Search results for: extreme weather events

Authors: Ping Xu, Gregory T. Golm, Guanghan (Frank) Liu

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In the presence of competing events, traditional survival analysis may not be appropriate and can result in biased estimates, as it assumes independence between competing events and the event of interest. Instead, competing risk analysis should be considered to correctly estimate the survival probability of the event of interest and the hazard ratio between treatment groups. The COVID-19 pandemic has provided a potential source of competing risks in clinical trials, as participants in trials may experienceCOVID-related competing events before the occurrence of the event of interest, for instance, death due to COVID-19, which can affect the incidence rate of the event of interest. We have performed simulation studies to compare multiple competing risk analysis models, including the cumulative incidence function, the sub-distribution hazard function, and the cause-specific hazard function, to the traditional survival analysis model under various scenarios. We also provide a general recommendation on conducting competing risk analysis in randomized clinical trials during the era of the COVID-19 pandemic based on the extensive simulation results.

Keywords: competing risk, survival analysis, simulations, randomized clinical trial, COVID-19 pandemic

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Authors: Yu-Da Chen, Chia-Chun Wu

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The relationship between antecedent soil moisture content and soil erosion is a complicated phenomenon. Some studies confirm the effect of antecedent soil moisture content on soil erosion, but some deny it. Therefore, the objective of this study is to clarify such contradictions through field experiments. This study conducted two-year field observations of soil losses from natural rainfall events on runoff plots with a length of 10 meters, width of 3 meters, and uniform slope of 9%. Volumetric soil moisture sensors were used to log the soil moisture changes for each rainfall event. A total of 49 effective events were monitored. Results of this study show that antecedent soil moisture content promotes the generation of surface runoff, especially for rainfall events with short duration or lower magnitudes. A positive correlation was found between antecedent soil moisture content and soil loss per unit Rainfall-Runoff Erosivity Index, which indicated that soil with high moisture content is more susceptible to detachment. Once the rainfall duration exceeds 10 hours, the impact from the rainfall duration to soil erosion overwrites, and the effect of antecedent soil moisture is almost negligible.

Keywords: antecedent soil moisture content, soil loss, runoff coefficient, rainfall-runoff erosivity

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Authors: Ivana Čavlina Tomašević, Višnjica Vučetić, Maja Telišman Prtenjak, Barbara Malečić

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The Split wildfire on the mid-Adriatic Coast in July 2017 is one of the most severe wildfires in Croatian history, given the size and unexpected fire behavior, and it is used in this research as a case study to run the Weather Research and Forecasting Spread Fire (WRF SFIRE) model. This coupled fire-atmosphere model was successfully run for the first time ever for one Croatian wildfire case. Verification of coupled simulations was possible by using the detailed reconstruction of the Split wildfire. Specifically, precise information on ignition time and location, together with mapped fire progressions and spotting within the first 30 hours of the wildfire, was used for both – to initialize simulations and to evaluate the model’s ability to simulate fire’s propagation and final fire scar. The preliminary simulations were obtained using high-resolution vegetation and topography data for the fire area, additionally interpolated to fire grid spacing at 33.3 m. The results demonstrated that the WRF SFIRE model has the ability to work with real data from Croatia and produce adequate results for forecasting fire spread. As the model in its setup has the ability to include and exclude the energy fluxes between the fire and the atmosphere, this was used to investigate possible fire-atmosphere interactions during the Split wildfire. Finally, successfully coupled simulations provided the first numerical evidence that a wildfire from the Adriatic coast region can modify the dynamical structure of the surrounding atmosphere, which agrees with observations from fire grounds. This study has demonstrated that the WRF SFIRE model has the potential for operational application in Croatia with more accurate fire predictions in the future, which could be accomplished by inserting the higher-resolution input data into the model without interpolation. Possible uses for fire management in Croatia include prediction of fire spread and intensity that may vary under changing weather conditions, available fuels and topography, planning effective and safe deployment of ground and aerial firefighting forces, preventing wildland-urban interface fires, effective planning of evacuation routes etc. In addition, the WRF SFIRE model results from this research demonstrated that the model is important for fire weather research and education purposes in order to better understand this hazardous phenomenon that occurs in Croatia.

Keywords: meteorology, agrometeorology, fire weather, wildfires, couple fire-atmosphere model

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Authors: Minho Kwon, Jeonghee Lim, Yeongseok Jeong, Donghoon Shin, Kiyoung Kim

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Recently, global warming phenomenon has led to natural disasters caused by global environmental changes, and due to abnormal weather events, the frequency and intensity of heavy rain storm typhoons are increasing. Therefore, it is imperative to prepare for future heavy rain storms and typhoons. This study selects arbitrary target bridges and performs numerical analysis to evaluate the safety of bridge piers in the event that the water level changes. The numerical model is based on two-dimensional surface elements. Actual reinforced concrete was simulated by modeling concrete to include reinforcements, and a contact boundary model was applied between the ground and the concrete. The water level applied to the piers was considered at 18 levels between 7.5 m and 16.1 m. The elastic modulus, compressive strength, tensile strength, and yield strength of the reinforced concrete were calculated using 250 random combinations and numerical analysis was carried out for each water level. In the results of analysis, the bridge exceeded the stated limit at 15.0 m. At the maximum water level of 16.1m, the concrete’s failure rate was 35.2%, but the probability that the reinforcement would fail was 61.2%.

