Disaster Conditions Research Articles

Omsk Industrialist Georgy Yakovlevich Serebryakov in the Conditions of a Civil War

The publication is a biographical study dedicated to a prominent representative of the pre-revolutionary Siberian industrial and commercial bourgeoisie, tobacco manufacturer George Yakovlevich Serebryakov. The work illustrates the social adaptation of a person to the conditions of state and political disasters caused by the events of the Revolution and the Civil War in the east of Russia, using the example of the personality of this figure, very famous in the circles of commerce and power. Based on the specifics of the study the theory of social adaptation, as well as the historical and biographical method, became the methodological basis for the preparation of this article and determined its genre. A connection is made between the question presented in the study and the historiography of the problem, with an emphasis on unexplored plots in the biography of the hero of the story, which allows us to confirm the novelty of this publication. To write the article, a complex of historical sources was used, concentrated in the case of G.Ya. Serebryakov as a justice of the peace (from the funds of the Historical Archive of the Omsk Region) and criminal case 1920-1921 initiated by the Cheka in relation to our hero (from the archive of the FSB of Russia in the Omsk region). This work is addressed to researchers of social history, the Civil War in Russia, the repressive policies of the Soviet state at an early stage and genealogy-practices.

Toward a coordination of inventory and distribution schedules for blood in disasters

The need for efficient blood supply is of more significance in the event of disasters, when there is a lack of coordination between distribution and inventory management. The recent earthquake in Kermanshah province in Iran is among such cases that confirmed the need for coordinating such schedules. In this respect, a two-stage stochastic programming (SP) approach is presented for planning supply of blood after disasters that can assist in inventory decisions under hybrid uncertainty, minimizing the shortage and wastages. The uncertainty stems from imprecise parameters and scenario variability, and a robust-fuzzy-stochastic programming (RFSP) approach is devised to hedge against the uncertainty. The perishability of blood, the substitutability of blood groups, and the age-based characteristic of blood are taken into account to make the model more reliable. The compromise programming is applied to solve the multi-objective model. The results illustrate that the RFSP model can make a reasonable trade-off between mean value, feasibility robustness, and optimality robustness, which results in a robust and reliable solution under disastrous conditions.

A bi-level programming approach for improving relief logistics operations: A real case in Kermanshah earthquake

Due to its location on the world dry belt, Iran is known as a disaster-prone country. Regarding such a problem, planning for relief operations in disaster situations seems significant and undeniable. The literature on disaster management has mostly defined their problems in a single-level framework, ignoring the bi-level aspect of such problems in both preparedness and response phases. However, in the context of disaster in the real world, there is normally more than one decision-maker that each of them may have their own objective. In this study, a bi-level multi-objective programming approach is extended to design a pre-positioning and distribution network under disastrous conditions considering both preparedness and response phases. The extended framework takes into account simultaneous planning for the distribution of drug, blood and relief items among disaster victims, and transferring the injured to hospital in order to diminish the adverse effects of potential disasters in the response phase. Additionally, to determine suitable candidate places for locating relief centers in the preparedness phase, a modified version of data envelopment analysis model is utilized, something that is not frequently done for facility location planning in the disaster management field. On the other hand, to solve the bi-level multi-objective programming problem with decision-makers at the upper level (the affected country) and the lower level (the international organization), a fuzzy goal programming algorithm is proposed. Furthermore, a consolidated method with respect to a novel fuzzy measure is developed to keep the considered network safe against the inherent uncertainty. Finally, the extended framework is utilized to solve a case study in Kermanshah, the province of Iran.

Factors affecting successful transition between post-disaster recovery phases: a case study of 2010 floods in Sindh, Pakistan

