Search results for: rainfall events

Authors: Charlotte Dreger, Erik Bollaert

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This paper presents two environmentally-friendly coastal structures realized on the Lake of Neuchâtel. Both structures reflect current environmental issues of concern on the lake and have been strongly affected by extreme meteorological conditions between their period of design and their actual operational period. The Lake of Neuchatel is one of the biggest Swiss lakes and measures around 38 km in length and 8.2 km in width, for a maximum water depth of 152 m. Its particular topographical alignment, situated in between the Swiss Plateau and the Jura mountains, combines strong winds and large fetch values, resulting in significant wave heights during storm events at both north-east and south-west lake extremities. In addition, due to flooding concerns, historically, lake levels have been lowered by several meters during the Jura correction works in the 19th and 20th century. Hence, during storm events, continuous erosion of the vulnerable molasse shorelines and sand banks generate frequent and abundant littoral transport from the center of the lake to its extremities. This phenomenon does not only cause disturbances of the ecosystem, but also generates numerous problems at natural or man-made infrastructures located along the shorelines, such as reed plants, harbor entrances, canals, etc. A first example is provided at the southwestern extremity, near the city of Yverdon, where an ensemble of 11 small islands, the Iles des Vernes, have been artificially created in view of enhancing biological conditions and food availability for bird species during their migration process, replacing at the same time two larger islands that were affected by lack of morphodynamics and general vegetalization of their surfaces. The article will present the concept and dimensioning of these islands based on 2D numerical modelling, as well as the realization and follow-up campaigns. In particular, the influence of several major storm events that occurred immediately after the works will be pointed out. Second, a sediment retention dike is discussed at the northeastern extremity, at the entrance of the Canal de la Broye into the lake. This canal is heavily used for navigation and suffers from frequent and significant sedimentation at its outlet. The new coastal structure has been designed to minimize sediment deposits around the exutory of the canal into the lake, by retaining the littoral transport during storm events. The article will describe the basic assumptions used to design the dike, as well as the construction works and follow-up campaigns. Especially the huge influence of changing meteorological conditions on the littoral transport of the Lake of Neuchatel since project design ten years ago will be pointed out. Not only the intensity and frequency of storm events are increasing, but also the main wind directions alter, affecting in this way the efficiency of the coastal structure in retaining the sediments.

Keywords: meteorological evolution, sediment transport, lake of Neuchatel, numerical modelling, environmental measures

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Authors: Zhao Kuo, Chen Liang, Zhang Zhongbing, Ruan Jinlu. He Shiyi, Xu Mengxuan

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Stilbene, C₁₄H₁₂, is well known as one of the most useful organic scintillators for pulse shape discrimination (PSD) technique for its good scintillation properties. An on-line acquisition system and an off-line acquisition system were developed with several CAMAC standard plug-ins, NIM plug-ins, neutron/γ discriminating plug-in named 2160A and a digital oscilloscope with high sampling rate respectively for which stilbene crystals and photomultiplier tube detectors (PMT) as detector for accelerator neutron sources measurement carried out in China Institute of Atomic Energy. Pulse amplitude spectrums and charge amplitude spectrums were real-time recorded after good neutron/γ discrimination whose best PSD figure-of-merits (FoMs) are 1.756 for D-D accelerator neutron source and 1.393 for D-T accelerator neutron source. The probability of neutron events in total events was 80%, and neutron detection efficiency was 5.21% for D-D accelerator neutron sources, which were 50% and 1.44% for D-T accelerator neutron sources after subtracting the background of scattering observed by the on-line acquisition system. Pulse waveform signals were acquired by the off-line acquisition system randomly while the on-line acquisition system working. The PSD FoMs obtained by the off-line acquisition system were 2.158 for D-D accelerator neutron sources and 1.802 for D-T accelerator neutron sources after waveform digitization off-line processing named charge integration method for just 1000 pulses. In addition, the probabilities of neutron events in total events obtained by the off-line acquisition system matched very well with the probabilities of the on-line acquisition system. The pulse information recorded by the off-line acquisition system could be repetitively used to adjust the parameters or methods of PSD research and obtain neutron charge amplitude spectrums or pulse amplitude spectrums after digital analysis with a limited number of pulses. The off-line acquisition system showed equivalent or better measurement effects compared with the online system with a limited number of pulses which indicated a feasible method based on stilbene crystals detectors for the measurement of prompt neutrons neutron sources like prompt accelerator neutron sources emit a number of neutrons in a short time.

Keywords: stilbene crystal, accelerator neutron source, neutron / γ discrimination, figure-of-merits, CAMAC, waveform digitization

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Authors: Nick Woodier, Iain Moppett

