Search results for: co-citation networks; keyword co-occurrence network

Authors: Rodrigo T. Sepulveda-Hirose, Ana B. Carrera-Aguilar, Francisco Andree Ramirez-Casas, Alondra Orozco-Gomez, Miguel Angel Sanchez-Caro, Carlos Herrera-Ventosa

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High concentrations of particulate matter in the atmosphere pose a threat to human health, especially over areas with high concentrations of population; however, field air pollution monitoring is expensive and time-consuming. In order to achieve reduced costs and global coverage of the whole urban area, remote sensing can be used. This study evaluates PM2.5 concentrations, over the Mexico City´s metropolitan area, are estimated using atmospheric reflectance from LANDSAT 8, satellite imagery and historical PM2.5 measurements of the Automatic Environmental Monitoring Network of Mexico City (RAMA). Through the processing of the available satellite images, a preliminary model was generated to evaluate the optimal bands for the generation of the final model for Mexico City. Work on the final model continues with the results of the preliminary model. It was found that infrared bands have helped to model in other cities, but the effectiveness that these bands could provide for the geographic and climatic conditions of Mexico City is still being evaluated.

Keywords: air pollution modeling, Landsat 8, PM2.5, remote sensing

Procedia PDF Downloads 188

Authors: Ahmad Alsolami, Darren Mundy, Manuel Hernandez-Perez

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Social media networks, such as Twitter, offer the perfect opportunity to either positively or negatively affect political attitudes on large audiences. The existence of influential users who have developed a reputation for their knowledge and experience of specific topics is a major factor contributing to this impact. Therefore, knowledge of the mechanisms to identify influential users on social media is vital for understanding their effect on their audience. The concept of the influential user is related to the concept of opinion leaders' to indicate that ideas first flow from mass media to opinion leaders and then to the rest of the population. Hence, the objective of this research was to provide reliable and accurate structural mechanisms to identify influential users, which could be applied to different platforms, places, and subjects. Twitter was selected as the platform of interest, and Saudi Arabia as the context for the investigation. These were selected because Saudi Arabia has a large number of Twitter users, some of whom are considerably active in setting agendas and disseminating ideas. The study considered the scientific methods that have been used to identify public opinion leaders before, utilizing metrics software on Twitter. The key findings propose multiple novel metrics to compare Twitter influencers, including the number of followers, social authority and the use of political hashtags, and four secondary filtering measures. Thus, using ratio and percentage calculations to classify the most influential users, Twitter accounts were filtered, analyzed and included. The structured approach is used as a mechanism to explore the top ten influencers on Twitter from the political domain in Saudi Arabia.

Keywords: Twitter, influencers, structured mechanism, Saudi Arabia

Procedia PDF Downloads 111

Authors: Arnab Mondal, Sanjeev Kumar Sharma, Ranjit Kumar Upadhyay

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We study the spatiotemporal dynamics of a neuronal cable. The processes of one- dimensional (1D) and 2D diffusion are considered for a single variable, which is the membrane voltage, i.e., membrane voltage diffusively interacts for spatiotemporal pattern formalism. The recovery and other variables interact through the membrane voltage. A 3D Leech-Heart (LH) model is introduced to investigate the nonlinear responses of an excitable neuronal cable. The deterministic LH model shows different types of firing properties. We explore the parameter space of the uncoupled LH model and based on the bifurcation diagram, considering v_k2_ashift as a bifurcation parameter, we analyze the 1D diffusion dynamics in three regimes: bursting, regular spiking, and a quiescent state. Depending on parameters, it is shown that the diffusive system may generate regular and irregular bursting or spiking behavior. Further, it is explored a 2D diffusion acting on the membrane voltage, where different types of patterns can be observed. The results show that the LH neurons with different firing characteristics depending on the control parameters participate in a collective behavior of an information processing system that depends on the overall network.

Keywords: bifurcation, pattern formation, spatio-temporal dynamics, stability analysis

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Authors: M. Macchiaroli, L. Dolores, V. Pellecchia

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With the recent Resolution n. 580/2019/R/idr, the Italian Regulatory Authority for Energy, Networks, and Environment (ARERA) for the Urban Water Management has introduced, for water managements characterized by persistent critical issues regarding the planning and organization of the service and the implementation of the necessary interventions for the improvement of infrastructures and management quality, a new mechanism for determining tariffs: the regulatory scheme of Convergence. The aim of this regulatory scheme is the overcoming of the Water Service Divided in order to improve the stability of the local institutional structures, technical quality, contractual quality, as well as in order to guarantee transparency elements for Users of the Service. Convergence scheme presupposes the identification of the cost items to be considered in the tariff in parametric terms, distinguishing three possible cases according to the type of historical data available to the Manager. The study, in particular, focuses on operations that have neither data on tariff revenues nor data on operating costs. In this case, the Manager's Constraint on Revenues (VRG) is estimated on the basis of a reference benchmark and becomes the starting point for defining the structure of the tariff classes, in compliance with the TICSI provisions (Integrated Text for tariff classes, ARERA's Resolution n. 665/2017/R/idr). The proposed model implements the recent studies on optimization models for the definition of tariff classes in compliance with the constraints dictated by TICSI in the application of the Convergence mechanism, proposing itself as a support tool for the Managers and the local water regulatory Authority in the decision-making process.

