Search results for: simulink simulation model

Authors: Mohammad Hossein Modarressi, Mozhgan Mondeali, Khabat Barkhordari, Ali Etemadi

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The COVID-19 pandemic, caused by SARS-CoV-2, has led to significant concerns worldwide due to its catastrophic effects on public health. The SARS-CoV-2 infection is initiated with the binding of the receptor-binding domain (RBD) in its spike protein to the ACE2 receptor in the host cell membrane. Due to the error-prone entity of the viral RNA-dependent polymerase complex, the virus genome, including the coding region for the RBD, acquires new mutations, leading to the appearance of multiple variants. These variants can potentially impact transmission, virulence, antigenicity and evasive immune properties. S477N mutation located in the RBD has been observed in the SARS-CoV-2 omicron (B.1.1. 529) variant. In this study, we investigated the consequences of S477N mutation at the molecular level using computational approaches such as molecular dynamics simulation, protein-protein interaction analysis, immunoinformatics and free energy computation. We showed that displacement of Ser with Asn increases the stability of the spike protein and its affinity to ACE2 and thus increases the transmission potential of the virus. This mutation changes the folding and secondary structure of the spike protein. Also, it reduces antibody neutralization, raising concern about re-infection, vaccine breakthrough and therapeutic values.

Keywords: S477N, COVID-19, molecular dynamic, SARS-COV2 mutations

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Authors: J. Raub, H. Schillok, L. Kaupe, C. Jung-Sievers, G. Pitschel-Walz, M. Bühner, J. Gensichen, F. D. Pokal-Gruppe

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Introduction: In Germany, depression ranks among the top ten diseases with the highest disease burden and often occurs with comorbidities. Collaborative Care (CC), a concept developed in the United States for the primary care management of chronic diseases, has been identified as an efficient model for the treatment of depression in general medicine. A recent meta-analysis highlights research gaps regarding CC in patients with psychiatric multimorbidity. The highest prevalence of psychiatric comorbidities in depression is observed in anxiety disorders, post-traumatic stress disorder (PTSD), and substance use disorders. Methods: We conducted a literature search following the PRISMA guidelines with three components: Collaborative Care, Depression and randomized controlled trial on the common databases. We focused on the examination of psychiatric comorbidities in depression, specifically Posttraumatic Stress Disorder (PTSD) and Substance Use Disorder (SUD). Results: During the screening process, we identified nine relevant articles related to PTSD, the number of articles related to Substance Use Disorder (SUD) was ten. We examined a total of 8,634 individuals. Our literature review did not reveal any overall significant superiority of the Collaborative Care model compared to Usual Care in patients with depression with comorbid Substance Use Disorder (SUD) or Posttraumatic Stress Disorder (PTSD). Discussion: Five studies demonstrate a faster and statistically significant improvement in depression outcomes among patients with Substance Use Disorder (SUD) and Posttraumatic Stress Disorder (PTSD). Currently, several randomized controlled trials on the topic of Collaborative Care in depression with psychiatric comorbidity are ongoing, such as miCare, Claro and COMET.

Keywords: Depression, primary care, collaborative care, PTSD, Substance use Disorder

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Authors: Zerzouri Nora, Benalia Nadia, Bensiali Nadia

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This paper presents a grid-connected wind power generation scheme using Doubly Fed Induction Generator (DFIG). This can supply power at constant voltage and constant frequency with the rotor speed varying. This makes it suitable for variable speed wind energy application. The DFIG system consists of wind turbine, asynchronous wound rotor induction generator, and inverter with Space Vector Modulation (SVM) controller. In which the stator is connected directly to the grid and the rotor winding is in interface with rotor converter and grid converter. The use of back-to-back SVM converter in the rotor circuit results in low distortion current, reactive power control and operate at variable speed. Mathematical modeling of the DFIG is done in order to analyze the performance of the systems and they are simulated using MATLAB. The simulation results for the system are obtained and hence it shows that the system can operate at variable speed with low harmonic current distortion. The objective is to track and extract maximum power from the wind energy system and transfer it to the grid for useful work.

Keywords: Doubly Fed Induction Generator, Wind Energy Conversion Systems, Space Vector Modulation, distortion harmonics

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Authors: M. Mulumpwa, W. W. L. Jere, M. Lazaro, A. H. N. Mtethiwa

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The study considered Seasonal Autoregressive Integrated Moving Average (SARIMA) processes to select an appropriate stochastic model to forecast the monthly data from the Lake Malawi water levels for the period 1986 through 2015. The appropriate model was chosen based on SARIMA (p, d, q) (P, D, Q)S. The Autocorrelation function (ACF), Partial autocorrelation (PACF), Akaike Information Criteria (AIC), Bayesian Information Criterion (BIC), Box–Ljung statistics, correlogram and distribution of residual errors were estimated. The SARIMA (1, 1, 0) (1, 1, 1)12 was selected to forecast the monthly data of the Lake Malawi water levels from August, 2015 to December, 2021. The plotted time series showed that the Lake Malawi water levels are decreasing since 2010 to date but not as much as was the case in 1995 through 1997. The future forecast of the Lake Malawi water levels until 2021 showed a mean of 474.47 m ranging from 473.93 to 475.02 meters with a confidence interval of 80% and 90% against registered mean of 473.398 m in 1997 and 475.475 m in 1989 which was the lowest and highest water levels in the lake respectively since 1986. The forecast also showed that the water levels of Lake Malawi will drop by 0.57 meters as compared to the mean water levels recorded in the previous years. These results suggest that the Lake Malawi water level may not likely go lower than that recorded in 1997. Therefore, utilisation and management of water-related activities and programs among others on the lake should provide room for such scenarios. The findings suggest a need to manage the Lake Malawi jointly and prudently with other stakeholders starting from the catchment area. This will reduce impacts of anthropogenic activities on the lake’s water quality, water level, aquatic and adjacent terrestrial ecosystems thereby ensuring its resilience to climate change impacts.