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Background: It is estimated that one in ten patients admitted to hospital will suffer an adverse event in their care. While the majority of these will result in low harm, patients are being significantly harmed by the processes meant to help them. Healthcare, therefore, seeks to make improvements in patient safety by taking learning from other industries that are perceived to be more mature in their management of safety events. Of particular interest to healthcare are ‘near misses,’ those events that almost happened but for an intervention. Healthcare does not have any guidance as to how best to manage and learn from near misses to reduce the chances of harm to patients. The authors, as part of a larger study of near-miss management in healthcare, sought to learn from the UK nuclear sector to develop principles for how healthcare can identify, report, and learn from near misses to improve patient safety. The nuclear sector was chosen as an exemplar due to its status as an ultra-safe industry. Methods: A Grounded Theory (GT) methodology, augmented by a scoping review, was used. Data collection included interviews, scenario discussion, field notes, and the literature. The review protocol is accessible online. The GT aimed to develop theories about how nuclear manages near misses with a focus on defining them and clarifying how best to support reporting and analysis to extract learning. Near misses related to radiation release or exposure were focused on. Results: Eightnuclear interviews contributed to the GT across nuclear power, decommissioning, weapons, and propulsion. The scoping review identified 83 articles across a range of safety-critical industries, with only six focused on nuclear. The GT identified that nuclear has a particular focus on precursors and low-level events, with regulation supporting their management. Exploration of definitions led to the recognition of the importance of several interventions in a sequence of events, but that do not solely rely on humans as these cannot be assumed to be robust barriers. Regarding reporting and analysis, no consistent methods were identified, but for learning, the role of operating experience learning groups was identified as an exemplar. The safety culture across nuclear, however, was heard to vary, which undermined reporting of near misses and other safety events. Some parts of the industry described that their focus on near misses is new and that despite potential risks existing, progress to mitigate hazards is slow. Conclusions: Healthcare often sees ‘nuclear,’ as well as other ultra-safe industries such as ‘aviation,’ as homogenous. However, the findings here suggest significant differences in safety culture and maturity across various parts of the nuclear sector. Healthcare can take learning from some aspects of management of near misses in nuclear, such as how they are defined and how learning is shared through operating experience networks. However, healthcare also needs to recognise that variability exists across industries, and comparably, it may be more mature in some areas of safety.

Keywords: culture, definitions, near miss, nuclear safety, patient safety

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Authors: Quznetsov Gunn

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In the study of the logical foundations of probability theory, it was found that the terms and equations of the fundamental theoretical physics represent terms and theorems of the classical probability theory, more precisely, of that part of this theory, which considers the probability of dot events in the 3 + 1 space-time. In particular, the masses, moments, energies, spins, etc. turn out of parameters of probability distributions such events. The terms and the equations of the electroweak and of the quark-gluon theories turn out the theoretical-probabilistic terms and theorems. Here the relation of a neutrino to his lepton becomes clear, the W and Z bosons masses turn out dynamic ones, the cause of the asymmetry between particles and antiparticles is the impossibility of the birth of single antiparticles. In addition, phenomena such as confinement and asymptotic freedom receive their probabilistic explanation. And here we have the logical foundations of the gravity theory with phenomena dark energy and dark matter.

Keywords: classical theory of probability, logical foundation of fundamental theoretical physics, masses, moments, energies, spins

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Authors: Edward Hwang

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The efficiency of public policies depends on customer's satisfaction, and the change directions of public policies hinge on customer's assessment; i.e., the performance of public policies in governments is decided by the citizen's administrative satisfaction! The governments in all levels must heave their efficiency and effectiveness of public services to meet the people's substantially multiple needs in order to make citizens trust the governmental operation styles. To pursue the societal equality and justice, governments should treat people equally and provide more services for the disadvantages. The recent Dapu protest event involves Miaoli county Magistrate Liu cheng-hung who arbitrarily demolished houses and destroyed farmlands, and it shifts his popularity into disaffection. Liu case tells us that the political events are lethal to politicians; it cut almost 20% satisfaction degree for Magistrate Liu and hurt KMT support levels nationally. In terms of administrative satisfaction levels, political factors do matter, especially for the derogated events.

Keywords: local politics, administrative satisfaction, Taiwan, customer satisfaction

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Authors: Adrian O'Hagan, Robert McLoughlin

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Considerable focus in the world of insurance risk quantification is placed on modeling loss values from lines of business (LOBs) that possess upper tail dependence. Copulas such as the Joe, Gumbel and Student-t copula may be used for this purpose. The copula structure imparts a desired level of tail dependence on the joint distribution of claims from the different LOBs. Alternatively, practitioners may possess historical or simulated data that already exhibit upper tail dependence, through the impact of catastrophe events such as hurricanes or earthquakes. In these circumstances, it is not desirable to induce additional upper tail dependence when modeling the joint distribution of the loss values from the individual LOBs. Instead, it is of interest to accurately assess the degree of tail dependence already present in the data. The empirical copula and its associated upper tail dependence coefficient are presented in this paper as robust, efficient means of achieving this goal.

Keywords: empirical copula, extreme events, insurance loss reserving, upper tail dependence coefficient

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Authors: Marzieh Khedmati, Shannon L. Bartelt-Hunt

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Vegetative Filter Strips (VFS) are used for controlling the volume of runoff and decreasing contaminant concentrations in runoff before entering water bodies. Many studies have investigated the role of VFS in sediment and nutrient removal, but little is known about their efficiency for the removal of emerging contaminants such as antimicrobial resistance genes (ARGs). Vegetative Filter Strip Modeling System (VFSMOD) was used to simulate the efficiency of VFS in this regard. Several studies demonstrated the ability of VFSMOD to predict reductions in runoff volume and sediment concentration moving through the filters. The objectives of this study were to calibrate the VFSMOD with experimental data and assess the efficiency of the model in simulating the filter behavior in removing ARGs (ermB) and tylosin. The experimental data were obtained from a prior study conducted at the University of Nebraska (UNL) Rogers Memorial Farm. Three treatment factors were tested in the experiments, including manure amendment, narrow grass hedges and rainfall events. Sediment Delivery Ratio (SDR) was defined as the filter efficiency and the related experimental and model values were compared to each other. The VFS Model generally agreed with the experimental results and as a result, the model was used for predicting filter efficiencies when the runoff data are not available. Narrow Grass Hedges (NGH) were shown to be effective in reducing tylosin and ARGs concentration. The simulation showed that the filter efficiency in removing ARGs is different for different soil types and filter lengths. There is an optimum length for the filter strip that produces minimum runoff volume. Based on the model results increasing the length of the filter by 1-meter leads to higher efficiency but widening beyond that decreases the efficiency. The VFSMOD, which was proved to work well in estimation of VFS trapping efficiency, showed confirming results for ARG removal.