PurposeThis paper aims to describe an in-depth study conducted on transition of recovery into subsequent recovery phases after the 2010 super floods in the Sindh province of Pakistan. The objectives of this research were to examine the post-disaster activities after the floods and highlight the critical areas hindering the transition into an effective recovery phase.Design/methodology/approachA case study approach based on literature reviews with semi-structured interviews with disaster management stakeholders were applied as the primary source of data.FindingsThe study found that long-term recovery was the most neglected phase of post-disaster recovery (PDR). The factors hindering successful transition following short-term recovery activities are lack of following: community-level involvement, local administration and community capacity, disaster governance, different stakeholders and coordination, information and knowledge management.Research limitations/implicationsThis paper examines the long-term disaster recovery after the 2010 super floods in three districts of Sindh. Therefore, researchers are encouraged to investigate the factors in other areas for different types of disasters.Practical implicationsThese findings are critical to planning future post-disaster recoveries in the region. It also provides a basis to investigate other types of disasters.Originality/valueThe transition of recovery into long-term phase has never been investigated before. The recovery phase is an opportune time to incorporate strategies for building back better, resilience, mitigation and preparedness. A PDR that does not incorporate these strategies in the long-term leaves affected communities in more vulnerable conditions for future disasters.

The Model of Fuzzy Logic in IoT System as Decision Support System for Determining Flood Disaster Status

Flood is the most frequent disaster in the world. The impact of floods is very large, like human and animal death, the villages vanished and other environments damaged. In disaster preparedness, it is very necessary to divide the stages of the disaster status level. Therefore the public can prepare themselves according to these stages. The stage of disaster preparedness status is also beneficial for the government and related institutions to act according to the status stage of the disaster. This paper will propose the early warning system for flood disaster based on fuzzy logic in IoT system. This algorithm was built 8 rules. The inputs are the rainfall and height of water. The output is the status of flood disaster. The types of disaster status are normal, moderate 1, moderate 2, emergency 1, and emergency 2. From the simulation result, it is concluded that this fuzzy logic model can to determine the status of flood disaster very well.

Settlement Landscape Planning based on Flood Mitigation in Pinang Sub-district Tangerang City

The Pinang sub-district is one of the sub-districts in Tangerang City. Along with the access road development, the residential areas in The Pinang Sub-district has also increased. But behind the development activities of residential areas in Pinang sub-district, there is a flood disaster in the residential landscape as a landscape hazard. Flood disaster in Pinang sub-district, is a disaster that occurs almost every year, especially during the rainy season. Pinang sub-district itself belongs to the Angke River Basin. According to the BNPB 2016, the potential for flood disasters in Pinang District also played a role in the magnitude of the impact of flooding in Banten Province, such as social impacts of 10,476,016 people and economic impacts of 3,611,576 million rupiahs. Settlement landscape planning based on flood disaster mitigation needs to be done to prevent loss and loss of life in Pinang District. The purpose of this study is to identify the physical, biophysical, and social aspects of settlements in Pinang sub-district, analyze the risk of flood disasters and the land suitability of the residential landscape in Pinang sub-district, and develop a landscape plan of settlement based on flood mitigation in Pinang Sub-district. This research conducted at eleven villages in Pinang sub-district, from January to May 2019. The methods used in this research are preparation, inventory, analysis, synthesis, and landscape planning. The analysis conducted the legality analysis, flood disaster risk analysis, and land suitability analysis for settlement development. The analysis results then become a reference in landscape plan preparation. The landscape plan is prepared based on spatial, activity, evacuation, facility plan, circulation plan, and vegetation plan. The basic concept in this research is the settlement landscape of Pinang sub-district based on flood disaster mitigation to reduce the impact that can occur due to disasters by considering pre-disaster, disaster, and post-flood conditions.

Blood RNA Integrity is a Direct and Simple Reporter of Radiation Exposure and Prognosis: A Pilot Study.