Keywords: forecasting, Lake Malawi, water levels, water level fluctuation, climate change, anthropogenic activities

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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: Smita Mondal, Dinesh Kumar Pandey, Prakash Biswas

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During past two decades, considerable attention has been given to the value addition of biodiesel derived glycerol (~10wt.%) to make the biodiesel industry economically viable. Among the various glycerol value-addition methods, hydrogenolysis of glycerol to 1,2-propanediol is one of the attractive and promising routes. In this study, highly active and selective γ-Al₂O₃ supported bimetallic Cu-Ni catalyst was developed for selective hydrogenolysis of glycerol to 1,2-propanediol in the liquid phase. The catalytic performance was evaluated in a high-pressure autoclave reactor. The formation of mixed oxide indicated the strong interaction of Cu, Ni with the alumina support. Experimental results demonstrated that bimetallic copper-nickel catalyst was more active and selective to 1,2-PDO as compared to monometallic catalysts due to bifunctional behavior. To verify the effect of calcination temperature on the formation of Cu-Ni mixed oxide phase, the calcination temperature of 20wt.% Cu:Ni(1:1)/Al₂O₃ catalyst was varied from 300°C-550°C. The physicochemical properties of the catalysts were characterized by various techniques such as specific surface area (BET), X-ray diffraction study (XRD), temperature programmed reduction (TPR), and temperature programmed desorption (TPD). The BET surface area and pore volume of the catalysts were in the range of 71-78 m²g⁻¹, and 0.12-0.15 cm³g⁻¹, respectively. The peaks at the 2θ range of 43.3°-45.5° and 50.4°-52°, was corresponded to the copper-nickel mixed oxidephase [JCPDS: 78-1602]. The formation of mixed oxide indicated the strong interaction of Cu, Ni with the alumina support. The crystallite size decreased with increasing the calcination temperature up to 450°C. Further, the crystallite size was increased due to agglomeration. Smaller crystallite size of 16.5 nm was obtained for the catalyst calcined at 400°C. Total acidic sites of the catalysts were determined by NH₃-TPD, and the maximum total acidic of 0.609 mmol NH₃ gcat⁻¹ was obtained over the catalyst calcined at 400°C. TPR data suggested the maximum of 75% degree of reduction of catalyst calcined at 400°C among all others. Further, 20wt.%Cu:Ni(1:1)/γ-Al₂O₃ catalyst calcined at 400°C exhibited highest catalytic activity ( > 70%) and 1,2-PDO selectivity ( > 85%) at mild reaction condition due to highest acidity, highest degree of reduction, smallest crystallite size. Further, the modified Power law kinetic model was developed to understand the true kinetic behaviour of hydrogenolysis of glycerol over 20wt.%Cu:Ni(1:1)/γ-Al₂O₃ catalyst. Rate equations obtained from the model was solved by ode23 using MATLAB coupled with Genetic Algorithm. Results demonstrated that the model predicted data were very well fitted with the experimental data. The activation energy of the formation of 1,2-PDO was found to be 45 kJ mol⁻¹.

Keywords: glycerol, 1, 2-PDO, calcination, kinetic

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Authors: Sakkarin Chingulpitak, Somchai Wongwises

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Over the past several decades, the development of electronic devices has led to higher performance. Therefore, an electronic cooling system is important for the electronic device. A heat sink which is a part of the electronic cooling system is continuously studied in the research field to enhance the heat transfer. To author’s best knowledge, there have been only a few articles which reported the thermal performance of plate-fin heat sink with perforation. This research aims to study on the flow and heat transfer characteristics of the solid-fin heat sink (SFHS) and laterally perforated plate-fin heat sink (LAP-PFHS). The SFHS and LAP-PFHSs are investigated on the same fin dimensions. The LAP-PFHSs are performed with a 27 perforation number and two different diameters of circular perforation (3 mm and 5 mm). The experimental study is conducted under various Reynolds numbers from 900 to 2,000 and the heat input of 50W. The experimental results show that the LAP-PFHS with perforation diameter of 5 mm gives the minimum thermal resistance about 25% lower than SFHS. The thermal performance factor which takes into account the ratio of the Nusselt number and ratio of friction factor is used to find the suitable design parameters. The experimental results show that the LAP-PFHS with the perforation diameter of 3 mm provides the thermal performance of 15% greater than SFHS. In addition, the simulation study is presented to investigate the effect of the air flow behavior inside the perforation on the thermal performance of LAP-PFHS.