Keywords: Monte-Carlo method, pier, water level change, limit state

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Authors: Abdullah Eqal Al Mazrooei

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In this paper, a nonlinear dynamical system is presented. This system is a bilinear class. The bilinear systems are very important kind of nonlinear systems because they have many applications in real life. They are used in biology, chemistry, manufacturing, engineering, and economics where linear models are ineffective or inadequate. They have also been recently used to analyze and forecast weather conditions. Bilinear systems have three advantages: First, they define many problems which have a great applied importance. Second, they give us approximations to nonlinear systems. Thirdly, they have a rich geometric and algebraic structures, which promises to be a fruitful field of research for scientists and applications. The type of nonlinearity that is treated and analyzed consists of bilinear interaction between the states vectors and the system input. By using some properties of the tensor product, these systems can be transformed to linear systems. But, here we discuss the nonlinearity when the state vector is multiplied by itself. So, this model will be able to handle evolutions according to the Lotka-Volterra models or the Lorenz weather models, thus enabling a wider and more flexible application of such models. Here we apply by using an estimator to estimate temperatures. The results prove the efficiency of the proposed system.

Keywords: Lorenz models, nonlinear systems, nonlinear estimator, state-space model

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Authors: Farnaz Farhangi

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Many people in New Zealand believe that the access to water is inexhaustible, and it comes from a history of virtually unrestricted access to it. For the region like Hamilton which is one of New Zealand’s fastest growing cities, it is crucial for policy makers to know about the future water consumption and implementation of rules and regulation such as universal water metering. Hamilton residents use water freely and they do not have any idea about how much water they use. Hence, one of proposed objectives of this research is focusing on forecasting water consumption using different methods. Residential water consumption time series exhibits seasonal and trend variations. Seasonality is the pattern caused by repeating events such as weather conditions in summer and winter, public holidays, etc. The problem with this seasonal fluctuation is that, it dominates other time series components and makes difficulties in determining other variations (such as educational campaign’s effect, regulation, etc.) in time series. Apart from seasonality, a stochastic trend is also combined with seasonality and makes different effects on results of forecasting. According to the forecasting literature, preprocessing (de-trending and de-seasonalization) is essential to have more performed forecasting results, while some other researchers mention that seasonally non-adjusted data should be used. Hence, I answer the question that is pre-processing essential? A wide range of forecasting methods exists with different pros and cons. In this research, I apply double seasonal ARIMA and Artificial Neural Network (ANN), considering diverse elements such as seasonality and calendar effects (public and school holidays) and combine their results to find the best predicted values. My hypothesis is the examination the results of combined method (hybrid model) and individual methods and comparing the accuracy and robustness. In order to use ARIMA, the data should be stationary. Also, ANN has successful forecasting applications in terms of forecasting seasonal and trend time series. Using a hybrid model is a way to improve the accuracy of the methods. Due to the fact that water demand is dominated by different seasonality, in order to find their sensitivity to weather conditions or calendar effects or other seasonal patterns, I combine different methods. The advantage of this combination is reduction of errors by averaging of each individual model. It is also useful when we are not sure about the accuracy of each forecasting model and it can ease the problem of model selection. Using daily residential water consumption data from January 2000 to July 2015 in Hamilton, I indicate how prediction by different methods varies. ANN has more accurate forecasting results than other method and preprocessing is essential when we use seasonal time series. Using hybrid model reduces forecasting average errors and increases the performance.

Keywords: artificial neural network (ANN), double seasonal ARIMA, forecasting, hybrid model

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Authors: Indu Gupta

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Climate change and global warming is most burning issue for “our common future”. For this common global interest. Countries organize conferences of government and nongovernment type. Human being destroying the non-renewable resources and polluting the renewable resources of planet for economic growth. Air pollution is mainly responsible for global warming and climate change .Due to global warming ice glaciers are shrinking and melting. Forests are shrinking, deserts expanding and soil eroding. The depletion of stratospheric ozone layer is depleting and hole in ozone layer that protect us from harmful ultra violet radiation. Extreme high temperature in summer and extreme low temperature and smog in winters, floods in rainy season. These all are indication of climate change. The level of carbon dioxide and other heat trapping gases in the atmosphere is increasing at high speed. Nation’s are worried about environmental degradation.

Keywords: environmental degradation, global warming, soil eroding, ultra-Violate radiation

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Authors: Elizabeth F. Rodrigues, Julia da R. Mattos, Naira Q. Leitão, Roberta T. da Cunha

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The business strategy of many companies has two factors in common: the search for the competitive edge and its long term maintenance. The thing that differentiates the companies’ performance in their abilities to set the right strategy, which depends on their capacity to analyze and apply all sort of management support tools. In this context, the sponsorship of events stands out as an important way to increase brand awareness, especially when it is a worldwide event, such as Rio 2016 Olympic and Paralympic Games. This paper will present the case of a car maker company, which chose to invest on sponsorship as a way to reach its goals and grow in the brazilian market.