In the event of a mass casualty radiation scenario, rapid assessment of patients' health and triage is required for optimal resource utilization. Identifying the level and extent of exposure as well as prioritization of care is extremely challenging under such disaster conditions. Blood-based biomarkers, such as RNA integrity numbers (RIN), could help healthcare personnel quickly and efficiently determine the extent and effect of multiple injuries on patients' health. Evaluation of the effect of different radiation doses, alone or in combination with burn injury, on total RNA integrity over multiple time points was performed. Total RNA integrity was tallied in blood samples for potential application as a marker of radiation exposure and survival. Groups of aged mice (3-6 mice/group, 13-18 months old) received 0.5, 1, 5, 10 or 20 Gy ionizing radiation. Two additional mouse groups received low-dose irradiation (0.5 or 1 Gy) with a 15% total body surface area (TBSA) burn injury. Animals were euthanized at 2 or 12 h and at day 1, 2, 3, 7 or 14 postirradiation, or when injury-mediated mortality occurred. Total RNA was isolated from blood. The quality of RNA was evaluated and RNA RIN were obtained. Analysis of RIN indicated that blood showed the clearest radiation effect. There was a time- and radiation-dose-dependent reduction in RIN that was first detectable at 12 h postirradiation for all doses in animals receiving irradiation alone. This effect was reversible in lower-dose groups (i.e., 0.5, 1 and 5 Gy) that survived to the end of the study (14 days). In contrast, the effect persisted for 10 and 20 Gy groups, which showed suppression of RIN values <4.5 with high mortalities. Radiation doses of 20 Gy were lethal and required euthanasia by day 6. A low RIN (<2.5) at any time point was associated with 100% mortality. Combined radiation-burn injury produced significantly increased mortality such that no dually-injured animals survived beyond day 3, and no radiation dose >1 Gy resulted in survival past day 1. More modest suppression of RIN was observed in the surviving dually challenged mice, and no statistically significant changes were identified in RIN values of burn-only mice at any time point. In this study of an animal model, a proof of concept is presented for a simple and accurate method of assessing radiation dose exposure in blood which potentially predicts lethality. RIN assessment of blood-derived RNA could form the basis for a clinical decision-support tool to guide healthcare providers under the strenuous conditions of a radiation-based mass casualty event.

Preparation of cookies from banana flour, soy flour, and Moringa leaf flour as an emergency food product

Emergency food is a processed food product specifically designed for consumption in post-natural disaster conditions. The food can be provided for 15 days until having adequate assistance. Emergency food products must meet the daily energy requirements of individuals, around 2100 kcal per day. One of the emergency food products is cookies. The purpose of this study was to evaluate the nutritional compound, hardness, and organoleptic properties of emergency food in the form of cookies, prepared from Saba banana flour, soy flour, and Moringa flour. The treatment in this research using a single factor, namely different composition of the flour with three variables and three replications. The three variables were F1 (banana flour 25%, soy flour 10%, and Moringa flour 10%), F2 (banana flour 15%, soy flour 15%, and Moringa flour 15%), and F3 (banana flour 20%, soy flour 20%, and Moringa flour 5%). The parameters were macro nutritional components, such as protein (Kjedhal extraction), fat content (Soxhlet method), and carbohydrate (difference method). It was also evaluated water content (wet basis by drying oven), ash content (furnace), fiber content, hardness (Texture analyzer), calorie (by calculation), and hedonic sensory test in terms of color, taste, aroma, and texture. The results showed that all treatments fulfill the calorie requirement of emergency food. In terms of hardness, F2 resulted in the hardest texture of cookies but still eatable. Organoleptic test results showed that cookies with the use of 20% banana flour, 20% soybean flour, and 5% moringa flour favored by the panelists.

Disastrous hydropower, uneven regional development, and decolonization in India's Eastern Himalayan borderlands

Sikkim, a small Eastern Himalayan state in India has twenty-seven hydropower projects proposed under the Indian Power Ministry's hydropower initiative that envisions the Himalayan region as the country's "future powerhouse" (Dharamadhikary 2008; Kohli, 2011). In 2011, a 6.9 magnitude earthquake rocked Sikkim, the epicenter of which was located eerily close to two under construction dams and the Dzongu reserve, revered as sacred by Sikkim's Indigenous minority Lepchas. Drawing on interviews with Lepcha residents of Dzongu, and state geologists and disaster management officials, I center my analysis on their encounters with disasters and hydropower infrastructure. Building on decolonial theorizations and scholarship on Himalayan borderlands, I argue that disastrous hydropower forms on historical terrains shaped not only by geophysical conditions but also generations of uneven regional development, and the racialized colonial and postcolonial governance of the Eastern Himalayan frontier. In placing ‘disastrous’ as a prefix to hydropower, I follow my interlocutors who implicate state and private developers in producing disaster conditions in Sikkim even as they evade culpability by discursively shifting blame onto the region's “inhospitable terrain” (GoI 2008: 27). I demonstrate that despite key differences in their relation to state power both Dzongu Lepchas and Sikkimese technocrats, forward a materialist, place-based understanding of precarity, differential vulnerability, and uneven regional development. Centering Indigenous and regionalist critiques, I argue that the recent entry of hydropower development in the Eastern Himalayas, conceptualized by colonial authorities as India's “Mongolian Fringe” (Baruah, 2013), requires a closer attention to the entanglements of frontier-making and racialization in India. More broadly, I demonstrate how disastrous hydropower development in a racialized frontier region offers a productive entry into decolonial theorizing in the Indian context.