Keywords: heat sink, parallel flow, circular perforation, non-bypass flow

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Authors: Manal M. Kame, Zeinab A. Demerdash, Hanan G. El-Baz, Salwa M. Hassan, Faten M. Salah, Wafaa Mansour, Olfat Hammam

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Cord blood (CB) derived Unrestricted Somatic Stem Cells (USSCs) with their multipotentiality hold great promise in liver regeneration. This work aims at evaluation of the therapeutic potentiality of USSCs in two experimental models of chronic liver injury induced either by S. mansoni infection in balb/c mice or CCL4 injection in hamsters. Isolation, propagation, and characterization of USSCs from CB samples were performed. USSCs were induced to differentiate into osteoblasts, adipocytes and hepatocyte-like cells. Cells of the third passage were transplanted in two models of liver fibrosis: (1) Twenty hamsters were induced to liver fibrosis by repeated i. p. injection of 100 μl CCl4 /hamster for 8 weeks. This model was designed as; 10 hamsters with liver fibrosis and treated with i.h. injection of 3x106 USSCs (USSCs transplanted group), 10 hamsters with liver fibrosis (pathological control group), and 10 hamsters with healthy livers (normal control group). (2) Murine chronics S.mansoni model: twenty mice were induced to liver fibrosis with S. mansoni ceracariae (60 cercariae/ mouse) using the tail immersion method and left for 12 weeks. This model was designed as; 10 mice with liver fibrosis were transplanted with i. v. injection of 1×106 USCCs (USSCs transplanted group). Other 2 groups were designed as in hamsters model. Animals were sacrificed 12 weeks after USSCs transplantation, and their liver sections were examined for detection of human hepatocyte-like cells by immunohistochemistry staining. Moreover, liver sections were examined for fibrosis level, and fibrotic indices were calculated. Sera of sacrificed animals were tested for liver functions. CB USSCs, with fibroblast-like morphology, expressed high levels of CD44, CD90, CD73 and CD105 and were negative for CD34, CD45, and HLA-DR. USSCs showed high expression of transcripts for Oct4 and Sox2 and were in vitro differentiated into osteoblasts, adipocytes. In both animal models, in vitro induced hepatocyte-like cells were confirmed by cytoplasmic expression of glycogen, alpha-fetoprotein, and cytokeratin18. Livers of USSCs transplanted group showed engraftment with human hepatocyte-like cells as proved by cytoplasmic expression of human alpha-fetoprotein, cytokeratin18, and OV6. In addition, livers of this group showed less fibrosis than the pathological control group. Liver functions in the form of serum AST & ALT level and serum total bilirubin level were significantly lowered in USSCs transplanted group than pathological control group (p < 0.001). Moreover, the fibrotic index was significantly lower (p< 0.001) in USSCs transplanted group than pathological control group. In addition liver sections, of i. v. injection of 1×106 USCCs of mice, stained with either H&E or sirius red showed diminished granuloma size and a relative decrease in hepatic fibrosis. Our experimental liver fibrosis models transplanted with CB-USSCs showed liver engraftment with human hepatocyte-like cells as well as signs of liver regeneration in the form of improvement in liver function assays and fibrosis level. These data provide hope that human CB- derived USSCs are introduced as multipotent stem cells with great potentiality in regenerative medicine & strengthens the concept of cellular therapy for the treatment of liver fibrosis.

Keywords: cord blood, liver fibrosis, stem cells, transplantation

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Authors: Dino Carpentras, Paul Maher, Caoimhe O'Reilly, Michael Quayle

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Opinion dynamics is dedicated to modeling the dynamic evolution of people's opinions. Models in this field are based on a micro-dynamic rule, which determines how people update their opinion when interacting. Despite the high number of new models (many of them based on new rules), little research has been dedicated to experimentally validate the rule. A few studies started bridging this literature gap by experimentally testing the rule. However, in these studies, participants are forced to express their opinion as a number instead of using natural language. Furthermore, some of these studies average data from experimental questions, without testing if differences existed between them. Indeed, it is possible that different topics could show different dynamics. For example, people may be more prone to accepting someone's else opinion regarding less polarized topics. In this work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions using natural language ('agree' or 'disagree') and the certainty of their answer, expressed as a number between 1 and 10. To keep the interaction based on natural language, certainty was not shown to other participants. We then showed to the participant someone else's opinion on the same topic and, after a distraction task, we repeated the measurement. To produce data compatible with standard opinion dynamics models, we multiplied the opinion (encoded as agree=1 and disagree=-1) with the certainty to obtain a single 'continuous opinion' ranging from -10 to 10. By analyzing the topics independently, we observed that each one shows a different initial distribution. However, the dynamics (i.e., the properties of the opinion change) appear to be similar between all topics. This suggested that the same micro-dynamic rule could be applied to unpolarized topics. Another important result is that participants that change opinion tend to maintain similar levels of certainty. This is in contrast with typical micro-dynamics rules, where agents move to an average point instead of directly jumping to the opposite continuous opinion. As expected, in the data, we also observed the effect of social influence. This means that exposing someone with 'agree' or 'disagree' influenced participants to respectively higher or lower values of the continuous opinion. However, we also observed random variations whose effect was stronger than the social influence’s one. We even observed cases of people that changed from 'agree' to 'disagree,' even if they were exposed to 'agree.' This phenomenon is surprising, as, in the standard literature, the strength of the noise is usually smaller than the strength of social influence. Finally, we also built an opinion dynamics model from the data. The model was able to explain more than 80% of the data variance. Furthermore, by iterating the model, we were able to produce polarized states even starting from an unpolarized population. This experimental approach offers a way to test the micro-dynamic rule. This also allows us to build models which are directly grounded on experimental results.