Keywords: decision-making process, economic evaluation of projects, optimizing tools, urban water management, water tariff

Procedia PDF Downloads 113

Authors: Yacine Babou, Nitesh Ranjan, Branimir Radisavljevic , Martin Seeger, Daniel Over, Torsten Votteler, Bernardo Galletti, Paulo Cristini

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In the frame of replacement of Sulfur hexafluoride (SF6) gas as insulating and switching medium, diverse alternative gases, offering acceptable Global Warming Potential and fulfilling requirements in terms of heat dissipation, insulation and arc quenching performances are currently investigated for High Voltage Circuit Breaker applications. Among the potential gases, CO₂ seems a promising candidate for replacing SF6, because on one hand it is environmentally friendly, harmless, non-toxic, non-corrosive, non-flammable and on the other hand previous studies have demonstrated its fair interruption capabilities. The present study aims at investigating the performance of CO₂ for the thermal interruption in high voltage self-blast circuit breakers. In particular, the correlation between thermal interruption performance and arc voltage is considered and the effect of the arc-network interaction on the performance is rigorously analyzed. For the considered designs, the thermal interruption was evaluated by varying the slope at current zero (i.e., di/dt) for which the breaker could interrupt. Besides, the characteristics of the post-arc current are examined in detail for various rated voltages and currents. The outcome of these experimental investigations will be reported and analyzed.

Keywords: current zero measurement, high voltage circuit breaker, thermal arc discharge, thermal interruption

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Authors: George Mahalu

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The Chua diode has been configured over time in various ways, using electronic structures like as operational amplifiers (OAs) or devices with gas or semiconductors. When discussing the use of semiconductor devices, tunnel diodes (Esaki diodes) are most often considered, and more recently, transistorized configurations such as lambda diodes. The paper-work proposed here uses in the modeling a lambda diode type configuration consisting of two Junction Field Effect Transistors (JFET). The original scheme is created in the MULTISIM electronic simulation environment and is analyzed in order to identify the conditions for the appearance of evolutionary unpredictability specific to nonlinear dynamic systems with chaos-induced behavior. The chaotic deterministic oscillator is one autonomous type, a fact that places it in the class of Chua’s type oscillators, the only significant and most important difference being the presence of a nonlinear device like the one mentioned structure above. The chaotic behavior is identified both by means of strange attractor-type trajectories and visible during the simulation and by highlighting the hypersensitivity of the system to small variations of one of the input parameters. The results obtained through simulation and the conclusions drawn are useful in the further research of ways to implement such constructive electronic solutions in theoretical and practical applications related to modern small signal amplification structures, to systems for encoding and decoding messages through various modern ways of communication, as well as new structures that can be imagined both in modern neural networks and in those for the physical implementation of some requirements imposed by current research with the aim of obtaining practically usable solutions in quantum computing and quantum computers.

Keywords: chaos, lambda diode, strange attractor, nonlinear system

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Authors: Frank C. Amaechi, Adeyinka A. Aderinto, Usman A. Ojedokun, Oludayo Tade

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Illicit trading in new naira notes has become a common practice in most communities in Nigeria despite the Central Bank Act’s in 2007 proscription of all forms of naira abuse. This study investigated the socio-economic factors sustaining illicit trading in new naira notes in Ibadan metropolis. The study was exploratory and cross-sectional in design. Neutralization theory was adopted as theoretical framework. Data were generated through the combination of in-depth interview and key informant interview methods. The purposive sampling technique was utilised to select five illicit traders of new naira notes, 32 patrons of the trade and six bank officials. Findings revealed that illicit trading in Nigeria’s national currency is flourishing because of the frequent demand for new naira notes that are not readily available in Nigerian banks. Also, the norm of cash spraying at social events is sustaining the illicit markets for new naira notes in Ibadan metropolis. In addition, a chain of network, comprising three principal actors, is behind the illegal business. A strict enforcement of the law banning cash spraying is advocated as a means of arresting this phenomenon.