Keywords: strategy, sponsorship, events, management

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Authors: Raul Chavez Jr.

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Green roof's body of knowledge appears to be in its infancy stage in the Philippines. To contribute to its development, this study intends to answer the question: Does the existing green roof in Metro Manila perform well in providing thermal comfort and satisfaction to users? Relatively, this study focuses on thermal sensation and satisfaction of users, surface temperature comparison, weather data comparison of the site (Sky Garden) and local weather station (PAG-ASA), and its thermal resistance capacity. Initially, the researcher conducted a point-in-time survey in parallel with weather data gathering from PAG-ASA and Sky Garden. In line with these, ambient and surface temperature are conducted through the use of a digital anemometer, with humidity and temperature, and non-contact infrared thermometer respectively. Furthermore, to determine the Sky Garden's overall thermal resistance, materials found on site were identified and tabulated based on specified locations. It revealed that the Sky Garden can be considered comfortable based from PMV-PPD Model of ASHRAE Standard 55 having similar results from thermal comfort and thermal satisfaction survey, which is contrary to the actual condition of the Sky Garden by means of a psychrometric chart which falls beyond the contextualized comfort zone. In addition, ground floor benefited the most in terms of lower average ambient temperature and humidity compared to the Sky Garden. Lastly, surface temperature data indicates that the green roof portion obtained the highest average temperature yet performed well in terms of heat resistance compared to other locations. These results provided the researcher valuable baseline information of the actual performance of a certain green roof in Metro Manila that could be vital in locally enhancing the system even further and for future studies.

Keywords: Green Roof, Thermal Analysis, Thermal Comfort, Thermal Performance

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Authors: Satyendra Mourya, Jyoti Jaiswal, Gaurav Malik, Brijesh Kumar, Ramesh Chandra

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Present work describes the fabrication and sensing characteristics of the Pd-Pt decorated nanostructured silicon carbide (SiC) thin films on anodized porous silicon (PSi) substrate by RF magnetron sputtering. The gas sensing performance of Pd-Pt/SiC/PSi sensing electrode towards H2 gas under low (10–400 ppm) detection limit and high operating temperature regime (25–600 °C) were studied in detail. The chemiresistive sensor exhibited high selectivity, good sensing response, fast response/recovery time with excellent stability towards H2 at high temperature. The selectivity measurement of the sensing electrode was done towards different oxidizing and reducing gases and proposed sensing mechanism discussed in detail. Therefore, the investigated Pd-Pt/SiC/PSi structure may be a highly sensitive and selective hydrogen gas sensing electrode for deployment in extreme environment applications.

Keywords: RF Sputtering, silicon carbide, porous silicon, hydrogen gas sensor

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Authors: B. S. Akhmetov, P. T.Kharitonov, L. Sh. Balgabayeva, O. V. Kisseleva, T. S. Kartbayev

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This article analyzes the applicability of known renewable energy technical means as mobile power sources under the field and extreme conditions. The requirements are determined for the parameters of mobile micro-HPP. The application prospectively of the mobile micro-HPP with intelligent control systems is proved for this purpose. Variants of low-speed electric generators for micro HPP are given. Variants of designs for mobile micro HPP are presented with the direct (gearless) transfer of torque from the hydraulic drive to the rotor of the electric generator. Variant of the hydraulic drive for micro HPP is described workable at low water flows. A general structure of the micro HPP intelligent system control is offered that implements the principle of maximum energy efficiency. The legitimacy of construction and application of mobile micro HPP is proved as electrical power sources for life safety of people under the field and extreme conditions.

Keywords: mobile micro-hydro powerplants, information management systems, hydraulic drive, computer science

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Authors: Omaymah AlAzhari

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Nomadic tribes have always had the need to relocate and build shelters, moving from one site to another in search of food, water, and natural resources. They are affected by weather and seasonal changes and consequently started innovating textiles to build better shelters. Their solutions came from the observation of their natural environment, material, and surroundings. The textile innovation of nomadic tribes has led designers to create environmentally responsive products, such as Ceginskas Lindström’s new self-shading tent membrane developed by her ‘smocking’ technique. ‘AlRahala’ Nomadic Bedouin tribes from the Middle East and North African region have used textiles as a fundamental architectural element in their tent structure, ‘Bayt AlShar’ (House of Hair). The nomadic tribe has innovated their textile to create a fabric that is more suited to change in climatic and weather conditions. Based on the research of existing literature and documents, as well as analysis of photographs and videos, to conclude that the traditional textiles and innovations done by nomadic tribes may be a rich source of information for designers, which can provide innovative solutions for manufacturing modern-day textiles.

Keywords: ‘AlRahala’ nomadic tribes, ‘Bayt AlShar’, tent structure, textile innovation

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Authors: Saeed Mohammadirad

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Financing activities involve long-term liabilities, stockholders' equity (or owner's equity), and changes to short-term borrowings. Finance is very important for every business activities. To perform the finance we have to follow the accounting languages bases on the nature of the business. If all are one package in the software, it is easy to handle, monitor, control, plan, organize, direct and budget the finance. Let us make a challenge in the computer software for the whole finance packages of every business related activities. In this article, it mentioned about the finance functions in the various levels of the business activities and how it should be maintained properly to avoid the unethical events.