Keywords: antimicrobial resistance genes, emerging contaminants, narrow grass hedges, vegetative filter strips, vegetative filter strip modeling system

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Authors: James P. Takona

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Most of the global population has never lived through a pandemic, and thus there is so much that remains unknown about students' capacity for resiliency under such environments and circumstances and what a timeline for full recovery will look like. The session will guide participants to focus on misinformation and disinformation in the context of recent crisis events, with specific reference to how information flows across. Particular focus will be given to the flow of information in mediated technology and platforms with particular reference to K-12 and teacher preparation program environments. The paper will draw on theories and responses from the sociology of disaster, the social psychology of rumoring, and published studies on disinformation and misinformation. Applications will be identified and applied in the context of online information-sharing during crisis events. The session will offer the application of the Center for Contagious Diseases' Crisis and Emergency Risk Communication model to understand the themes and evolution of misinformation and disinformation. The paper will invite session participants to suggest and interact with raised challenges on the impact of dis-and misinformation.

Keywords: Sociology of disaster, misinformation, dis-information, Social Psychology of rumors

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Authors: Melese Wondatir

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Flooding ranks among the most destructive natural disasters, impacting millions of individuals globally and resulting in substantial economic, social, and environmental repercussions. This study's objective was to create a comprehensive model that assesses the Nile River basin's susceptibility to flood damage and improves existing flood risk management strategies. Authorities responsible for enacting policies and implementing measures may benefit from this research to acquire essential information about the flood, including its scope and susceptible areas. The identification of severe flood damage locations and efficient mitigation techniques were made possible by the use of geospatial data. Slope, elevation, distance from the river, drainage density, topographic witness index, rainfall intensity, distance from road, NDVI, soil type, and land use type were all used throughout the study to determine the vulnerability of flood damage. Ranking elements according to their significance in predicting flood damage risk was done using the Analytic Hierarchy Process (AHP) and geospatial approaches. The analysis finds that the most important parameters determining the region's vulnerability are distance from the river, topographic witness index, rainfall, and elevation, respectively. The consistency ratio (CR) value obtained in this case is 0.000866 (<0.1), which signifies the acceptance of the derived weights. Furthermore, 10.84m2, 83331.14m2, 476987.15m2, 24247.29m2, and 15.83m2 of the region show varying degrees of vulnerability to flooding—very low, low, medium, high, and very high, respectively. Due to their close proximity to the river, the northern-western regions of the Nile River basin—especially those that are close to Sudanese cities like Khartoum—are more vulnerable to flood damage, according to the research findings. Furthermore, the AUC ROC curve demonstrates that the categorized vulnerability map achieves an accuracy rate of 91.0% based on 117 sample points. By putting into practice strategies to address the topographic witness index, rainfall patterns, elevation fluctuations, and distance from the river, vulnerable settlements in the area can be protected, and the impact of future flood occurrences can be greatly reduced. Furthermore, the research findings highlight the urgent requirement for infrastructure development and effective flood management strategies in the northern and western regions of the Nile River basin, particularly in proximity to major towns such as Khartoum. Overall, the study recommends prioritizing high-risk locations and developing a complete flood risk management plan based on the vulnerability map.

Keywords: analytic hierarchy process, Blue Nile Basin, geospatial techniques, flood vulnerability, multi-criteria decision making

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Authors: Hengki Eko Putra, Dennish Ari Putro, Tri Wahyu Hadi, Edi Riawan, Junnaedhi Dewa Gede, Aditia Rojali, Fariza Dian Prasetyo, Yudhistira Satya Pribadi, Dita Fatria Andarini, Mila Khaerunisa, Raditya Hanung Prakoswa

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Catastrophe risk management can only be done if we are able to calculate the exposed risks. Jakarta is an important city economically, socially, and politically and in the same time exposed to severe floods. On the other hand, flood risk calculation is still very limited in the area. This study has calculated the risk of flooding for Jakarta using 2-Dimensional Model ANUGA. 2-Dimensional model ANUGA and 1-Dimensional Model HEC-RAS are used to calculate the risk of flooding from 13 major rivers in Jakarta. ANUGA can simulate physical and dynamical processes between the streamflow against river geometry and land cover to produce a 1-meter resolution inundation map. The value of streamflow as an input for the model obtained from hydrological analysis on rainfall data using hydrologic model HEC-HMS. The probabilistic streamflow derived from probabilistic rainfall using statistical distribution Log-Pearson III, Normal and Gumbel, through compatibility test using Chi Square and Smirnov-Kolmogorov. Flood event on 2007 is used as a comparison to evaluate the accuracy of model output. Property damage estimations were calculated based on flood depth for 1, 5, 10, 25, 50, and 100 years return period against housing value data from the BPS-Statistics Indonesia, Centre for Research and Development of Housing and Settlements, Ministry of Public Work Indonesia. The vulnerability factor was derived from flood insurance claim. Jakarta's flood loss estimation for the return period of 1, 5, 10, 25, 50, and 100 years, respectively are Rp 1.30 t; Rp 16.18 t; Rp 16.85 t; Rp 21.21 t; Rp 24.32 t; and Rp 24.67 t of the total value of building Rp 434.43 t.