Keywords: illicit trading, naira notes, national currency, Nigeria

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Authors: Farah Kanani

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Blue Tide Environmental is a company focused on developing a network of used motor oil recycling facilities across the U.S. They initiated the redesign of its recycling plant in Texas, and aimed to establish an updated carbon footprint of re-refined used motor oils compared to an equivalent product derived from virgin stock that is not re-refined. The aim was to quantify emissions savings of a circular alternative to conventional end-of-life combustion of used motor oil (UMO). To do so, they mandated an ISO-compliant carbon footprint, utilizing complex models requiring geographical and temporal accuracy to accommodate the U.S. refinery market. The quantification of linear and circular flows, proxies for fuel substitution and system expansion for multi-product outputs were all critical methodological choices and were tested through sensitivity analyses. The re-refined system consisted of continuous recycling of UMO and thus, end-of-life is considered non-existent. The unique perspective to this topic will be from a life cycle i.e. holistic one and essentially demonstrate using this example of how a cradle-to-cradle model can be used to quantify a comparative carbon footprint. The intended audience is lubricant manufacturers as the consumers, motor oil industry professionals and other industry members interested in performing a cradle-to-cradle modeling.

Keywords: circularity, used motor oil, re-refining, systems expansion

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Authors: Peter J. H. Carnell, Panayiotis Theophanous

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Natural gas due to its cleaner combustion characteristics is expected to be the most widely used fuel in the move towards less polluting and renewable energy sources. Thus, the developed world is supplied by a complex network of gas pipelines and natural gas is becoming a major source of fuel. Natural gas delivered directly from the well will differ in composition from gas derived from LNG or produced by anaerobic digestion processes. Each will also have specific contaminants and properties although gas from all sources is likely to enter the distribution system and be blended to provide the desired characteristics such as Higher Heating Value and Wobbe No. The absence of a standard gas composition poses problems when the gas is used as a chemical feedstock, in specialised furnaces or on gas turbines. The chemical industry has suffered in the past as a result of variable gas composition. Transition metal catalysts used in ammonia, methanol and hydrogen plants were easily poisoned by sulphur, chlorides and mercury reducing both activity and catalyst expected lives from years to months. These plants now concentrate on purification and conditioning of the natural gas feed using fixed bed technologies, allowing them to run for several years and having transformed their operations. Similar technologies can be applied to the power industry reducing maintenance requirements and extending the operating life of gas turbines.

Keywords: gas composition, gas conditioning, gas turbines, power generation, purification

Procedia PDF Downloads 279

Authors: Zareen Khan

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Islamic Banking has experienced high growth in Pakistan in recent years and has successfully survived the economic downturn of 2009-2011. Despite the increase in branch network and expansion of services, it is unclear if Islamic banks are truly following the theory and practical application of Shariah Law. This paper explores the theological basis of Islamic finance and examines the discrepancies between the theory and practice of Islamic banking using Pakistan as a case study. It discusses areas where Islamic banks lack proper Shariah compliance and analyzes the financial weaknesses of Islamic banks in terms of the services offered. Furthermore, the paper offers plausible explanations for the clientele of Islamic banks. The case study has three major findings. Firstly, most of the employees of Islamic banks come from conventional banking backgrounds and the banks have to invest in additional trainings to specialize employees in Islamic Banking. Secondly despite the efforts of State Bank of Pakistan, there is a lack of accounting and auditing standards tailored for Islamic Banking. Thirdly, majority of the clients of Islamic banks in Pakistan are accustomed to conventional banking causing the bankers to “speak the conventional banking language.” Combined, these three factors can create gaps in the practical application of Islamic finance in Islamic banks in Pakistan.

Keywords: islamic finance, comparing theory with practice, islamic banking, Pakistan

Procedia PDF Downloads 455

Authors: Godwin A. Otogo, Sansanee Wangvoralak, Graham J. Pierce, Lee C. Hastie, Beth Scott

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The squid Loligo forbesii is suspected to be an important species in marine food webs, as it can strongly impact its prey and be impacted upon by predation, competition, fishing and/or climate variability. To quantify these impacts in the food web, the measurement of its trophic position and ecological role within well-studied ecosystems is essential. An Ecopath model was balanced and run for the Moray Firth ecosystem and was used to investigate the significance of this squid’s trophic roles. The network analysis routine included in Ecopath with Ecosim (EwE) was used to estimate trophic interaction, system indicators (health condition and developmental stage) and food web features. Results indicated that within the Moray Firth squid occupy a top trophic position in the food web and also a major prey item for many other species. Results from Omnivory Index (OI) showed that squid is a generalized feeder transferring energy across wide trophic levels and is more important as a predator than that as a prey in the Moray Firth ecosystem. The results highlight the importance of taking squid into account in the management of Europe’s living marine resources.