Keywords: financing activities, business activities, computer software, unethical events

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Authors: Zhengyang Ma

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Mongolia is a significant country bordered by China and Russia. The Mongolian people are the descendants of Genghis Khan. Mongolia has a glorious history and possesses strategic mineral resources. Throughout history, the Qing empire of China has always considered this region as part of China’s hegemony. Due to a series of historical events, Mongolia successfully achieved its independence from China in 1945. In order to clearly understand the status quo in Mongolia today better, it is necessary to explore the reasons that caused Mongolia to achieve its independence from a historical context. Therefore, this essay will analyze and describe the crucial events and reasons that led to the independence of Mongolia through different historical periods.

Keywords: Mongolia, history, power bargain, Sino-Russia relations

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Authors: Saad Ahmed, Sanjeev Khannaa

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Glass fiber reinforced polymers are widely used in structural systems as load-bearing elements at both high and low temperatures. This investigation presents the evaluation of glass fiber reinforced unsaturated polyurethane under harsh conditions of changing temperature and moisture content. This study Explores how these parameters affect the optical properties of the polymer matrix and the composite. Using the hand layup method, the polyurethane resin was modified by E-glass fibers (15 vol. %) to manufacture fiber-reinforced composite. This work includes the preparation of glass-like polyurethane resin sheets and estimates all light transmittance properties at high and very low temperatures and wet conditions. All-optical properties were retested to evaluate the level of improvement or failure. The results found that when comprising reinforced composite fiber to the unreinforced specimens, the reinforced composite shows a fair optical property at high temperatures and good performance at low temperatures.

Keywords: unsaturated polyurethane, extreme temperatures, light transmittance, haze number

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Authors: Andrey V. Timofeev

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The paper presents new results concerning selection of optimal information fusion formula for ensembles of C-OTDR channels. The goal of information fusion is to create an integral classificator designed for effective classification of seismoacoustic target events. The LPBoost (LP-β and LP-B variants), the Multiple Kernel Learning, and Weighing of Inversely as Lipschitz Constants (WILC) approaches were compared. The WILC is a brand new approach to optimal fusion of Lipschitz Classifiers Ensembles. Results of practical usage are presented.

Keywords: Lipschitz Classifier, classifiers ensembles, LPBoost, C-OTDR systems

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Authors: Stefan W. Kienzle

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The increasing number of occurrences of extreme weather and climate events have significant impacts on society and are the cause of continued and increasing loss of human and animal lives, loss or damage to property (houses, cars), and associated stresses to the public in coping with a changing climate. A climate index breaks down daily climate time series into meaningful derivatives, such as the annual number of frost days. Climate indices allow for the spatially consistent analysis of a wide range of climate-dependent variables, which enables the quantification and mapping of historical and future climate change across regions. As trends of phenomena such as the length of the growing season change differently in different hydro-climatological regions, mapping needs to be carried out at a high spatial resolution, such as the 10km by 10km Canadian Climate Grid, which has interpolated daily values from 1950 to 2017 for minimum and maximum temperature and precipitation. Climate indices form the basis for the analysis and comparison of means, extremes, trends, the quantification of changes, and their respective confidence levels. A total of 39 temperature indices and 16 precipitation indices were computed for the period 1951 to 2017 for the Province of Alberta. Temperature indices include the annual number of days with temperatures above or below certain threshold temperatures (0, +-10, +-20, +25, +30ºC), frost days, and timing of frost days, freeze-thaw days, growing or degree days, and energy demands for air conditioning and heating. Precipitation indices include daily and accumulated 3- and 5-day extremes, days with precipitation, period of days without precipitation, and snow and potential evapotranspiration. The rank-based nonparametric Mann-Kendall statistical test was used to determine the existence and significant levels of all associated trends. The slope of the trends was determined using the non-parametric Sen’s slope test. The Google mapping interface was developed to create the website albertaclimaterecords.com, from which beach of the 55 climate indices can be queried for any of the 6833 grid cells that make up Alberta. In addition to the climate indices, climate normals were calculated and mapped for four historical 30-year periods and one future period (1951-1980, 1961-1990, 1971-2000, 1981-2017, 2041-2070). While winters have warmed since the 1950s by between 4 - 5°C in the South and 6 - 7°C in the North, summers are showing the weakest warming during the same period, ranging from about 0.5 - 1.5°C. New agricultural opportunities exist in central regions where the number of heat units and growing degree days are increasing, and the number of frost days is decreasing. While the number of days below -20ºC has about halved across Alberta, the growing season has expanded by between two and five weeks since the 1950s. Interestingly, both the number of days with heat waves and cold spells have doubled to four-folded during the same period. This research demonstrates the enormous potential of using climate indices at the best regional spatial resolution possible to enable society to understand historical and future climate changes of their region.

