипсовых негорючих плит, был разработан типовой экспериментальный образец. Огнестойкий подвесной потолок, сформированный двумя сплошными слоями гипсовых негорючих плит марки Gyproc Fire общей толщиной 25 мм и двумя слоями минеральной ваты марки ISOVER 50/E/K плотностью 14±10 % кг/м3 общей толщиной 100 мм на несущем двухуровневом каркасе из тонкостенных профилей соответствует пределу огнестойкости EI 60 (a←b) согласно СТБ EN 1364-2-2009. Средняя температура на необогреваемой поверхности минераловатных плит составила 170 °С на 65-й минуте испытаний. Область применения исследований. Полученные результаты огневых испытаний могут быть использованы в численном моделировании нагрева огнестойкого подвесного потолка при высокотемпературном воздействии, а также в практической деятельности как огнезащитное решение для строительных конструкций.

اصغر عابدینی, امیر شیخی

آمایش دفاعی در کشوری مانند ایران می‌تواند در جهت برنامه‌ریزی و ایجاد موانعی برای بازدارندگی از حملات دشمن و به‌حداقل‌رساندن آسیب‌پذیری‌ها در شهرها و در راستای مسائل توسعه پایدار و امنیت شهرها، جوامع و زیرساخت‌های مهم شهری استفاده نمود. در این راستا پژوهش حاضر به پهنه‌بندی شهر ارومیه با رویکرد آمایش دفاعی پرداخته است. نوع تحقیق بر اساس اهداف کاربردی و ماهیت توصیفی تحلیلی است. به همین منظور ابتدا با مطالعه منابع مرتبط با رویکرد آمایش دفاعی و پدافند غیرعامل تعداد 6 معیار و 22 زیر معیار با توجه به در دسترس بودن اطلاعات برای شهر ارومیه انتخاب شده است. محاسبه وزن شاخص ها با استفاده از فرایند تحلیل شبکه ANP در نرم افزار Super Decision انجام گرفت. سپس با وارد کردن شاخص ها به محیط GIS و پیاده­سازی آن ها بر گستره شهر، نقشه­های مربوط به هر شاخص تولید شد؛ از تلفیق نقشه های زیرمعیارهای مربوط به هر معیار، نقشه پهنه بندی بر اساس آن معیار خاص و در نهایت از تلفیق این نقشه­های 6 گانه، پهنه­بندی نهایی آمایش دفاعی شهرارومیه به دست آمد. نتایج حاصل از نقشه همپوشانی معیار ها نشان می­دهد حدود 17درصد از سطح شهر در پهنه آسیب پذیری زیاد و 26 درصد در پهنه آسیب­پذیری متوسط و 55 درصد در پهنه آسیب­پذیری کم قرار گرفته است . در ادامه جهت رتبه­بندی مناطق از مدل تصمیم­گیری SAW استفاده شده است که حاکی از آسیب­پذیری منطقه 2 و 4 بیشتر از مناطق 3 و 1 است.

Наталия Николаевна Пыжова

Цель. Выявить особенности и описать механизмы формирования субъектами деятельности оперативных образов при разрешении проблемных и экстремальных ситуаций, проанализировать возможности оценки и развития оперативного интеллекта. Методы. Для моделирования проблемной ситуации использовался эксперимент. Анализ письменных тестов проводился методом контент-анализа. Для выявления взаимосвязи эффективности действий в эксперименте и показателей оперативного мышления использовались тест на практический интеллект (Хорст Х. Зиверт), оперативные задачи (В.Н. Пушкин, Д.Н. Завалишина). Результаты. Показано, что оперативный образ складывается по ходу действия как продукт отражения преобразуемого объекта. Он динамичен, подчинен задаче действия, в нем не содержится избыточных признаков. Важным свойством оперативного образа является функциональная деформация признаков объекта, на основании которой из информационного задела отбираются только те признаки, которые способствуют решению задачи. В ситуации информационной неопределенности динамический оперативный образ сразу не формируется, имеет место этап случайного перебора альтернативных вариантов действий, в результате чего состояние управляемого объекта, как правило, ухудшается. Затем происходит уточнение релевантных признаков, структура образа становится адекватной задаче действия, и, наконец, вырабатывается принятая стратегия по разрешению проблемной ситуации. Правильная постановка цели деятельности на начальном этапе включения субъекта в оперативный процесс сокращает количество циклов проб и ошибок. Оперативный интеллект можно оценивать и целенаправленно развивать путем стимулирования нестандартного мышления обучающихся, решения пространственно-комбинаторных оперативных задач, моделирования проблемной ситуации, включая использование потенциала группы в деловых играх. Область применения исследований. Результаты исследования могут быть применены для оценки компонентов оперативного мышления в различных видах деятельности, связанных с принятием решений в проблемных и экстремальных ситуациях, а также для развития оперативного интеллекта при подготовке специалистов соответствующих профессий.