Keywords: experimental validation, micro-dynamic rule, opinion dynamics, update rule

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Authors: Suphaphon Udomluck, Pannathorn Chachvarat

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Information Communication Technology (ICT) using management is essential for effective decision making in organization. The Concerns Based Adoption Model (CBAM) was employed as the conceptual framework. The purposes of the study were to assess the situation of Information Communication Technology (ICT) using management in College of Nursing under the Praboromarajchanok Institute. The samples were multi – stage sampling of 10 colleges of nursing that participated include directors, vice directors, head of learning groups, teachers, system administrator and responsible for ICT. The total participants were 280; the instrument used were questionnaires that include 4 parts, general information, Information Communication Technology (ICT) using management, the Stage of concern Questionnaires (SoC), and the Levels of Use (LoU) ICT Questionnaires respectively. Reliability coefficients were tested; alpha coefficients were 0.967for Information Communication Technology (ICT) using management, 0.884 for SoC and 0.945 for LoU. The data were analyzed by frequency, percentage, mean, standard deviation, Pearson Product Moment Correlation and Multiple Regression. They were founded as follows: The high level overall score of Information Communication Technology (ICT) using management and issue were administration, hardware, software, and people. The overall score of the Stage of concern (SoC)ICTis at high level and the overall score of the Levels of Use (LoU) ICTis at moderate. The Information Communication Technology (ICT) using management had the positive relationship with the Stage of concern (SoC)ICTand the Levels of Use (LoU) ICT(p < .01). The results of Multiple Regression revealed that administration hardwear, software and people ware could predict SoC of ICT (18.5%) and LoU of ICT (20.8%).The factors that were significantly influenced by SoCs were people ware. The factors that were significantly influenced by LoU of ICT were administration hardware and people ware.

Keywords: information communication technology (ICT), management, the concerns-based adoption model (CBAM), stage of concern(SoC), the levels of use(LoU)

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Authors: Alamgir Naushad, Ghulam Abbas, Shehzad Ali Shah, Ziaul Haq Abbas

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Unlike conventional networks, it is particularly challenging to manage resources efficiently in Wireless Sensor Networks (WSNs) due to their inherent characteristics, such as dynamic network topology and limited bandwidth and battery power. To ensure energy efficiency, this paper presents a routing protocol for WSNs, namely, Enhanced Hybrid Multipath Routing (EHMR), which employs hierarchical clustering and proposes a next hop selection mechanism between nodes according to a maximum residual energy metric together with a minimum hop count. Load-balancing of data traffic over multiple paths is achieved for a better packet delivery ratio and low latency rate. Reliability is ensured in terms of higher data rate and lower end-to-end delay. EHMR also enhances the fast-failure recovery mechanism to recover a failed path. Simulation results demonstrate that EHMR achieves a higher packet delivery ratio, reduced energy consumption per-packet delivery, lower end-to-end latency, and reduced effect of data rate on packet delivery ratio when compared with eminent WSN routing protocols.

Keywords: energy efficiency, load-balancing, hierarchical clustering, multipath routing, wireless sensor networks

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Authors: Mary-Luz Olivares-Tenorio, Ruud Verkerk, Matthijs Dekker, Martinus A. J. S. van Boekel

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Cape gooseberry, the fruit of the plant Physalis peruviana L. has gained interest in research given its contents of promising health-promoting compounds like contents. The presence of carotenoids, ascorbic acid, minerals, polyphenols, vitamins and antioxidants. This project aims to study thermal stability of β-carotene, ascorbic acid, catechin and epicatechin and antioxidant activity in the matrix of the Cape Gooseberry. Fruits were obtained from a Colombian field in Cundinamarca. Ripeness stage was 4 (According to NTC 4580, corresponding to mature stage) at the moment of the experiment. The fruits have been subjected to temperatures of 40, 60, 80, 100 and 120°C for several times. β-Carotene, ascorbic acid, catechin and epicatechin content were assessed with HPLC and antioxidant activity with the DPPH method. β-Carotene was stable upon 100°C, and showed some degradation at 120°C. The same behavior was observed for epicatechin. Catechin increased during treatment at 40°C, at 60°C it remained stable and it showed degradation at 80°C, 100°C and 120°C that could be described by a second order kinetic model. Ascorbic acid was the most heat-sensitive of the analyzed compounds. It showed degradation at all studied temperatures, and could be described by a first order model. The activation energy for ascorbic acid degradation in cape gooseberry was 46.0 kJ/mol and its degradation rate coefficient at 100 °C was 6.53 x 10-3 s-1. The antioxidant activity declined for all studied temperatures. Results from this study showed that cape gooseberry is an important source of different health-promoting compounds and some of them are stable to heat. That makes this fruit a suitable raw material for processed products such as jam, juices and dehydrated fruit, giving the consumer a good intake of these compounds.