Quantifying Flood Water Levels Using Image-Based Volunteered Geographic Information

Many people use smartphone cameras to record their living environments through captured images, and share aspects of their daily lives on social networks, such as Facebook, Instagram, and Twitter. These platforms provide volunteered geographic information (VGI), which enables the public to know where and when events occur. At the same time, image-based VGI can also indicate environmental changes and disaster conditions, such as flooding ranges and relative water levels. However, little image-based VGI has been applied for the quantification of flooding water levels because of the difficulty of identifying water lines in image-based VGI and linking them to detailed terrain models. In this study, flood detection has been achieved through image-based VGI obtained by smartphone cameras. Digital image processing and a photogrammetric method were presented to determine the water levels. In digital image processing, the random forest classification was applied to simplify ambient complexity and highlight certain aspects of flooding regions, and the HT-Canny method was used to detect the flooding line of the classified image-based VGI. Through the photogrammetric method and a fine-resolution digital elevation model based on the unmanned aerial vehicle mapping technique, the detected flooding lines were employed to determine water levels. Based on the results of image-based VGI experiments, the proposed approach identified water levels during an urban flood event in Taipei City for demonstration. Notably, classified images were produced using random forest supervised classification for a total of three classes with an average overall accuracy of 88.05%. The quantified water levels with a resolution of centimeters (&lt;3-cm difference on average) can validate flood modeling so as to extend point-basis observations to area-basis estimations. Therefore, the limited performance of image-based VGI quantification has been improved to help in flood disasters. Consequently, the proposed approach using VGI images provides a reliable and effective flood-monitoring technique for disaster management authorities.

Airports’ role as logistics centers in humanitarian supply chains: A surge capacity management perspective

The purpose of this study is to investigate the key factors of airport logistics surge capacity and the relationships between these elements. The findings show that successful airport surge capacity management is closely related to prioritizing the flights and operational activities; considering the influx of local people to airports and local infrastructure capacity in the planning phase; developing suitable methods to encourage people to take part in surge operations; providing uninterrupted communication in and out of airport. In view of the above-stated findings this study suggests that airports can meet the surge demand through systematic capacity planning of the existing and additional human, supply, system and space elements by considering experienced or anticipated capacity shortages in disaster conditions.

Natural hazard assessment and mapping using remote sensing and QGIS tools for Mumbai city, India

Flooding and water logging possess severe hazards to human population in many parts of the world. Mumbai, the study area, is one of the cities in India and has been frequently affected by floods and landslides causing heavy loss of life and property. Enormous concretization and 150-year-old storm water drainage system of Mumbai have led to water logging and flood-like conditions which leads to natural hazard. The objective of this study is to identify the flood and landslide spots and to prepare the map by using GIS software. The study also consists of comparing potential of QGIS and Arc-GIS software in the form of data analysis and thematic map creation. From this study, it is clear that large-scale reshaping took place to complete the reclamation project which makes all those areas prone to various hazards. In assessment of flood and landslide spots, many significant points were revealed: the average elevation of Mumbai is 14 m, and also majority of the flood spots have an elevation range between 5 and 14 m. The analysis of the database generated in QGIS software also revealed that significant numbers of flood spots are mostly found in the reclamation zone and the landslide spots near base of hill. This study indicates that the current situation may trigger disastrous conditions in the future which need intervention from government bodies, institutions and NGOs to prepare proper disaster management plans to help mitigate this situation. To mitigate the problem of water logging, it is required to drain off the water into the ground. Pervious concrete is the best solution for it but for its implementation detailed database of the waterlogged area is required.