Keywords: Squid, Loligo forbesii, Ecopath, Moray Firth, Trophic level

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Authors: Jacob Green, Cecilia Cabrera, Maximilian Jakobs, Andrea Dimitracopoulos, Mark van der Wilk, Ryan Greenhalgh

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Predicting drug properties is key in drug discovery to enable de-risking of assets before expensive clinical trials and to find highly active compounds faster. Interest from the machine learning community has led to the release of a variety of benchmark datasets and proposed methods. However, it remains unclear for practitioners which method or approach is most suitable, as different papers benchmark on different datasets and methods, leading to varying conclusions that are not easily compared. Our large-scale empirical study links together numerous earlier works on different datasets and methods, thus offering a comprehensive overview of the existing property classes, datasets, and their interactions with different methods. We emphasise the importance of uncertainty quantification and the time and, therefore, cost of applying these methods in the drug development decision-making cycle. To the best of the author's knowledge, it has been observed that the optimal approach varies depending on the dataset and that engineered features with classical machine learning methods often outperform deep learning. Specifically, QSAR datasets are typically best analysed with classical methods such as Gaussian Processes, while ADMET datasets are sometimes better described by Trees or deep learning methods such as Graph Neural Networks or language models. Our work highlights that practitioners do not yet have a straightforward, black-box procedure to rely on and sets a precedent for creating practitioner-relevant benchmarks. Deep learning approaches must be proven on these benchmarks to become the practical method of choice in drug property prediction.

Keywords: activity (QSAR), ADMET, classical methods, drug property prediction, empirical study, machine learning

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Authors: Bismina Akbar, Smitha M. V.

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Flooding is a global phenomenon that causes widespread devastation, economic damage, and loss of human lives. In the past twenty years, the number of reported flood events has increased significantly. Millions of people around the globe are at risk of flooding from coastal, dam breaks, groundwater, and urban surface water and wastewater sources. Climate change is one of the important causes for them since it affects, directly and indirectly, the river network. Although the contribution of climate change is undeniable, human contributions are there to increase the frequency of floods. There are different types of floods, such as Flash floods, Coastal floods, Urban floods, River (or fluvial) floods, and Ponding (or pluvial flooding). This study focuses on formulating mitigation strategies for urban flood risk reduction through analysis of different best practice case studies, including China, Japan, Indonesia, and Brazil. The mitigation measures suggest that apart from the structural and non-structural measures, environmental considerations like blue-green solutions are beneficial for flood risk reduction. And also, Risk-Informed Master plans are essential nowadays to take risk-based decision processes that enable more sustainability and resilience.

Keywords: hazard, mitigation, risk reduction, urban flood

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Authors: S. Thaiudom, W. Toommuangpak

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Yoghurt ice cream (YIC) containing prebiotics and probiotics seems to be much more recognized among consumers who concern for their health. Not only can it be a benefit on consumers’ health but also its taste and freshness provide people easily accept. However, the survival of such probiotic especially Bifidobacterium longum, found in human gastrointestinal tract and to be benefit to human gut, was still needed to study in the severe condition as whipping and freezing in ice cream process. Low and full-fat yoghurt ice cream containing 2 and 10% (w/w) fat content (LYIC and FYIC), respectively was produced by mixing 20% yoghurt containing B. longum into milk ice cream mix. Fructo-oligosaccharides (FOS) or galacto-oligosaccharides (GOS) at 0, 1, and 2% (w/w) were separately used as prebiotic in order to improve the survival of B. longum. Survival of this bacteria as a function of ice cream storage time and ice cream properties were investigated. The results showed that prebiotic; especially FOS could improve viable count of B. longum. The more concentration of prebiotic used, the more is the survival of B. Longum. These prebiotics could prolong the survival of B. longum up to 60 days, and the amount of survival number was still in the recommended level (106 cfu per gram). Fat content and prebiotic did not significantly affect the total acidity and the overrun of all samples, but an increase of fat content significantly increased the fat particle size which might be because of partial coalescence found in FYIC rather than in LYIC. However, addition of GOS or FOS could reduce the fat particle size, especially in FYIC. GOS seemed to reduce the hardness of YIC rather than FOS. High fat content (10% fat) significantly influenced on lowering the melting rate of YIC better than 2% fat content due to the 3-dimension networks of fat partial coalescence theoretically occurring more in FYIC than in LYIC. However, FOS seemed to retard the melting rate of ice cream better than GOS. In conclusion, GOS and FOS in YIC with different fat content can enhance the survival of B. longum and affect physical and chemical properties of such yoghurt ice cream.