Keywords: climate change, climate indices, habitat risk, regional, mapping, extremes

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Authors: Yahya N. Alfraidi, Abdel Halim Boussabaine

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Climate change risk impacts are one of the most challenging aspects that faces the built environment now and the near future. The impacts of climate change on buildings are considered in four different dimensions: physical, economic, social, and management. For each of these, the risks are discussed as they arise from various effects linked to climate change, including windstorms, precipitation, temperature change, flooding, and sea-level rise. For example, building assets in cities will be exposed to extreme hot summer days and nights due to the urban heat island effect and pollution. Buildings also could be vulnerable to water, electricity, gas, etc., scarcity. Building materials, fabric and systems could also be stressed by the emerging climate risks. More impotently the building users might experience extreme internal and extern comfort conditions leading to lower productivity, wellbeing and health problems. Thus, the main aim of this paper to document the emerging risks from climate change on building assets. An in-depth discussion on the consequences of these climate change risk is provided. It is expected that the outcome of this research will be a set of risk design indicators for developing and procuring resilient building assets.

Keywords: climate change, risks of climate change, risks on building from climate change, buildings

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Authors: Pedro Miguel Cardoso Carneiro, Ricardo André Nunes Borges, João Pedro Soares Loureiro, Hermínio Maio Graça Fernandes

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Wind energy has been exponentially growing over the last years and will allow countries to progress regarding the decarbonization objective. In parallel, the maintenance activities have also been increasing in consequence of ageing and deterioration of the wind farms. The time available for wind blade maintenance is given by the weather window that is based upon weather conditions. Most of the wind blade repair and maintenance activities require a narrow window of temperature and humidity. Due to this limitation, the current weather windows result only on approximately 35% days/year are used for maintenance, that takes place mostly during summertime. This limitation creates large economic losses in the energy production of the wind towers, since they can be inoperative or with the energy production output reduced for days or weeks due to existing damages. Another important aspect is that the maintenance costs are higher due to the high standby time and seasonality imposed on the technicians. To reduce the relevant maintenance costs of blades and energy loses some technological developments were carried out to significantly improve this reality. The focus of this activity was to develop a series of key developments to have in the near future a suspended access equipment that can operate in harsh conditions, wind rain, cold/hot environment. To this end we have identified key areas that need to be revised and require new solutions to be found; a habitat system, multi-configurable roof and floor, roof and floor interface to blade, secondary attachment solutions to the blade and to the tower. On this paper we will describe the advances produced during a national R&D project made in partnership with an end-user (Onrope) and a test center (ISQ).

Keywords: wind turbine maintenance, cost reduction, technological innovations, wind turbine blade

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Authors: E. Ghoneim, C. Narron, I. Iqbal, I. Hassan, E. Hammam

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The scarcity of water is becoming a more prominent threat, especially in areas that are already arid in nature. Although the Kingdom of Saudi Arabia (KSA) is an arid country, its southwestern region offers a high variety of botanical landscapes, many of which are wooded forests, while the eastern and northern regions offer large areas of groundwater irrigated farmlands. At present, some parts of KSA, including forests and farmlands, have witnessed protracted and severe drought due to change in rainfall pattern as a result of global climate change. Such prolonged drought that last for several consecutive years is expected to cause deterioration of forested and pastured lands as well as cause crop failure in the KSA (e.g., wheat yield). An analysis to determine vegetation drought vulnerability and severity during the growing season (September-April) over a fourteen year period (2000-2014) in KSA was conducted using MODIS Terra imagery. The Vegetation Condition Index (VCI), derived from the Normalized Difference Vegetation Index (NDVI), and the Temperature Condition Index (TCI), derived from the Land Surface Temperature (LST) data was extracted from MODIS Terra Images. The VCI and TCI were then combined to compute the Vegetation Health Index (VHI). The VHI revealed the overall vegetation health for the area under investigation. A preliminary outcome of the modeled VHI over KSA, using averaged monthly vegetation data over a 14-year period, revealed that the vegetation health condition is deteriorating over time in both naturally vegetated areas and irrigated farmlands. The derived drought map for KSA indicates that both extreme and severe drought occurrences have considerably increased over the same study period. Moreover, based on the cumulative average of drought frequency in each governorate of KSA it was determined that Makkah and Jizan governorates to the east and southwest, witness the most frequency of extreme drought, whereas Tabuk to the northwest, exhibits the less extreme drought frequency. Areas where drought is extreme or severe would most likely have negative influences on agriculture, ecosystems, tourism, and even human welfare. With the drought risk map the kingdom could make informed land management decisions including were to continue with agricultural endeavors and protect forested areas and even where to develop new settlements.

Keywords: drought, vegetation health condition, TCI, Saudi Arabia

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Authors: Justin-Herve Noubissi, Jean Claude Kamgang, Eric Ramat, Januarius Asongu, Christophe Cambier

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The goal of our study is to analyse the impact of climatic factors in malaria transmission taking into account migration between Douala and Yaoundé, two cities of Cameroon country. We show how variations of climatic factors such as temperature and relative humidity affect the malaria spread. We propose a meta-population model of the dynamic transmission of malaria that evolves in space and time and that takes into account temperature and relative humidity and the migration between Douala and Yaoundé. We also integrate the variation of environmental factors as events also called mathematical impulsion that can disrupt the model evolution at any time. Our modelling has been done using the Discrete EVents System Specification (DEVS) formalism. Our implementation has been done on Virtual Laboratory Environment (VLE) that uses DEVS formalism and abstract simulators for coupling models by integrating the concept of DEVS.