Keywords: goldenberry, health-promoting compounds, phytochemical, processing, heat treatment

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Authors: Youngsun Moon, Yeong-Ju Go, Jong-Soo Choi

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Most drones that currently have surveillance/reconnaissance missions are basically equipped with optical equipment, but we also need to use a microphone array to estimate the location of the acoustic source. This can provide additional information in the absence of optical equipment. The purpose of this study is to estimate Direction of Arrival (DOA) based on Time Difference of Arrival (TDOA) estimation of the acoustic source in the drone. The problem is that it is impossible to measure the clear target acoustic source because of the drone noise. To overcome this problem is to separate the drone noise and the target acoustic source using Blind Source Separation(BSS) based on Independent Component Analysis(ICA). ICA can be performed assuming that the drone noise and target acoustic source are independent and each signal has non-gaussianity. For maximized non-gaussianity each signal, we use Negentropy and Kurtosis based on probability theory. As a result, we can improve TDOA estimation and DOA estimation of the target source in the noisy environment. We simulated the performance of the DOA algorithm applying BSS algorithm, and demonstrated the simulation through experiment at the anechoic wind tunnel.

Keywords: aeroacoustics, acoustic source detection, time difference of arrival, direction of arrival, blind source separation, independent component analysis, drone

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Authors: Nicola Colaninno, Eugenio Morello

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The urban environment affects local-to-global climate and, in turn, suffers global warming phenomena, with worrying impacts on human well-being, health, social and economic activities. Physic-morphological features of the built-up space affect urban air temperature, locally, causing the urban environment to be warmer compared to surrounding rural. This occurrence, typically known as the Urban Heat Island (UHI), is normally assessed by means of air temperature from fixed weather stations and/or traverse observations or based on remotely sensed Land Surface Temperatures (LST). The information provided by ground weather stations is key for assessing local air temperature. However, the spatial coverage is normally limited due to low density and uneven distribution of the stations. Although different interpolation techniques such as Inverse Distance Weighting (IDW), Ordinary Kriging (OK), or Multiple Linear Regression (MLR) are used to estimate air temperature from observed points, such an approach may not effectively reflect the real climatic conditions of an interpolated point. Quantifying local UHI for extensive areas based on weather stations’ observations only is not practicable. Alternatively, the use of thermal remote sensing has been widely investigated based on LST. Data from Landsat, ASTER, or MODIS have been extensively used. Indeed, LST has an indirect but significant influence on air temperatures. However, high-resolution near-surface air temperature (NSAT) is currently difficult to retrieve. Here we have experimented Geographically Weighted Regression (GWR) as an effective approach to enable NSAT estimation by accounting for spatial non-stationarity of the phenomenon. The model combines on-site measurements of air temperature, from fixed weather stations and satellite-derived LST. The approach is structured upon two main steps. First, a GWR model has been set to estimate NSAT at low resolution, by combining air temperature from discrete observations retrieved by weather stations (dependent variable) and the LST from satellite observations (predictor). At this step, MODIS data, from Terra satellite, at 1 kilometer of spatial resolution have been employed. Two time periods are considered according to satellite revisit period, i.e. 10:30 am and 9:30 pm. Afterward, the results have been downscaled at 30 meters of spatial resolution by setting a GWR model between the previously retrieved near-surface air temperature (dependent variable), the multispectral information as provided by the Landsat mission, in particular the albedo, and Digital Elevation Model (DEM) from the Shuttle Radar Topography Mission (SRTM), both at 30 meters. Albedo and DEM are now the predictors. The area under investigation is the Metropolitan City of Milan, which covers an area of approximately 1,575 km2 and encompasses a population of over 3 million inhabitants. Both models, low- (1 km) and high-resolution (30 meters), have been validated according to a cross-validation that relies on indicators such as R2, Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). All the employed indicators give evidence of highly efficient models. In addition, an alternative network of weather stations, available for the City of Milano only, has been employed for testing the accuracy of the predicted temperatures, giving and RMSE of 0.6 and 0.7 for daytime and night-time, respectively.

Keywords: urban climate, urban heat island, geographically weighted regression, remote sensing

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Authors: Fan Yang, Ye-Lu Wang, Yang Zhao

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The dynamic load allowance, as an application result of the vehicle-bridge coupled vibration theory, is an important parameter for bridge design and evaluation. Based on the coupled vehicle-bridge vibration theory, the current work establishes a full girder model of a dynamic load allowance, selects a planar five-degree-of-freedom three-axis vehicle model, solves the coupled vehicle-bridge dynamic response using the APDL language in the spatial finite element program ANSYS, selects the pivot point 2 sections as the representative of the negative moment section, and analyzes the effects of parameters such as travel speed, unevenness, vehicle frequency, span diameter, span number and forced displacement of the support on the negative moment dynamic load allowance through orthogonal tests. The influence of parameters such as vehicle speed, unevenness, vehicle frequency, span diameter, span number, and forced displacement of the support on the negative moment dynamic load allowance is analyzed by orthogonal tests, and the influence law of each influencing parameter is summarized. It is found that the effects of vehicle frequency, unevenness, and speed on the negative moment dynamic load allowance are significant, among which vehicle frequency has the greatest effect on the negative moment dynamic load allowance; the effects of span number and span diameter on the negative moment dynamic load allowance are relatively small; the effects of forced displacement of the support on the negative moment dynamic load allowance are negligible.