Keywords: Bifidobacterium longum, prebiotic, survival, yoghurt ice cream

Procedia PDF Downloads 156

Authors: P. Abhishesh, B. S. Ryuh, Y. S. Oh, H. J. Moon, R. Akanksha

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This paper discusses about the conceptual design and development of the control system software using Programmable logic controller (PLC) for autonomous driving and agricultural operations of Multipurpose Agricultural Robot Platform (MARP). Based on given initial conditions by field analysis and desired agricultural operations, the structural design development of MARP is done using modelling and analysis tool. PLC, being robust and easy to use, has been used to design the autonomous control system of robot platform for desired parameters. The robot is capable of performing autonomous driving and three automatic agricultural operations, viz. hilling, mulching, and sowing of seeds in the respective order. The input received from various sensors on the field is later transmitted to the controller via ZigBee network to make the changes in the control program to get desired field output. The research is conducted to provide assistance to farmers by reducing labor hours for agricultural activities by implementing automation. This study will provide an alternative to the existing systems with machineries attached behind tractors and rigorous manual operations on agricultural field at effective cost.

Keywords: agricultural operations, autonomous driving, MARP, PLC

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Authors: Swati Kishor Zode, Rahul Ambekar

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Data mining is the extraction of fascinating examples on the other hand information from enormous measure of information and choice is made as indicated by the applicable information extracted. As of late, with the dangerous advancement in internet, stockpiling of information and handling procedures, privacy preservation has been one of the major (higher) concerns in data mining. Various techniques and methods have been produced for protection saving data mining. In the situation of Clinical Decision Support System, the choice is to be made on the premise of the data separated from the remote servers by means of Internet to diagnose the patient. In this paper, the fundamental thought is to build the precision of Decision Support System for multiple diseases for different maladies and in addition protect persistent information while correspondence between Clinician side (Client side) also, the Server side. A privacy preserving protocol for clinical decision support network is proposed so that patients information dependably stay scrambled amid diagnose prepare by looking after the accuracy. To enhance the precision of Decision Support System for various malady C5.0 classifiers and to save security, a Homomorphism encryption algorithm Paillier cryptosystem is being utilized.

Keywords: classification, homomorphic encryption, clinical decision support, privacy

Procedia PDF Downloads 327

Authors: Soheila Sadeghi

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Accurate forecasting of project performance metrics is crucial for successfully managing and delivering urban road reconstruction projects. Traditional methods often rely on static baseline plans and fail to consider the dynamic nature of project progress and external factors. This research proposes a machine learning-based approach to forecast project performance metrics, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category in an urban road reconstruction project. The proposed model utilizes time series forecasting techniques, including Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance based on historical data and project progress. The model also incorporates external factors, such as weather patterns and resource availability, as features to enhance the accuracy of forecasts. By applying the predictive power of machine learning, the performance forecasting model enables proactive identification of potential deviations from the baseline plan, which allows project managers to take timely corrective actions. The research aims to validate the effectiveness of the proposed approach using a case study of an urban road reconstruction project, comparing the model's forecasts with actual project performance data. The findings of this research contribute to the advancement of project management practices in the construction industry, offering a data-driven solution for improving project performance monitoring and control.

Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, earned value management

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Authors: Sidi Mohamed Mesli, Mohamed Habchi, Mohamed Kotbi, Rafik Benallal, Abdelali Derouiche

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Fluoride glasses with a nominal composition of BaMnMF7 (M = FeV assuming isomorphous replacement) have been structurally modelled through the simultaneous simulation of their neutron diffraction patterns by a reverse Monte Carlo (RMC) model and by a Rietveld for disordered materials (RDM) method. Model is consistent with an expected network of interconnected [MF6] polyhedra. The RMC results are accompanied by artificial satellite peaks. To remedy this problem, we use an extension of the RMC algorithm, which introduces an energy penalty term in acceptance criteria. This method is called the Hybrid Reverse Monte Carlo (HRMC) method. The idea of this paper is to apply the (HRMC) method to the title glasses, in order to make a study of the phenomenon nature of order and disorder by displaying and discussing the partial pair distribution functions (PDFs) g(r). We suggest that this method can be used to describe average correlations between components of fluoride glass or similar system.

Keywords: fluoride glasses, RMC simulation, neutron scattering, hybrid RMC simulation, Lennard-Jones potential, partial pair distribution functions

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Authors: Prakash Thapa, Gye Choon Park, Sung Gi Kwon, Jin Lee

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The generation of electric power from a proton exchange membrane (PEM) fuel cell is influenced by temperature, pressure, humidity, flow rate of reactant gaseous and partial flooding of membrane electrode assembly (MEA). Among these factors, temperature and cathode flooding are the most affecting parameters on the performance of fuel cell. This paper describes the detail design and effect of these parameters on PEM fuel cell. Performance of all parameters was monitored, analyzed and controlled by using 5KWatt PEM fuel cell. In the real-time data communication for remote monitoring and control of PEM fuel cell, a normalized least mean square algorithm in cognitive radio environment is used. By the use of this method, probability of energy signal detection will be maximum which solved the frequency shortage problem. So the monitoring system hanging out and slow speed problem will be solved. Also from the control unit, all parameters are controlled as per the system requirement. As a result, PEM fuel cell generates maximum electricity with better performance.