Keywords: 2D hydrodynamic model, ANUGA, flood, flood modeling

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Authors: Amani Abdallah, Isam Shahrour

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The quality of drinking water is a major concern of public health. The control of this quality is generally performed in the laboratory, which requires a long time. This type of control is not adapted for accidental pollution from sudden events, which can have serious consequences on population health. Therefore, it is of major interest to develop real-time innovative solutions for the detection of accidental contamination in drinking water systems This paper presents researches conducted within the SunRise Demonstrator for ‘Smart and Sustainable Cities’ with a particular focus on the supervision of the water quality. This work aims at (i) implementing a smart water system in a large water network (Campus of the University Lille1) including innovative equipment for real-time detection of abnormal events, such as those related to the contamination of drinking water and (ii) develop a numerical modeling of the contamination diffusion in the water distribution system. The first step included verification of the water quality sensors and their effectiveness on a network prototype of 50m length. This part included the evaluation of the efficiency of these sensors in the detection both bacterial and chemical contamination events in drinking water distribution systems. An on-line optical sensor integral with a laboratory-scale distribution system (LDS) was shown to respond rapidly to changes in refractive index induced by injected loads of chemical (cadmium, mercury) and biological contaminations (Escherichia coli). All injected substances were detected by the sensor; the magnitude of the response depends on the type of contaminant introduced and it is proportional to the injected substance concentration.

Keywords: distribution system, drinking water, refraction index, sensor, real-time

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Authors: José Leandro Melgar Néris, Claudinéia Brazil, Luciane Teresa Salvi, Isabel Cristina Damin

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The impact the climate change is not recent, the main variable in the hydrological cycle is the sequence and shortage of a drought, which has a significant impact on the socioeconomic, agricultural and environmental spheres. This study aims to characterize and quantify, based on precipitation climatic projections, the rainy and dry events in the region of the Uruguay River Basin, through the Standardized Precipitation Index (SPI). The database is the image that is part of the Intercomparison of Model Models, Phase 5 (CMIP5), which provides condition prediction models, organized according to the Representative Routes of Concentration (CPR). Compared to the normal set of climates in the Uruguay River Watershed through precipitation projections, seasonal precipitation increases for all proposed scenarios, with a low climate trend. From the data of this research, the idea is that this article can be used to support research and the responsible bodies can use it as a subsidy for mitigation measures in other hydrographic basins.

Keywords: climate change, climatic model, dry events, precipitation projections

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Authors: Newton Muhury, Armando A. Apan, Tek N. Marasani, Gebiaw T. Ayele

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The changing climate has degraded freshwater availability in Australia that influencing vegetation growth to a great extent. This study assessed the vegetation responses to groundwater using Terra’s moderate resolution imaging spectroradiometer (MODIS), Normalised Difference Vegetation Index (NDVI), and soil water content (SWC). A hydrological model, SWAT, has been set up in a southeast Australian river catchment for groundwater analysis. The model was calibrated and validated against monthly streamflow from 2001 to 2006 and 2007 to 2010, respectively. The SWAT simulated soil water content for 43 sub-basins and monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) were applied in the machine learning tool, Waikato Environment for Knowledge Analysis (WEKA), using two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The assessment shows that different types of vegetation response and soil water content vary in the dry and wet seasons. The WEKA model generated high positive relationships (r = 0.76, 0.73, and 0.81) between NDVI values of all vegetation in the sub-basins against soil water content (SWC), the groundwater flow (GW), and the combination of these two variables, respectively, during the dry season. However, these responses were reduced by 36.8% (r = 0.48) and 13.6% (r = 0.63) against GW and SWC, respectively, in the wet season. Although the rainfall pattern is highly variable in the study area, the summer rainfall is very effective for the growth of the grass vegetation type. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

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Authors: Kyoko Tominaga

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Non-Government Organizations (NGOs), Non-Profit Organizations (NPOs), Social Enterprises and other actors play an important role in political decisions in governments at the international levels. Especially, such organizations’ and activists’ network in civil society is quite important to effect to the global politics. To solve the complex social problems in global era, diverse actors should corporate each other. Moreover, network of protesters is also contributes to diffuse tactics, information and other resources of social movements. Based on the findings from the study of International Trade Fairs (ITFs), the author analyzes the network of activists in anti-globalism movement. This research focuses the transition of 54 activists’ whole network in the “protest event” against 2008 G8 summit in Japan. Their network is examined at the three periods: Before protest event phase, during protest event phase and after event phase. A mixed method is used in this study: the author shows the hypothesis from social network analysis and evaluates that with interview data analysis. This analysis gives the two results. Firstly, the more protesters participate to the various events during the protest event, the more they build the network. After that, active protesters keep their network as well. From interview data, we can understand that the active protesters can build their network and diffuse the information because they communicate with other participants and understand that diverse issues are related. This paper comes to same conclusion with previous researches: protest events activate the network among the political activists. However, some participants succeed to build their network, others do not. “Networked” activists are participated in the various events for short period of time and encourage the diffusion of information and tactics of social movements.

Keywords: social movement, global justice movement, tactics, diffusion

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Authors: Semachew M. Kassa, Africa M Geremew, Tezera F. Azmatch, Nandyala Darga Kumar

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Frequency ratio (FR) and analytical hierarchy process (AHP) methods are developed based on past landslide failure points to identify the landslide susceptibility mapping because landslides can seriously harm both the environment and society. However, it is still difficult to select the most efficient method and correctly identify the main driving factors for particular regions. In this study, we used fourteen landslide conditioning factors (LCFs) and five soft computing algorithms, including Random Forest (RF), Support Vector Machine (SVM), Logistic Regression (LR), Artificial Neural Network (ANN), and Naïve Bayes (NB), to predict the landslide susceptibility at 12.5 m spatial scale. The performance of the RF (F1-score: 0.88, AUC: 0.94), ANN (F1-score: 0.85, AUC: 0.92), and SVM (F1-score: 0.82, AUC: 0.86) methods was significantly better than the LR (F1-score: 0.75, AUC: 0.76) and NB (F1-score: 0.73, AUC: 0.75) method, according to the classification results based on inventory landslide points. The findings also showed that around 35% of the study region was made up of places with high and very high landslide risk (susceptibility greater than 0.5). The very high-risk locations were primarily found in the western and southeastern regions, and all five models showed good agreement and similar geographic distribution patterns in landslide susceptibility. The towns with the highest landslide risk include Amhara Saint Town's western part, the Northern part, and St. Gebreal Church villages, with mean susceptibility values greater than 0.5. However, rainfall, distance to road, and slope were typically among the top leading factors for most villages. The primary contributing factors to landslide vulnerability were slightly varied for the five models. Decision-makers and policy planners can use the information from our study to make informed decisions and establish policies. It also suggests that various places should take different safeguards to reduce or prevent serious damage from landslide events.