Keywords: continuous T-girder bridge, dynamic load allowance, sensitivity analysis, vehicle-bridge coupling

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Authors: Ming-Hong Chen

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In the study, the mechanical and financial feasibility for the compressed air energy storage (CAES) system in the porous media reservoir in Taiwan is evaluated. In 2035, Taiwan aims to install 16.7 GW of wind power and 40 GW of photovoltaic (PV) capacity. However, renewable energy sources often generate more electricity than needed, particularly during winter. Consequently, Taiwan requires long-term, large-scale energy storage systems to ensure the security and stability of its power grid. Currently, the primary large-scale energy storage options are Pumped Hydro Storage (PHS) and Compressed Air Energy Storage (CAES). Taiwan has not ventured into CAES-related technologies due to geological and cost constraints. However, with the imperative of achieving net-zero carbon emissions by 2050, there's a substantial need for the development of a considerable amount of renewable energy. PHS has matured, boasting an overall installed capacity of 4.68 GW. CAES, presenting a similar scale and power generation duration to PHS, is now under consideration. Taiwan's geological composition, being a porous medium unlike salt caves, introduces flow field resistance affecting gas injection and extraction. This study employs a program analysis model to establish the system performance analysis capabilities of CAES. The finite volume model is then used to assess the impact of porous media, and the findings are fed back into the system performance analysis for correction. Subsequently, the financial implications are calculated and compared with existing literature. For Taiwan, the strategic development of CAES technology is crucial, not only for meeting energy needs but also for decentralizing energy allocation, a feature of great significance in regions lacking alternative natural resources.

Keywords: compressed-air energy storage, efficiency, porous media, financial feasibility

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Authors: Rui Tu, Yakui Bai, Huailin Li

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The lead-bismuth eutectic (LBE) alloy is a promising candidate of coolant in the fast neutron reactors and accelerator-driven systems (ADS) because of its good properties, such as low melting point, high neutron yields and high thermal conductivity. Although the corrosion of the structure materials caused by the liquid metal (LM) coolant is a challenge to the safe operating of a lead-bismuth eutectic nuclear reactor. Thermodynamic theories, experiential formulas and experimental data can be used for explaining the maintenance of the protective oxide layers on stainless steels under satisfaction oxygen concentration, but the atomic scale insights of such anti-corrosion mechanisms are little known. In the present work, the first-principles calculations are carried out to study the effects of oxygen partial pressure on the formation energies of the liquid metal coolant relevant impurity defects in the anti-corrosion oxide films on the surfaces of the structure materials. These approaches reveal the microscope mechanisms of the corrosion of the structure materials, especially for the influences from the oxygen partial pressure. The results are helpful for identifying a crucial oxygen concentration for corrosion control, which can ensure the systems to be operated safely under certain temperatures.

Keywords: oxygen partial pressure, liquid metal coolant, TDDFT, anti-corrosion layer, formation energy

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Authors: Yi-Guang Li, Suresh Sampath

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Gas turbine performance degrades over time, and the degradation is greatly affected by environmental, ambient, and operating conditions. The engines may degrade slowly under favorable conditions and result in a waste of engine life if a scheduled maintenance scheme is followed. They may also degrade fast and fail before a scheduled overhaul if the conditions are unfavorable, resulting in serious secondary damage, loss of engine availability, and increased maintenance costs. To overcome these problems, gas turbine owners are gradually moving from scheduled maintenance to condition-based maintenance, where condition monitoring is one of the key supporting technologies. This paper presents an integrated adaptive GPA diagnostics and performance monitoring system developed at Cranfield University for gas turbine gas path condition monitoring. It has the capability to predict the performance degradation of major gas path components of gas turbine engines, such as compressors, combustors, and turbines, using gas path measurement data. It is also able to predict engine key performance parameters for condition monitoring, such as turbine entry temperature that cannot be directly measured. The developed technology has been implemented into digital twin computer Software, Pythia, to support the condition monitoring of gas turbine engines. The capabilities of the integrated GPA condition monitoring system are demonstrated in three test cases using a model gas turbine engine similar to the GE aero-derivative LM2500 engine widely used in power generation and marine propulsion. It shows that when the compressor of the model engine degrades, the Adaptive GPA is able to predict the degradation and the changing engine performance accurately using gas path measurements. Such a presented technology and software are generic, can be applied to different types of gas turbine engines, and provide crucial engine health and performance parameters to support condition monitoring and condition-based maintenance.

Keywords: gas turbine, adaptive GPA, performance, diagnostics, condition monitoring

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Authors: Felix Oromena Egara, Moeketsi Mosia

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The study aimed to evaluate the impact of blended learning on mathematics retention among secondary school students. Conducted in the Isoko North Local Government Area of Delta State, Nigeria, the research involved 1,235 senior class one (SS 1) students. Employing a non-equivalent control group pre-test-post-test quasi-experimental design, a sample of 70 students was selected from two secondary schools with ICT facilities through purposive sampling. Random allocation of students into experimental and control groups was achieved through balloting within each selected school. The investigation included three assessment points: pre-Mathematics Achievement Test (MAT), post-MAT, and post-post-MAT (retention), administered systematically by the researchers. Data collection utilized the established MAT instrument, which demonstrated a high reliability score of 0.86. Statistical analysis was conducted using the Statistical Package for Social Sciences (SPSS) version 28, with mean and standard deviation addressing study questions and analysis of covariance scrutinizing hypotheses at a significance level of .05. Results revealed significantly greater improvements in mathematics retention scores among students exposed to blended learning compared to those instructed through conventional methods. Moreover, noticeable differences in mean retention scores were observed, with male students in the blended learning group exhibiting notably higher performance. Based on these findings, recommendations were made, advocating for mathematics educators to integrate blended learning, particularly in geometry teaching, to enhance students’ retention of mathematical concepts.