Keywords: compartmental models, DEVS, discrete events, meta-population model, VLE

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Authors: Rahul Kumar Singh, Apurva Sharma, Dilip Kumar Srivastava

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Tilting of our interest towards unconventional exploitation of hydrocarbons has raised a serious concern to environmentalists. Emerging technologies like horizontal/multi-lateral drilling with subsequent hydraulic fracturing or fracking etc., for exploitation of different conventional/unconventional hydrocarbon reservoirs, are related to creating micro-level seismic events below the surface of the earth. Monitoring of these micro-level seismic events is not possible by the conventional methodology of the seismic method. So, to tackle this issue, a new technology that is microseismic is very much in discussions around the globe. Multiple researches are being carried out these days around the globe in order to prove microseismic as a new essential in the E & P industry, especially for unconventional reservoir management. Microseismic monitoring is now used for reservoir surveillance, and the best application is checking the integrity of the caprock and containment of fluid in it. In general, in whatever terms we want to use micro-seismic related events monitoring and understanding the effectiveness of stimulation, this technology offers a lot of value in terms of insight into the subsurface characteristics and processes, and this makes it really a good geophysical method to be used in future.

Keywords: microseismic, monitoring, hydraulic fracturing or fracking, reservoir surveillance, seismic hazards

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Authors: Habib Abida, Noura Dahri

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Flash floods are among the most serious natural hazards that have disastrous environmental and human impacts. They are associated with exceptional rain events, characterized by short durations, very high intensities, rapid flows and small spatial extent. Flash floods happen very suddenly and are difficult to forecast. They generally cause damage to agricultural crops and property, infrastructures, and may even result in the loss of human lives. The city of Gabes (South-eastern Tunisia) has been exposed to numerous damaging floods because of its mild topography, clay soil, high urbanization rate and erratic rainfall distribution. The risks associated with this situation are expected to increase further in the future because of climate change, deemed responsible for the increase of the frequency and the severity of this natural hazard. Recently, exceptional events hit Gabes City causing death and major property losses. A major flooding event hit the region on June 2nd, 2014, causing human deaths and major material losses. It resulted in the stagnation of storm water in the numerous low zones of the study area, endangering thereby human health and causing disastrous environmental impacts. The characterization of flood risk in Gabes Watershed (South-eastern Tunisia) is considered an important step for flood management. Analytical Hierarchy Process (AHP) method coupled with Monte Carlo simulation and geographic information system were applied to delineate and characterize flood areas. A spatial database was developed based on geological map, digital elevation model, land use, and rainfall data in order to evaluate the different factors susceptible to affect flood analysis. Results obtained were validated by remote sensing data for the zones that showed very high flood hazard during the extreme rainfall event of June 2014 that hit the study basin. Moreover, a survey was conducted from different areas of the city in order to understand and explore the different causes of this disaster, its extent and its consequences.

Keywords: analytical hierarchy process, flash floods, Gabes, remote sensing, Tunisia

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Authors: Ek-Uma Imkome, Jintana Yunibhand, Waraporn Chaiyawat

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Background: Persons with schizophrenia patient and misusing methamphetamines suffering from social dysfunction that impact on their quality of life. Knowledge of factors related to social dysfunction will guide the effective intervention. Objectives: To determine the direct effect, indirect effect and total effect of an acerbate Psychotics’ Symptoms, Social Support, Stressful life events, Medication use self-efficacy impact on social dysfunction in Thai schizophrenic patient and methamphetamine misuse. Methods: Data were collected from schizophrenic and methamphetamine misuse patient by self report. A linear structural relationship was used to test the hypothesized path model. Results: The hypothesized model was found to fit the empirical data and explained 54% of the variance of the psychotic symptoms (X² = 114.35, df = 92, p-value = 0.05, X² /df = 1.24, GFI = 0.96, AGFI = 0.92, CFI = 1.00, NFI = 0.99, NNFI = 0.99, RMSEA = 0.02). The highest total effect on social dysfunction was psychotic symptoms (0.67, p<0.05). Medication use self-efficacy had a direct effect on psychotic symptoms (-0.25, p<0.01), and social support had direct effect on medication use self efficacy (0.36, p <0.01). Conclusions: Psychotic symptoms and stressful life events were the significance factors that influenced direct on social dysfunctioning. Therefore, interventions that are designed to manage these factors are crucial in order to enhance social functioning in this population.