Keywords: proton exchange membrane (PEM) fuel cell, pressure, temperature and humidity sensor (PTH), efficiency curve, cognitive radio network (CRN)

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Authors: Mohammad Obeidat, Ayman Mansour

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In this paper a unique issue rising from feedback control of Atrial Fibrillation monitoring system with embedded communication channels has been investigated. One of the important factors to measure the performance of the feedback control closed loop system is disturbance and noise attenuation factor. It is important that the feedback system can attenuate such disturbances on the atrial fibrillation heart rate signals. Communication channels depend on network traffic conditions and deliver different throughput, implying that the sampling intervals may change. Since signal estimation is updated on the arrival of new data, its dynamics actually change with the sampling interval. Consequently, interaction among sampling, signal estimation, and the controller will introduce new issues in remotely controlled Atrial Fibrillation system. This paper treats a remotely controlled atrial fibrillation system with one communication channel which connects between the heart rate and rhythm measurements to the remote controller. Typical and optimal signal estimation schemes is represented by a signal averaging filter with its time constant derived from the step size of the signal estimation algorithm.

Keywords: atrial fibrillation, communication channels, closed loop, estimation

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Authors: Armana Huq

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Railway networks have a significant role in the economy of any country. Similar to other transportation modes, many lives suffer from fatalities or injuries caused by accidents related to the railway. Railway accidents are not as common as roadway accidents yet they are more devastating and damaging than other roadway accidents. Despite that, issues related to railway accidents are not taken into consideration with significant attention as a major threat because of their less frequency compared to other accident categories perhaps. However, the Federal Railroad Administration reported nearly twelve thousand train accidents related to the railroad in the year 2014, resulting in more than eight hundred fatalities and thousands of injuries in the United States alone of which nearly one third fatalities resulted from railway crossing accidents. From an analysis of railway accident data of six years (2005-2010), it has been revealed that 344 numbers of the collision were occurred resulting 200 people dead and 443 people injured in Bangladesh. This paper includes a comprehensive overview of the railway safety situation in Bangladesh from 1998 to 2015. Each year on average, eight fatalities are reported in at-grade level crossings due to railway accidents in Bangladesh. In this paper, the number of railway accidents that occurred in Bangladesh has been presented and a fatality rate of 58.62% has been estimated as the percentage of total at-grade railway level crossing accidents. For this study, analysis of railway accidents in Bangladesh for the period 1998 to 2015 was obtained from the police reported accident database using MAAP (Microcomputer Accident Analysis Package). Investigation of the major contributing factors to the railway accidents has been performed using the Multinomial Logit model. Furthermore, hotspot analysis has been conducted using ArcGIS. Eventually, some suggestions have been provided to mitigate those accidents.

Keywords: safety, human factors, multinomial logit model, railway

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Authors: Lakrim Abderrazak, Tahri Driss

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This paper presents a new behavioural electrothermal model of power Silicon Carbide (SiC) MOSFET under SPICE. This model is based on the MOS model level 1 of SPICE, in which phenomena such as Drain Leakage Current IDSS, On-State Resistance RDSon, gate Threshold voltage VGSth, the transconductance (gfs), I-V Characteristics Body diode, temperature-dependent and self-heating are included and represented using behavioural blocks ABM (Analog Behavioural Models) of Spice library. This ultimately makes this model flexible and easily can be integrated into the various Spice -based simulation softwares. The internal junction temperature of the component is calculated on the basis of the thermal model through the electric power dissipated inside and its thermal impedance in the form of the localized Foster canonical network. The model parameters are extracted from manufacturers' data (curves data sheets) using polynomial interpolation with the method of simulated annealing (S A) and weighted least squares (WLS). This model takes into account the various important phenomena within transistor. The effectiveness of the presented model has been verified by Spice simulation results and as well as by data measurement for SiC MOS transistor C2M0025120D CREE (1200V, 90A).

Keywords: SiC power MOSFET, DC electro-thermal model, ABM Spice library, SPICE modelling, behavioural model, C2M0025120D CREE.