Keywords: blended learning, flipped classroom model, secondary school students, station rotation model

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Authors: Mira Kadric

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The proposed paper deals with a new developed approach for interpreting teaching, combining traditional didactics with a new element. The fundamental principle of the approach is taken from the theatre pedagogy (Augusto Boal`s Theatre of the Oppressed) and includes the discussion on social power relations. From the point of view of education sociology this implies strengthening students’ individual potential for self-determination on a number of levels, especially in view of the present increase in social responsibility. This knowledge constitutes a starting point and basis for the process of self-determined action. This takes place in the context of a creative didactic policy which identifies didactic goals, provides clear sequences of content, specifies interdisciplinary methods and examines their practical adequacy and ultimately serves not only individual translators and interpreters, but all parties involved. The goal of the presented didactic model is to promote independent work and problem-solving strategies; this helps to develop creative potential and self-confident behaviour. It also conveys realistic knowledge of professional reality and thus also of the real socio-political and professional parameters involved. As well as providing a discussion of fundamental questions relevant to Translation and Interpreting Studies, this also serves to improve this interdisciplinary didactic approach which simulates interpreting reality and illustrates processes and strategies which (can) take place in real life. This idea is illustrated in more detail with methods taken from the Theatre of the Oppressed created by Augusto Boal. This includes examples from (dialogue) interpreting teaching based on documentation from recordings made in a seminar in the summer term 2014.

Keywords: augusto boal, didactic model, interpreting teaching, theatre of the oppressed

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Authors: Sajed A. Habib

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Problem-based learning (PBL) is a student-centered pedagogy that originated in the medical field and has also been used extensively in other knowledge disciplines with recognized advantages and limitations. PBL has been used in various undergraduate engineering programs with mixed outcomes. The current fourth industrial revolution (digital era or Industry 4.0) has made it essential for many science and engineering students to receive effective training in advanced courses such as industrial automation and robotics. This paper presents a case study at Assumption University of Thailand, where a PBL-like approach was used to teach some aspects of automation and robotics to selected groups of undergraduate engineering students. These students were given some basic level training in automation prior to participating in a subsequent training session in order to solve technical problems with increased complexity. The participating students’ evaluation of the training sessions in terms of learning effectiveness, skills enhancement, and incremental knowledge following the problem-solving session was captured through a follow-up survey consisting of 14 questions and a 5-point scoring system. From the most recent training event, an overall 70% of the respondents indicated that their skill levels were enhanced to a much greater level than they had had before the training, whereas 60.4% of the respondents from the same event indicated that their incremental knowledge following the session was much greater than what they had prior to the training. The instructor-facilitator involved in the training events suggested that this method of learning was more suitable for senior/advanced level students than those at the freshmen level as certain skills to effectively participate in such problem-solving sessions are acquired over a period of time, and not instantly.

Keywords: automation, industry 4.0, model-based design training, problem-based learning

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Authors: Aemro Tazeze Terefe, Mengistu K. Aredo, Abule M. Workagegnehu, Wondimagegn M. Tesfaye

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Climate-induced shocks have been shown to reduce agricultural production and cause fluctuation in output in developing countries. When livelihoods depend on rain-fed agriculture, climate-induced shocks translate into consumption shocks. Despite the substantial improvements in household consumption, climate-induced shocks, and other factors adversely affect consumption dynamics at the household level in Ethiopia. Therefore, household consumption dynamics in the context of climate-induced shocks help to guide resilience capacity and establish appropriate interventions and programs. The research employed three-round panel data based on the Ethiopian Socioeconomic Survey with spatial rainfall data to define unique measures of rainfall variability. The linear dynamic panel model results show that the lagged value of consumption, market shocks, and rainfall variability positively affected consumption dynamics. In contrast, production shocks, temperature, and amount of rainfall had a negative relationship. Coping strategies mitigate adverse climate-induced shocks on consumption aftershocks that smooth consumption over time. Support to increase the resilience capacity of households can involve efforts to make existing livelihoods and forms of production or reductions in the vulnerability of households. Therefore, government interventions are mandatory for asset accumulation agendas that support household coping strategies and respond to shocks. In addition, the dynamic linkage between consumption and significant socioeconomic and institutional factors should be taken into account to minimize the effect of climate-induced shocks on consumption dynamics.

Keywords: climate shock, Ethiopia, fixed-effect model, food security

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Authors: Khawar Naeem, Adel Elomri, Adel Zghibi

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Contamination leakage from municipal solid waste (MSW) landfills is a serious environmental challenge that poses a threat to interconnected ecosystems. It not only contaminates the soil of the saturated zone, but it also percolates down the earth and contaminates the groundwater (GW). In this concise literature review, an effort is made to understand the environmental hazards posed by this contamination to the soil and groundwater, the type of contamination, and possible solutions proposed in the literature. In the study’s second phase, the MSW management practices are explored as the landfill site dump rate and type of MSW into the landfill site directly depend on the MSW management strategies. Case studies from multiple developed and underdeveloped countries are presented, and the complex MSW management system is investigated from an operational perspective to minimize the contamination of GW. One of the significant tools used in the literature was found to be Systems Dynamic Modeling (SDM), which is a simulation-based approach to study the stakeholder’s approach. By employing the SDM approach, the risk of GW contamination can be reduced by devising effective MSW management policies, ultimately resulting in water resource sustainability and regional sustainable development.