Microgrid Control, Storage, and Communication Strategies to Enhance Resiliency for Survival of Critical Load

Adequately, as far as the global system is concerned with the variation in the climatic condition, the frequency of disaster is rising, resulting in various damages to the power grid. To cope with the power network problems due to disasters such as grid outages, frequency, and voltage deviation, the network should be incorporated with numerous distributed generations such as solar and wind. During the disaster condition, these distributed fossil generations form Microgrids (MGs) by disconnecting itself from the grid and maintain power flow to the local region. Besides, the negative impacts on the environment, such as carbon emission has reduced by using Renewable Energy Sources (RES). Apart from reducing carbon emission (as in the case of fossil fuel generation plants), RES based microgrid also useful for the resilient distribution system. However, high penetration of distributed generation, for a resilient system that can survive at least its critical loads during extreme disaster conditions, requires robust architecture and communication between the devices of a microgrid. This article presents the latest review of the various classification of microgrid architecture along with the technical characteristics of energy storage devices, various communication channels and discover the gaps to form a bridge between microgrid in normal and abnormal (during a climatic disaster) conditions. In addition, alteration in control techniques for Alternative Current and Direct Current microgrid for robust MGs is presented systematically. Furthermore, the latest developments with sectionalizer placement to provide the steps to achieve near-real-time data and necessary actions required to take during or before the actual disaster are also presented in a systematic manner.

Examination of the factors that influence public perception of mythically-based human behavior in disaster conditions

Starting from the importance of risk perception for taking certain preventive measures to protect people and their property from disasters, the subject of the research is to examine the factors influencing public perception of mythically-based human behavior in disaster conditions. Using the random sampling method, 250 adult respondents were surveyed in the city of Belgrade, using a specially created and adapted survey questionnaire. The results of the research show that there is no statistically significant influence of gender, age, educational and economic factors on the public perception of human behavior in disaster conditions. The results of the research can be used to improve strategies and campaigns based on risk assessment, aimed at improving the safety of people in disasters.

An Integrated Transmission Expansion and Sectionalizing-Based Black Start Allocation of BESS Planning Strategy for Enhanced Power Grid Resilience

This paper proposes a new comprehensive integrated planning strategy for the resilience enhancement of power system, including determining the transmission expansion and sectionalizing-based optimal black start (BS) resources allocation of battery energy storage system (BESS) during extreme events. The planning model comprises of two stages, namely the normal stage and resilience stage. The first stage is to make the collaborative planning decisions, i.e., constructing transmission lines and installation of BESS as BS sources. The second stage minimizes the power system generation cost and load shedding cost under disaster conditions. The planning algorithm is developed to describe the uncertainty of transmission lines outage status, which can be affected by the normal stage expansion states. In algorithm ways, the model was solved with a duality-based column and constraint generation (D-CCG) method. Taking IEEE 30-bus and 39-bus system for examples and GUROBI/CPLEX was utilized to solve proposed model. Numerical cases show the effectiveness of the model and the superiority of the solution strategy.

PROBLEMS OF HUMAN RIGHTS PROTECTION UNDER THE CONDITIONS OF A GLOBAL ECOLOGICAL DISASTER DUE TO POLLUTION OF ENVIRONMENT

Purpose: to investigate problems of human rights protection under the conditions of a global ecological disaster due to pollution of environment and suggest ways of their solution. Research methods: general scientific and special methods were used when writing the article. The dialectical method of cognition made it possible to consider the subject matter of research in unity of its social content and legal form, peculiarities of elements of the exercise of right to a secure environment, reveal interactions between them. The historical and legal method was used to analyze the evolution of protection of ecological human rights. In the process of writing the article, such philosophical methods of research were also used: analysis, synthesis, abstraction, deduction and others. An integrated approach to the use of the aforementioned scientific methods made it possible to comprehensively explore problems of human rights protection under a global ecological disaster due to pollution of environment. Results: creation of a single, sanctioned normative act that would regulate the field of ecological human rights is one of the priorities for the contemporary world. Neglecting ecological problems leads to millions of annual deaths, billions of pollution-related diseases, environmental degradation, including water scarcity, depletion of fisheries, natural disasters due to the depletion of natural resources, etc. A horrible picture of globalization of the world testifies about lack of control and interest on the part of citizens, civil organizations, loss of sense of ecological threat, non-using the opportunities for ecological control that leads to global ecological problems as well as starvation and malnutrition, diseases, epidemics, physical and moral exhaustion of human. In order to survive, conscious citizens must unite in civil organizations and form ecological awareness that is able to predict and model ecological processes and in future it will influence on the adoption of relevant laws, determining the directions of ecological activities. Discussion: state of protection of ecological human rights.