Keywords: psychotic symptoms, methamphetamine, schizophrenia, stressful life events, social dysfunction, social support, medication use self efficacy

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Authors: Retno A. Vinarti, Lucy M. Hederman

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This research describes a knowledge model for a system which give personalized alert to users about infectious disease risks in the context of weather, location and time. The knowledge model is based on established epidemiological concepts augmented by information gleaned from infection-related data repositories. The existing disease risk prediction research has more focuses on utilizing raw historical data and yield seasonal patterns of infectious disease risk emergence. This research incorporates both data and epidemiological concepts gathered from Atlas of Human Infectious Disease (AHID) and Centre of Disease Control (CDC) as basic reasoning of infectious disease risk prediction. Using CommonKADS methodology, the disease risk prediction task is an assignment synthetic task, starting from knowledge identification through specification, refinement to implementation. First, knowledge is gathered from AHID primarily from the epidemiology and risk group chapters for each infectious disease. The result of this stage is five major elements (Person, Infectious Disease, Weather, Location and Time) and their properties. At the knowledge specification stage, the initial tree model of each element and detailed relationships are produced. This research also includes a validation step as part of knowledge refinement: on the basis that the best model is formed using the most common features, Frequency-based Selection (FBS) is applied. The portion of the Infectious Disease risk model relating to Person comes out strongest, with Location next, and Weather weaker. For Person attribute, Age is the strongest, Activity and Habits are moderate, and Blood type is weakest. At the Location attribute, General category (e.g. continents, region, country, and island) results much stronger than Specific category (i.e. terrain feature). For Weather attribute, Less Precise category (i.e. season) comes out stronger than Precise category (i.e. exact temperature or humidity interval). However, given that some infectious diseases are significantly more serious than others, a frequency based metric may not be appropriate. Future work will incorporate epidemiological measurements of disease seriousness (e.g. odds ratio, hazard ratio and fatality rate) into the validation metrics. This research is limited to modelling existing knowledge about epidemiology and chain of infection concepts. Further step, verification in knowledge refinement stage, might cause some minor changes on the shape of tree.

Keywords: epidemiology, knowledge modelling, infectious disease, prediction, risk

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Authors: Rajkumar Ghosh

Abstract:

Earthquakes pose significant risks to human life and infrastructure, highlighting the importance of effective earthquake mitigation strategies. Traditional earthquake modelling and mitigation efforts have largely focused on the primary fault segments and their slip behaviour. However, earthquakes can exhibit complex rupture dynamics, including out-of-sequence thrust (OOST) events, which occur on secondary or subsidiary faults. This abstract examines the impact of OOST dynamics on earthquake mitigation strategies and their implications for hazard assessment and disaster planning. OOST events challenge conventional seismic hazard assessments by introducing additional fault segments and potential rupture scenarios that were previously unrecognized or underestimated. Consequently, these events may increase the overall seismic hazard in affected regions. The study reviews recent case studies and research findings that illustrate the occurrence and characteristics of OOST events. It explores the factors contributing to OOST dynamics, such as stress interactions between fault segments, fault geometry, and mechanical properties of fault materials. Moreover, it investigates the potential triggers and precursory signals associated with OOST events to enhance early warning systems and emergency response preparedness. The abstract also highlights the significance of incorporating OOST dynamics into seismic hazard assessment methodologies. It discusses the challenges associated with accurately modelling OOST events, including the need for improved understanding of fault interactions, stress transfer mechanisms, and rupture propagation patterns. Additionally, the abstract explores the potential for advanced geophysical techniques, such as high-resolution imaging and seismic monitoring networks, to detect and characterize OOST events. Furthermore, the abstract emphasizes the practical implications of OOST dynamics for earthquake mitigation strategies and urban planning. It addresses the need for revising building codes, land-use regulations, and infrastructure designs to account for the increased seismic hazard associated with OOST events. It also underscores the importance of public awareness campaigns to educate communities about the potential risks and safety measures specific to OOST-induced earthquakes. This sheds light on the impact of out-of-sequence thrust dynamics in earthquake mitigation. By recognizing and understanding OOST events, researchers, engineers, and policymakers can improve hazard assessment methodologies, enhance early warning systems, and implement effective mitigation measures. By integrating knowledge of OOST dynamics into urban planning and infrastructure development, societies can strive for greater resilience in the face of earthquakes, ultimately minimizing the potential for loss of life and infrastructure damage.

Keywords: earthquake mitigation, out-of-sequence thrust, seismic, satellite imagery

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Authors: Isaac Mugume, Charles Basalirwa, Daniel Waiswa, Triphonia Ngailo

Abstract:

Rainfall is a major climatic parameter affecting many sectors such as health, agriculture and water resources. Its quantitative prediction remains a challenge to weather forecasters although numerical weather prediction models are increasingly being used for rainfall prediction. The performance of six convective parameterization schemes, namely the Kain-Fritsch scheme, the Betts-Miller-Janjic scheme, the Grell-Deveny scheme, the Grell-3D scheme, the Grell-Fretas scheme, the New Tiedke scheme of the weather research and forecast (WRF) model regarding quantitative rainfall prediction over Uganda is investigated using the root mean square error for the March-May (MAM) 2013 season. The MAM 2013 seasonal rainfall amount ranged from 200 mm to 900 mm over Uganda with northern region receiving comparatively lower rainfall amount (200–500 mm); western Uganda (270–550 mm); eastern Uganda (400–900 mm) and the lake Victoria basin (400–650 mm). A spatial variation in simulated rainfall amount by different convective parameterization schemes was noted with the Kain-Fritsch scheme over estimating the rainfall amount over northern Uganda (300–750 mm) but also presented comparable rainfall amounts over the eastern Uganda (400–900 mm). The Betts-Miller-Janjic, the Grell-Deveny, and the Grell-3D underestimated the rainfall amount over most parts of the country especially the eastern region (300–600 mm). The Grell-Fretas captured rainfall amount over the northern region (250–450 mm) but also underestimated rainfall over the lake Victoria Basin (150–300 mm) while the New Tiedke generally underestimated rainfall amount over many areas of Uganda. For deterministic rainfall prediction, the Grell-Fretas is recommended for rainfall prediction over northern Uganda while the Kain-Fritsch scheme is recommended over eastern region.