Keywords: artificial neural network, logistic regression, landslide susceptibility, naïve Bayes, random forest, support vector machine

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Authors: Merve Akca

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Retrieval-induced forgetting (RIF) refers to the phenomenon that selective retrieval of some information impairs memory for related, but not previously retrieved information. Despite age differences in retrieval-induced forgetting regarding retrospective memory being documented, this research aimed to highlight age differences in RIF of the prospective memory tasks for the first time. By using retrieval-practice paradigm, this study comparatively examined RIF effects in retrospective memory and event-based prospective memory in young and old adults. In this experimental study, a mixed factorial design with age group (Young, Old) as a between-subject variable, and memory type (Prospective, Retrospective) and item type (Practiced, Non-practiced) as within-subject variables was employed. Retrieval-induced forgetting was observed in the retrospective but not in the prospective memory task. Therefore, the results indicated that selective retrieval of past events led to suppression of other related past events in both age groups but not the suppression of memory for future intentions.

Keywords: prospective memory, retrieval-induced forgetting, retrieval inhibition, retrospective memory

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Authors: Bahareh Golchin, Nooshin Riahi

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One of the most significant issues as attended a lot in recent years is that of recognizing the sentiments and emotions in social media texts. The analysis of sentiments and emotions is intended to recognize the conceptual information such as the opinions, feelings, attitudes and emotions of people towards the products, services, organizations, people, topics, events and features in the written text. These indicate the greatness of the problem space. In the real world, businesses and organizations are always looking for tools to gather ideas, emotions, and directions of people about their products, services, or events related to their own. This article uses the Twitter social network, one of the most popular social networks with about 420 million active users, to extract data. Using this social network, users can share their information and opinions about personal issues, policies, products, events, etc. It can be used with appropriate classification of emotional states due to the availability of its data. In this study, supervised learning and deep neural network algorithms are used to classify the emotional states of Twitter users. The use of deep learning methods to increase the learning capacity of the model is an advantage due to the large amount of available data. Tweets collected on various topics are classified into four classes using a combination of two Bidirectional Long Short Term Memory network and a Convolutional network. The results obtained from this study with an average accuracy of 93%, show good results extracted from the proposed framework and improved accuracy compared to previous work.

Keywords: emotion classification, sentiment analysis, social networks, deep neural networks

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Authors: Pius Marthin, Nihal Ata Tutkun

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Survival analysis has become one of the paramount procedures in the modeling of time-to-event data. When we encounter complex survival problems, the traditional approach remains limited in accounting for the complex correlational structure between the covariates and the outcome due to the strong assumptions that limit the inference and prediction ability of the resulting models. Several studies exist on the deep learning approach to survival modeling; moreover, the application for the case of complex survival problems still needs to be improved. In addition, the existing models need to address the data structure's complexity fully and are subject to noise and redundant information. In this study, we design a deep learning technique (CmpXRnnSurv_AE) that obliterates the limitations imposed by traditional approaches and addresses the above issues to jointly predict the risk-specific probabilities and survival function for recurrent events with competing risks. We introduce the component termed Risks Information Weights (RIW) as an attention mechanism to compute the weighted cumulative incidence function (WCIF) and an external auto-encoder (ExternalAE) as a feature selector to extract complex characteristics among the set of covariates responsible for the cause-specific events. We train our model using synthetic and real data sets and employ the appropriate metrics for complex survival models for evaluation. As benchmarks, we selected both traditional and machine learning models and our model demonstrates better performance across all datasets.

Keywords: cumulative incidence function (CIF), risk information weight (RIW), autoencoders (AE), survival analysis, recurrent events with competing risks, recurrent neural networks (RNN), long short-term memory (LSTM), self-attention, multilayers perceptrons (MLPs)

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Authors: Parvin Ghafarian, Mohammadreza Mohammadpur Panchah, Mehri Fallahi

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Synoptic patterns from surface up to tropopause are very important for forecasting the weather and atmospheric conditions. There are many tools to prepare and analyze these maps. Reanalysis data and the outputs of numerical weather prediction models, satellite images, meteorological radar, and weather station data are used in world forecasting centers to predict the weather. The forecasting extreme precipitating on the southern coast of the Caspian Sea (CS) is the main issue due to complex topography. Also, there are different types of climate in these areas. In this research, we used two reanalysis data such as ECMWF Reanalysis 5th Generation Description (ERA5) and National Centers for Environmental Prediction /National Center for Atmospheric Research (NCEP/NCAR) for verification of the numerical model. ERA5 is the latest version of ECMWF. The temporal resolution of ERA5 is hourly, and the NCEP/NCAR is every six hours. Some atmospheric parameters such as mean sea level pressure, geopotential height, relative humidity, wind speed and direction, sea surface temperature, etc. were selected and analyzed. Some different type of precipitation (rain and snow) was selected. The results showed that the NCEP/NCAR has more ability to demonstrate the intensity of the atmospheric system. The ERA5 is suitable for extract the value of parameters for specific point. Also, ERA5 is appropriate to analyze the snowfall events over CS (snow cover and snow depth). Sea surface temperature has the main role to generate instability over CS, especially when the cold air pass from the CS. Sea surface temperature of NCEP/NCAR product has low resolution near coast. However, both data were able to detect meteorological synoptic patterns that led to heavy rainfall over CS. However, due to the time lag, they are not suitable for forecast centers. The application of these two data is for research and verification of meteorological models. Finally, ERA5 has a better resolution, respect to NCEP/NCAR reanalysis data, but NCEP/NCAR data is available from 1948 and appropriate for long term research.