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Authors: Didier Birimwiragi Namogo

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The Kivu Lake Basin is located in the Western Branch of the East African Rift. In this basin is located a multitude of active faults, on which earthquakes occur regularly. The most recent earthquakes date from 2008, 2015, 2016, 2017 and 2019. The cities of Bukabu and Goma in DR Congo and Giseyi in Rwanda are the most impacted by this intense seismic activity in the region. The magnitude of the strongest earthquakes in the region is 6.1. The 2008 earthquake was particularly destructive, killing several people in DR Congo and Rwanda. This work aims to complete the distribution of seismicity in the region, deduce areas of weakness and establish a hazard map that can assist in seismic risk management. Using the local seismic network of the Goma Volcano Observatory, the earthquakes were relocated, and their focus mechanism was studied. The results show that most of these earthquakes occur on active faults described by Villeneuve in 1938. The alignment of the earthquakes shows a pace that follows directly the directions of the faults described by this author. The study of the focus mechanism of these earthquakes, also shows that these are in particular normal faults whose stresses show an extensive activity. Such study can be used for the establishment of seismic risk management tools.

Keywords: earthquakes, hazard map, faults, focus mechanism

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Authors: Marc Solé, Francesc Giné, Magda Valls, Nina Bijedic

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What people say on social media has turned into a rich source of information to understand social behavior. Specifically, the growing use of Twitter social media for political communication has arisen high opportunities to know the opinion of large numbers of politically active individuals in real time and predict the global political tendencies of a specific country. It has led to an increasing body of research on this topic. The majority of these studies have been focused on polarized political contexts characterized by only two alternatives. Unlike them, this paper tackles the challenge of forecasting Spanish political trends, characterized by multiple political parties, by means of analyzing the Twitters Users political tendency. According to this, a new strategy, named Tweets Analysis Strategy (TAS), is proposed. This is based on analyzing the users tweets by means of discovering its sentiment (positive, negative or neutral) and classifying them according to the political party they support. From this individual political tendency, the global political prediction for each political party is calculated. In order to do this, two different strategies for analyzing the sentiment analysis are proposed: one is based on Positive and Negative words Matching (PNM) and the second one is based on a Neural Networks Strategy (NNS). The complete TAS strategy has been performed in a Big-Data environment. The experimental results presented in this paper reveal that NNS strategy performs much better than PNM strategy to analyze the tweet sentiment. In addition, this research analyzes the viability of the TAS strategy to obtain the global trend in a political context make up by multiple parties with an error lower than 23%.

Keywords: political tendency, prediction, sentiment analysis, Twitter

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Authors: Raied Khayou

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The Hawza Al-'Ilmiyya is a network of religious seminaries in the Shia branch of Islam. This research mainly focuses on the oldest school located in Najaf, Iraq, because its core curriculum and main characteristics have been unchanged since the fourth century of Islam. Relying on a thorough literature review of Arabic and English publications, and interviews with current and previous students of the seminary, the current research outlines the factors proving how this seminary was crucial in keeping the Shia religious identity intact despite sometimes gruesome attempts of interference and persecution. There are several factors that helped the seminary to preserve its central importance. First, rooted in their theology, Shia Muslims believe that the Hawza Al-’Ilmiyya and its graduates carry a sacred authority. Secondly, the financial independence of the Seminary helped to keep it intact from any governmental or political meddling. Third, its unique teaching method, its matchless openness for new students, and its flexible curriculum made it attractive for many students who were interested in learning more about Shia theology and jurisprudence. The Hawza Al-‘Ilmiyya has the exclusive right to train clerics who hold the religious authority of Shia Islamic jurisprudence, and the seminary’s success in staying independent throughout history kept Shia Islamic theology independent, as well.

Keywords: Hawza Al'Ilmiyya, religious seminary, Shia Muslim education, Islamic jurisprudence

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Authors: Lijuan Zhou, Mengqi Wu, Changyong Niu

Abstract:

Attributed graph clustering can utilize the graph topology and node attributes to uncover hidden community structures and patterns in complex networks, aiding in the understanding and analysis of complex systems. Utilizing contrastive learning for attributed graph clustering can effectively exploit meaningful implicit relationships between data. However, existing attributed graph clustering methods based on contrastive learning suffer from the following drawbacks: 1) Complex data augmentation increases computational cost, and inappropriate data augmentation may lead to semantic drift. 2) The selection of positive and negative samples neglects the intrinsic cluster structure learned from graph topology and node attributes. Therefore, this paper proposes a method called self-supervised Attributed Graph Clustering with Dual Contrastive Loss constraints (AGC-DCL). Firstly, Siamese Multilayer Perceptron (MLP) encoders are employed to generate two views separately to avoid complex data augmentation. Secondly, the neighborhood contrastive loss is introduced to constrain node representation using local topological structure while effectively embedding attribute information through attribute reconstruction. Additionally, clustering-oriented contrastive loss is applied to fully utilize clustering information in global semantics for discriminative node representations, regarding the cluster centers from two views as negative samples to fully leverage effective clustering information from different views. Comparative clustering results with existing attributed graph clustering algorithms on six datasets demonstrate the superiority of the proposed method.