Advanced Wavelet Sampling Algorithm for IoT based environmental monitoring and management

Presently, various high end systems have been utilized to check the instantaneous change in the climate through deep monitoring methods with advanced mathematical modelling, whereas the major problem in the present research is the data management and precision in detecting various disaster conditions of the smart environment. Though The present instrument for disaster prediction has come up with various satellites and radar, which suffers instrumentation and data management issues that has been resolved in this research. The prominent improvement in the IoT technology shows better fine-grain structure, more flexibility and accuracy. The Proposed technique uses Advanced Adaptive Wavelet Sampling Algorithm (AAWSA)that has been designed and developed in this paper helps to improve the precision range of the instrument during disaster prediction in the urban region. The developed instrument utilizes advanced mathematical modelling with the linear data analytics approach which shows emerging outcomes than the present system which are used in practice.

Microgrids for Disaster Management: An Ethical Risk Perspective

Microgrids are interconnected distributed energy generation and storage systems that can act as either an extension of the existing grid or operate independently of the grid, in so-called island mode [1]. As a power supply technology, microgrids are attractive as they can be more reliable than existing infrastructure and reduce societies? reliance on nonrenewable energy sources [1]. As a valid alternative to reliance on centralized electricity generation and grid distribution, microgrids have value that materializes when disasters render grids inoperable and microgrids remain as islands of service. It is these specific disaster conditions that reveal the latent value of microgrids as disaster management tools, whereas under nondisaster conditions, their value remains hidden. Microgrids can thus be leveraged to manage disaster relief efforts while remaining connected to donor sources and the broader humanitarian relief supply chain.

Mathematical modeling and fuzzy approach for disaster analysis on geo-spatial rock mass in open-pit mining

Due to the complex nature of open-pit mining rock mass, multiple variables has a significant impact on slope stability, which is difficult to evaluate under disaster conditions. The damaged rock slope stability analysis using fundamental fuzzy model is established using the concept of fuzzy measurements upon the basis of statistical analysis on large amount of measured data in Geo-Spatial study. Because of the marked “fuzziness” of the variables is analyzed in this research, the slope stability issues under disaster conditions has been analyzed using Fuzzy Mathematical Theory (FMT) which examines damaged rock slope deformation failure at the open-pit mining. The fuzzy probability formula for rock mass deformation failure, and a numerical method for calculating the fuzzy probability, is derived by applying the theory of variation probability measurements in open pit mining. Here the damaged rock slope under disaster conditions in open-pit mine area has been analyzed and The fuzzy based disaster data management concept has been proposed for analyzing the disaster in open-pit mine area for the damaged rock due to disasters. Finally, the formulation of the Gauss–Legendre is a three-point technical illustration of damaged rock slope which has been used in the open pit. The practical calculation demonstrates that the technique is used for evaluating the slope stability problems in the metal mine opencast under disaster conditions.

Cloud assisted big data information retrieval system for critical data supervision in disaster regions

Presently, the advancement of Cloud Assisted Big Data information retrieval system(CABDIRS) for heterogeneous data management plays a significant role in disaster management framework. In the recent past, facilitating disaster related activities such as Emergency information collection, sharing of exposed insights data about the region, and integration with local groups as well as global scale across various communities’ need assistance for precise and timely information retrieval framework concerning about disaster management. However, the available information retrieval system in the market has limited invariant integration model, whereas it provides improper sharing and collaboration capabilities in dynamic environment about the disaster areas. Hence, this research driving this exploration for powerful use of Cloud assisted big data system which uses Regression based information retrieval measurable computational model (RBIRMM) that offers to foresee the collection, sharing and integration of data in the disaster management regions. This paper features the integration of Cloud assisted IoT(CIoT)and Big data system for information retrieval system which assist the government in taking decisions during disaster conditions in an effective fasten manner. This paper feature the fundamental research that moves through experimental validation which has been conducted and reported with numerical data in a virtual environment. The RBIRMM achieves 98% of accuracy when compared to other traditional methods.