Keywords: synoptic patterns, heavy precipitation, reanalysis data, snow

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Authors: Auwal Garba, Rabiu Maijama’a, Abdullahi Muhammad Jalam

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Variability in climate has affected the agricultural production all over the globe. This concern has motivated important changes in the field of research during the last decade. Climate variability is believed to have declining effects towards rice production in Nigeria. This study examined climate variability and its impact on rice productivity in Dass Local Government Area, Bauchi State, by employing Linear Trend Model (LTM), analysis of variance (ANOVA) and regression analysis. Annual seasonal data of the climatic variables for temperature (min. and max), rainfall, and solar radiation from 1990 to 2015 were used. Results confirmed that 74.4% of the total variation in rice yield in the study area was explained by the changes in the independent variables. That is to say, temperature (minimum and maximum), rainfall, and solar radiation explained rice yield with 74.4% in the study area. Rising mean maximum temperature would lead to reduction in rice production while moderate increase in mean minimum temperature would be advantageous towards rice production, and the persistent rise in the mean maximum temperature, in the long run, will have more negatively affect rice production in the future. It is, therefore, important to promote agro-meteorological advisory services, which will be useful in farm planning and yield sustainability. Closer collaboration among the meteorologist and agricultural scientist is needed to increase the awareness about the existing database, crop weather models among others, with a view to reaping the full benefits of research on specific problems and sustainable yield management and also there should be a special initiative by the ADPs (State Agricultural Development Programme) towards promoting best agricultural practices that are resilient to climate variability in rice production and yield sustainability.

Keywords: climate variability, impact, productivity, rice

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Authors: Lingxia Li, Frédéric Schnell, Shuzhe Ding, Solène Le Douairon Lahaye

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Background: The risk of sudden cardiac arret/death (SCA/D) in athletes is controversial. There is a lack of meta-analyses assessing the sex differences in the risk of SCA/D in competitive athletes. Purpose: The aim of the present study was to evaluate sex differences in the incidence of SCA/D in competitive athletes using meta-analyses. Methods: The systematic review was registered in the PROSPERO database (registration ID: CRD42023432022) and was conducted according to the PRISMA guidelines. PubMed, Embase, Scopus, SPORT Discus and Cochrane Library were searched up to July 2023. To avoid systematic bias in data pooling, only studies with data for both sexes were included. Results: From the 18 included studies, 2028 cases of SCA/D were observed (males 1821 (89.79%), females 207 (10.21%)). The age ranges from the adolescents (<26 years) to the elderly (>45 years). The incidence in male athletes was 1.32/100,000 AY (95% CI: [0.90, 1.93]) and in females was 0.26/100,000 AY (95% CI: [0.16, 0.43]), the incidence rate ratio (IRR) was 6.43 (95% CI: [4.22, 9.79]). The subgroup synthesis showed a higher incidence in males than in females in both age groups <25 years and ≤35 years, the IRR was 5.86 (95% CI: [4.69, 7.32]) and 5.79 (95% CI: [4.73, 7.09]), respectively. When considering the events, the IRR was 6.73 (95%CI: [3.06, 14.78]) among studies involving both SCA/D events and 7.16 (95% CI: [4.93, 10.40]) among studies including only cases of SCD. The available clinical evidence showed that cardiac events were most frequently seen in long-distance running races (26, 35.1%), marathon (16, 21.6%) and soccer (10, 13.5%). Coronary artery disease (14, 18.9%), hypertrophic cardiomyopathy (8, 10.8%), and arrhythmogenic right ventricular cardiomyopathy (7, 9.5%) are the most common causes of SCA/D in competitive athletes. Conclusion: The meta-analysis provides evidence of sex differences in the incidence of SCA/D in competitive athletes. The incidence of SCA/D in male athletes was 6 to 7 times higher than in females. Identifying the reasons for this difference may have implications for targeted the prevention of fatal evets in athletes.

Keywords: incidence, sudden cardiac arrest, sudden cardiac death, sex difference, athletes

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Authors: Hadi Allafta, Christian Opp

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Soil erosion is a major concern in the Shatt Al-Arab basin owing to the steepness of its topography as well as the remarkable altitudinal deference between the upstream and downstream parts of the basin. Such conditions resulted in soil vulnerability to erosion; huge amounts of soil are annually transported, creating enormous implications such as land degradation, structure damage, biodiversity loss, productivity decline, etc. Thus, evaluation of soil erosion risk and its spatial distribution is crucial to build adatabase for efficient control measures. The present study used revised universal soil loss equation (RUSLE) model integrated with Geographic Information System (GIS) for depicting soil erosion hazard zones in the Shatt Al-Arab basin. The RUSLE model incorporated several parameters such as rainfall-runoff erosivity, soil erodibility, slope length and steepness, land cover and management, and conservation support practice for soil erosion zonation. High to medium soil loss of 100 to 20 ton perhectare per year represents around 25% of the basin area, while the areas of low soil loss of less than 20 ton per hectare per year occupied the rest of the total area. The high soil loss rates are linked to areas of high rainfall levels, loamy soil domination, elevated terrains/plateau margins with steep side slope, and high cultivation activities. The findings of the current study can be useful for managers and policy makers in the implementation of a suitable conservation program to reduce soil erosion or to recommend soil conservation acts if development projects are to be continued at regions of high soil erosion risk.