Keywords: convective parameterization schemes, March-May 2013 rainfall season, spatial variation of parameterization schemes over Uganda, WRF model

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Authors: Tarek Dandashi

Abstract:

WSNs may provide a fast and reliable solution for the early detection of environment events like forest fires. This is crucial for alerting and calling for fire brigade intervention. Sensor nodes communicate sensor data to a host station, which enables a global analysis and the generation of a reliable decision on a potential fire and its location. A WSN with TinyOS and nesC for the capturing and transmission of a variety of sensor information with controlled source, data rates, duration, and the records/displaying activity traces is presented. We propose a similarity distance (SD) between the distribution of currently sensed data and that of a reference. At any given time, a fire causes diverging opinions in the reported data, which alters the usual data distribution. Basically, SD consists of a metric on the Cumulative Distribution Function (CDF). SD is designed to be invariant versus day-to-day changes of temperature, changes due to the surrounding environment, and normal changes in weather, which preserve the data locality. Evaluation shows that SD sensitivity is quadratic versus an increase in sensor node temperature for a group of sensors of different sizes and neighborhood. Simulation of fire spreading when ignition is placed at random locations with some wind speed shows that SD takes a few minutes to reliably detect fires and locate them. We also discuss the case of false negative and false positive and their impact on the decision reliability.

Keywords: forest fire, WSN, wireless sensor network, algortihm

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Authors: Patricia Kermeci

Abstract:

Policies related to the reduction of both carbon dioxide and energy consumption within the residential sector have contributed towards a growing number of energy-efficient houses being built in several countries. Many of these energy-efficient houses rely on the construction of very well insulated and highly airtight structures, ventilated mechanically. Although energy-efficient houses are indeed more energy efficient than conventional houses, concerns have been raised over the quality of their indoor air and, consequently, the possible adverse health and wellbeing effects for their occupants. Using a longitudinal study design over three different weather seasons (winter, spring and summer), this study has investigated the indoor climate and indoor air quality of different rooms (bedroom, living room and kitchen) in five energy-efficient houses and four conventional houses in the UK. Occupants have kept diaries of their activities during the studied periods and interviews have been conducted to investigate possible behavioural explanations for the findings. Data has been compared with reviews of epidemiological, toxicological and other health related published literature to reveals three main findings. First, it shows that the indoor environment quality of energy-efficient houses cannot be treated as a holistic entity as different rooms presented dissimilar indoor climate and indoor air quality. Thus, such differences might contribute to the health and wellbeing of occupants in different ways. Second, the results show that the indoor environment quality of energy-efficient houses can vary following changes in weather season, leaving occupants at a lower or higher risk of adverse health and wellbeing effects during different weather seasons. Third, one cannot assume that even identical energy-efficient houses provide a similar indoor environment quality. Fourth, the findings reveal that the practices and behaviours of the occupants of energy-efficient houses likely determine whether they enjoy a healthier indoor environment when compared with their control houses. In conclusion, it has been considered vital to understand occupants’ practices and behaviours in order to explain the ways they might contribute to the indoor climate and indoor air quality in energy-efficient houses.

Keywords: energy-efficient house, health and wellbeing, indoor environment, indoor air quality

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Authors: Jeonghun Lee

Abstract:

In this study, we investigated the relationship between stress and thyroid dysfunction in such patients who underwent thyroidectomy. This study included 101 patients who underwent thyroidectomy from January 2015 to June 2020 and experienced hypothyroidism. The included patients had good drug compliance with the same dosage of levothyroxine (LT4). The male-to-female ratio was 1:4.6, and the mean age was 45.4 years at surgery and 50.2 years at stressful events. Eighteen patients underwent lobectomies and, of these, 12 did not take LT4. The mean follow-up period was 49(8-93) months. Statistical analyses were performed using the paired t-test, Wilcoxon signed-rank test, and McNemer test using PROC MIXED with SAS 9.4. Forty-five patients (44.6%) had hypothyroidism with thyroid-stimulating hormone (TSH) >10 μIU/mL. There was distress in 81 patients and eustress in 10 patients. TSH levels increased during a mean 5.8 months (min 1, max 12) in 24 patients who specified the date of their life events. Even though each patient took the same dose of LT4, when the patients were under stress, both the free T4 and T3 decreased and TSH increased, regardless of whether the patient experienced distress or eustress (P <0.001). While adjusting for the effect of the free T4 and T3, TSH increased significantly in the patients after stress (P <0.001). For patients with thyroid cancer who are simultaneously experiencing life events, TSH may be used as a stress biomarker to enable the implementation of appropriate treatment and counseling strategies.

Keywords: endocrine, thyroid, thyroid function, biomarker, stress

Procedia PDF Downloads 87