Keywords: attributed graph clustering, contrastive learning, clustering-oriented, self-supervised learning

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Authors: Amal A. Hassan, Faten H. Fahmy, Abd El-Shafy A. Nafeh, Hosam K. M. Youssef

Abstract:

Due to the growing penetration of wind energy into the power grid, it is very important to study its interactions with the power system and to provide good control technique in order to deliver high quality power. In this paper, an intelligent control methodology is proposed for optimizing the controllers’ parameters of doubly fed induction generator (DFIG) based wind turbine generation system (WTGS). The genetic algorithm (GA) and particle swarm optimization (PSO) are employed and compared for the parameters adaptive tuning of the proposed proportional integral (PI) multiple controllers of the back to back converters of the DFIG based WTGS. For this purpose, the dynamic model of WTGS with DFIG and its associated controllers is presented. Furthermore, the simulation of the system is performed using MATLAB/SIMULINK and SIMPOWERSYSTEM toolbox to illustrate the performance of the optimized controllers. Finally, this work is validated to 33-bus test radial system to show the interaction between wind distributed generation (DG) systems and the distribution network.

Keywords: DFIG wind turine, intelligent control, distributed generation, particle swarm optimization, genetic algorithm

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Authors: Abdulwahab Alalyani, Mahbub Rashid

Abstract:

Urban Open Space (UOS) a central role to promotes community health, including daily activities, but these resources may not available, accessible enough, and or equitably be distributed. This paper measures and compares spatial equity of the availability and accessibility UOS among low, middle, and high-income neighborhoods in Riyadh city. The measurement mothdulgy for the UOSavailability was by calculating the total of UOS with respect to the population total (m2/inhabitant) and the accessibility indicted by using walking distance of a 0.25 mi (0.4 km) buffering streets network.All UOS were mapped and measured using geographical information systems. To evaluate the significant differences in UOS availability and accessibility across low, medium, and high-income Riyadh neighborhoods, we used a One-way ANOVA analysis of covariance to test the differences.The findings are as follows; finding, UOSavailability was lower than global standers. Riyadh has only 1.13 m2 per capita of UOS, and the coverage accessible area by walking distance to UOS was lower than 50%. The final finding, spatial equity of the availability and accessibility, were significantly different among Riyadh neighborhoods based on socioeconomic status. The future development of UOS should be focused on increasing Urban park availability and should be given priority to those low-income and unhealthy communities.

Keywords: distribution urban open space, urban open space accessibility, spatial equity, riyadh city

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Authors: Gyoutae Park, Geunjun Lyu, Yeonjae Lee, Jaheon Gu, Sanguk Ahn, Hiesik Kim

Abstract:

In this paper, we propose a system for preventing gas risks through the use of wireless communication modules and intelligent gas safety appliances. Our system configuration consists of an automatic extinguishing system, detectors, a wall-pad, and a microcomputer controlled micom gas meter to monitor gas flow and pressure as well as the occurrence of earthquakes. The automatic fire extinguishing system checks for both combustible gaseous leaks and monitors the environmental temperature, while the detector array measures smoke and CO gas concentrations. Depending on detected conditions, the micom gas meter cuts off an inner valve and generates a warning, the automatic fire-extinguishing system cuts off an external valve and sprays extinguishing materials, or the sensors generate signals and take further action when smoke or CO are detected. Information on intelligent measures taken by the gas safety appliances and sensors are transmitted to the wall-pad, which in turn relays this as real time data to a server that can be monitored via an external network (BcN) connection to a web or mobile application for the management of gas safety. To validate this smart-home gas management system, we field-tested its suitability for use in Korean apartments under several scenarios.

Keywords: gas sensor, leak, gas safety, gas meter, gas risk, wireless communication

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Authors: Ramin Vafadary, Maryam Khanbaghi

Abstract:

Forecasting electricity load is important for various purposes like planning, operation, and control. Forecasts can save operating and maintenance costs, increase the reliability of power supply and delivery systems, and correct decisions for future development. This paper compares various time series methods to forecast 24 hours ahead of electricity load. The methods considered are the Holt-Winters smoothing, SARIMA Modeling, LSTM Network, Fbprophet, and Tensorflow probability. The performance of each method is evaluated by using the forecasting accuracy criteria, namely, the mean absolute error and root mean square error. The National Renewable Energy Laboratory (NREL) residential energy consumption data is used to train the models. The results of this study show that the SARIMA model is superior to the others for 24 hours ahead forecasts. Furthermore, a Bagging technique is used to make the predictions more robust. The obtained results show that by Bagging multiple time-series forecasts, we can improve the robustness of the models for 24 hours ahead of electricity load forecasting.

Keywords: bagging, Fbprophet, Holt-Winters, LSTM, load forecast, SARIMA, TensorFlow probability, time series

Procedia PDF Downloads 89