Keywords: geographic information system, revised universal soil loss equation, shatt Al-Arab basin, soil erosion

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Authors: Masoud Ghahvechi Pour

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Risk management is a systematic and regular process of identifying, analyzing and responding to risks throughout the project's life cycle in order to achieve the optimal level of elimination, reduction or control of risk. The purpose of project risk management is to increase the probability and effect of positive events and reduce the probability and effect of unpleasant events on the project. Risk management is one of the most fundamental parts of project management, so that unmanaged or untransmitted risks can be one of the primary factors of failure in a project. Effective risk management does not apply to risk regression, which is apparently the cheapest option of the activity. However, the main problem with this option is the economic sensitivity, because what is potentially profitable is by definition risky, and what does not pose a risk is economically interesting and does not bring tangible benefits. Therefore, in relation to the implemented project, effective risk management is finding a "middle ground" in its management, which includes, on the one hand, protection against risk from a negative direction by means of accurate identification and classification of risk, which leads to analysis And it becomes a comprehensive analysis. On the other hand, management using all mathematical and analytical tools should be based on checking the maximum benefits of these decisions. Detailed analysis, taking into account all aspects of the company, including stakeholder analysis, will allow us to add what will become tangible benefits for our project in the future to effective risk management. Identifying the risk of the project is based on the theory that which type of risk may affect the project, and also refers to specific parameters and estimating the probability of their occurrence in the project. These conditions can be divided into three groups: certainty, uncertainty, and risk, which in turn support three types of investment: risk preference, risk neutrality, specific risk deviation, and its measurement. The result of risk identification and project analysis is a list of events that indicate the cause and probability of an event, and a final assessment of its impact on the environment.

Keywords: risk, management, knowledge, risk management

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Authors: Ionel Zagan, Vasile Gheorghita Gaitan

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Minimizing the response time to asynchronous events in a real-time system is an important factor in increasing the speed of response and an interesting concept in designing equipment fast enough for the most demanding applications. The present article will present the results regarding the validation of the nMPRA (Multi Pipeline Register Architecture) architecture using the FPGA Virtex-7 circuit. The nMPRA concept is a hardware processor with the scheduler implemented at the processor level; this is done without affecting a possible bus communication, as is the case with the other CPU solutions. The implementation of static or dynamic scheduling operations in hardware and the improvement of handling interrupts and events by the real-time executive described in the present article represent a key solution for eliminating the overhead of the operating system functions. The nMPRA processor is capable of executing a preemptive scheduling, using various algorithms without a software scheduler. Therefore, we have also presented various scheduling methods and algorithms used in scheduling the real-time tasks.

Keywords: nMPRA architecture, pipeline processor, preemptive scheduling, real-time system

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Authors: Benghenia Hadj Abd El Kader

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Sleep apnea events as obstructive, central, mixed or hypopnea are characterized by frequent breathing cessations or reduction in upper airflow during sleep. An advanced method for analyzing the patterning of biomedical signals to recognize obstructive sleep apnea and hypopnea is presented. In the aim to extract characteristic parameters, which will be used for classifying the above stated (obstructive, central, mixed) sleep apnea and hypopnea, the proposed method is based first on the analysis of polysomnography signals such as electrocardiogram signal (ECG) and electromyogram (EMG), then classification of the (obstructive, central, mixed) sleep apnea and hypopnea. The analysis is carried out using the wavelet transform technique in order to extract characteristic parameters whereas classification is carried out by applying the SVM (support vector machine) technique. The obtained results show good recognition rates using characteristic parameters.

Keywords: obstructive, central, mixed, sleep apnea, hypopnea, ECG, EMG, wavelet transform, SVM classifier

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Authors: Oluwaseun K. Oyebode, Josiah A. Adeyemo

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Hydrological modelling plays a crucial role in the planning and management of water resources, most especially in water stressed regions where the need to effectively manage the available water resources is of critical importance. However, due to the complex, nonlinear and dynamic behaviour of hydro-climatic interactions, achieving reliable modelling of water resource systems and accurate projection of hydrological parameters are extremely challenging. Although a significant number of modelling techniques (process-based and data-driven) have been developed and adopted in that regard, the field of hydrological modelling is still considered as one that has sluggishly progressed over the past decades. This is majorly as a result of the identification of some degree of uncertainty in the methodologies and results of techniques adopted. In recent times, evolutionary computation (EC) techniques have been developed and introduced in response to the search for efficient and reliable means of providing accurate solutions to hydrological related problems. This paper presents a comprehensive review of the underlying principles, methodological needs and applications of a promising evolutionary computation modelling technique – genetic programming (GP). It examines the specific characteristics of the technique which makes it suitable to solving hydrological modelling problems. It discusses the opportunities inherent in the application of GP in water related-studies such as rainfall estimation, rainfall-runoff modelling, streamflow forecasting, sediment transport modelling, water quality modelling and groundwater modelling among others. Furthermore, the means by which such opportunities could be harnessed in the near future are discussed. In all, a case for total embracement of GP and its variants in hydrological modelling studies is made so as to put in place strategies that would translate into achieving meaningful progress as it relates to modelling of water resource systems, and also positively influence decision-making by relevant stakeholders.

Keywords: computational modelling, evolutionary algorithms, genetic programming, hydrological modelling

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Authors: Samuel Abraham Berhane, Lingbing Bu

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This paper presents the spatiotemporal variability of aerosols, clouds, and precipitation within the major cities in Eritrea and it investigates the relationship between aerosols, clouds, and precipitation concerning the presence of aerosols over the study region. In Eritrea, inadequate water supplies will have both direct and indirect adverse impacts on sustainable development in areas such as health, agriculture, energy, communication, and transport. Besides, there exists a gap in the knowledge on suitable and potential areas for cloud seeding. Further, the inadequate understanding of aerosol-cloud-precipitation (ACP) interactions limits the success of weather modification aimed at improving freshwater sources, storage, and recycling. Spatiotemporal variability of aerosols, clouds, and precipitation involve spatial and time series analysis based on trend and anomaly analysis. To find the relationship between aerosols and clouds, a correlation coefficient is used. The spatiotemporal analysis showed larger variations of aerosols within the last two decades, especially in Assab, indicating that aerosol optical depth (AOD) has increased over the surrounding Red Sea region. Rainfall was significantly low but AOD was significantly high during the 2011 monsoon season. Precipitation was high during 2007 over most parts of Eritrea. The correlation coefficient between AOD and rainfall was negative over Asmara and Nakfa. Cloud effective radius (CER) and cloud optical thickness (COT) exhibited a negative correlation with AOD over Nakfa within the June–July–August (JJA) season. The hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model that is used to find the path and origin of the air mass of the study region showed that the majority of aerosols made their way to the study region via the westerly and the southwesterly winds.

Keywords: aerosol-cloud-precipitation, aerosol optical depth, cloud effective radius, cloud optical thickness, HYSPLIT

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Authors: Kittipon Chittanukul, Chayut Bureethan, Chutimon Piromyaporn

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In Thailand, the natural gas pipeline system requires the preparation of an Environmental Impact Assessment (EIA) report for approval by the relevant agency, the Office of Natural Resources and Environmental Policy and Planning (ONEP), in the pre-construction stage. As of December 2022, PTT has a lot of gas pipeline system spanning around the country. Our experience has shown that the EIA is a significant part of the project plan. In 2011, There was a catastrophic flood in multiple areas of Thailand. It destroyed lives and properties. This event is still in Thai people’s mind. Furthermore, rainfall has been increasing for three consecutive years (2020-2022). Moreover, municipalities are situated in low land river basin and tropical rainfall zone. So many areas still suffer from flooding. Especially in 2022, there will be a 60% increase in water demand compared to the previous year. Therefore, all activities will take into account the quality of the receiving water. The above information emphasizes water and wastewater management are significant in EIA report. PTT has accumulated a large number of lessons learned in water and wastewater management. Our pipeline system execution is composed of EIA stage, construction stage, and operation and maintenance phase. We provide practical Information on water and wastewater management to enhance the EIA process for the pipeline system. The examples of lessons learned in water and wastewater management include techniques to address water and wastewater impact throughout the overall pipelines systems, mitigation measures and monitoring results of these measures. This practical information will alleviate the anxiety of the ONEP committee when approving the EIA report and will build trust among stakeholders in the vicinity of the gas pipeline system area.

Keywords: environmental impact assessment, gas pipeline system, low land basin, high risk flooding area, mitigation measure

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Authors: Tracy Smith-Carrier

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Burgeoning research extols the benefits of innovative experiential learning activities to increase participants’ engagement, enhance their individual learning, and bridge the gap between theory and practice. This presentation discusses findings from a multiple case study on poverty simulation events conducted with two samples: undergraduate students and community participants. After exploring the nascent research on the benefits and limitations of poverty simulation activities, the study explores whether participating in a poverty simulation resulted in changes to participants’ beliefs about the causes and effects of poverty, as well as shifts in their attitudes and actions toward people experiencing poverty. For the purposes of triangulation, quantitative and qualitative data from a variety of sources were analyzed: participant feedback surveys, qualitative responses, and pre, post, and follow-up questionnaires. Findings show statistically significant results (p<.05) from both samples on cumulative scores of the modified Attitudes Toward Poverty Scale, indicating an improvement in participants’ attitudes toward poverty. Although generally positive about their experiences, participating in the simulation did not appear to have prompted participants to take specific actions to reduce poverty. Conclusions drawn from the research study suggest that poverty simulation planners should be wary of adopting scenarios that emphasize, or fail to adequately contextualize, behaviours or responses that might perpetuate individual explanations of poverty. Moreover, organizers must carefully consider how to ensure participants in their audience currently experiencing low-income do not become emotionally distressed, triggered or further marginalized in the process. While overall participants were positive about their experiences in the simulation, the events did not appear to have prompted them to action. Moving beyond the goal of increasing participants’ understandings of poverty, interventions that foster greater engagement in poverty issues over the long-term are necessary.

Keywords: empathy, experiential learning, poverty awareness, poverty simulation

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Authors: Ali Raza, Shafiq Ur Rehman Khan, Raja Sher Afgun Usmani, Asif Raza, Basit Umair

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Detection of Fake news and missing information is gaining popularity, especially after the advancement in social media and online news platforms. Social media platforms are the main and speediest source of fake news propagation, whereas online news websites contribute to fake news dissipation. In this study, we propose a framework to detect fake news using the temporal features of text and consider user feedback to identify whether the news is fake or not. In recent studies, the temporal features in text documents gain valuable consideration from Natural Language Processing and user feedback and only try to classify the textual data as fake or true. This research article indicates the impact of recurring and non-recurring events on fake and true news. We use two models BERT and Bi-LSTM to investigate, and it is concluded from BERT we get better results and 70% of true news are recurring and rest of 30% are non-recurring.

Keywords: natural language processing, fake news detection, machine learning, Bi-LSTM

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