Keywords: groundwater contamination, environmental risk, municipal solid waste management, system dynamic modeling, water resource sustainability, sustainable development

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Authors: Mirim Kim, Won-Oak Oh

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Purpose: The purpose of this study was to identify hospitalized children's fall risk factors, fall prevention status and fall prevention strategies recognized by nurses and caregivers of hospitalized children and present an ecological model for fall preventive management in hospitalized children. Method: The participants of this study were 14 nurses working in medical institutions and having more than one year of child care experience and 14 adult caregivers of children under 6 years of age receiving inpatient treatment at a medical institution. One to one interview was attempted to identify their perception of fall preventive management. Transcribed data were analyzed through latent content analysis method. Results: Fall risk factors in hospitalized children were 'unpredictable behavior', 'instability', 'lack of awareness about danger', 'lack of awareness about falls', 'lack of child control ability', 'lack of awareness about the importance of fall prevention', 'lack of sensitivity to children', 'untidy environment around children', 'lack of personalized facilities for children', 'unsafe facility', 'lack of partnership between healthcare provider and caregiver', 'lack of human resources', 'inadequate fall prevention policy', 'lack of promotion about fall prevention', 'a performanceism oriented culture'. Fall preventive management status of hospitalized children were 'absence of fall prevention capability', 'efforts not to fall', 'blocking fall risk situation', 'limit the scope of children's activity when there is no caregiver', 'encourage caregivers' fall prevention activities', 'creating a safe environment surrounding hospitalized children', 'special management for fall high risk children', 'mutual cooperation between healthcare providers and caregivers', 'implementation of fall prevention policy', 'providing guide signs about fall risk'. Fall preventive management strategies of hospitalized children were 'restrain dangerous behavior', 'inspiring awareness about fall', 'providing fall preventive education considering the child's eye level', 'efforts to become an active subject of fall prevention activities', 'providing customed fall prevention education', 'open communication between healthcare providers and caregivers', 'infrastructure and personnel management to create safe hospital environment', 'expansion fall prevention campaign', 'development and application of a valid fall assessment instrument', 'conversion of awareness about safety'. Conclusion: In this study, the ecological model of fall preventive management for hospitalized children reflects various factors that directly or indirectly affect the fall prevention of hospitalized children. Therefore, these results can be considered as useful baseline data for developing systematic fall prevention programs and hospital policies to prevent fall accident in hospitalized children. Funding: This study was funded by the National Research Foundation of South Korea (grant number NRF-2016R1A2B1015455).

Keywords: fall down, safety culture, hospitalized children, risk factors

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Authors: Jenney Perez Bacalla

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The study was conducted to assess the five (5) identified school administrators of the identified secondary schools in terms of professional characteristics, management skills and values patterns in the Division of Leyte Area IV for a proposed enhancement model for school administrators. The study utilized the qualitative method. There were two (2) groups of respondents: the teachers and the school administrators. The teachers perceived the management skills of the school administrators in their technical and conceptual skills and values in planning and organizing work, allocating and using of funds, submitting reports, decision-making, leading people, public relations and community involvement and other value development. It was found out in the study that most of the school administrators’ management skills were very well manifested. Their value patterns were also very well manifested. Most of them had earned master’s degree and with a unit in doctoral and five (5) years and above in service as a school administrator. Most administrators were performing and successfully execute the planning, organizing and utilizing funds and they were able to lead their subordinates. In planning, it shows that administrators studied the future and arrange the plan. Administrators also were able to manage, maintained the good environment wherein individual work together. School administrators were creating an environment conducive to learning. The school administrator is manifesting the desirable practices in school management. In terms of their educational qualifications, they were all qualified. Academic preparation, trainings and maturation were their attributes to the development of managerial skills of the school administrators. They showed competence in the areas of management skills that they were able to carry their functions with utmost responsibility and capability. School administrators in terms of seminars and trainings on administration and supervision were already equipped. It is concluded that the school administrators possessed the necessary skills and work values in administering the school.

Keywords: management skills and values, public secondary schools, qualitative, school administrators

Procedia PDF Downloads 339

Authors: Anil Kumar, Rajnish Kaur, Mateusz Czyzycki, Alessandro Migilori, Andreas Germanos Karydas, Sanjiv Puri

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The radiative decay of Li(i=1-3) sub-shell vacancies produced through photoionization results in production of the characteristic emission spectrum comprising several X-ray lines, whereas non-radiative vacancy decay results in Auger electron spectrum. Accurate reliable data on the Li(i=1-3) sub-shell X-ray production (XRP) cross sections is of considerable importance for investigation of atomic inner-shell ionization processes as well as for quantitative elemental analysis of different types of samples employing the energy dispersive X-ray fluorescence (EDXRF) analysis technique. At incident photon energies in vicinity of the absorption edge energies of an element, the many body effects including the electron correlation, core relaxation, inter-channel coupling and post-collision interactions become significant in the photoionization of atomic inner-shells. Further, in case of compounds, the characteristic emission spectrum of the specific element is expected to get influenced by the chemical environment (coordination number, oxidation state, nature of ligand/functional groups attached to central atom, etc.). These chemical effects on L X-ray fluorescence parameters have been investigated by performing the measurements at incident photon energies much higher than the Li(i=1-3) sub-shell absorption edge energies using EDXRF spectrometers. In the present work, the cross sections for production of the Lk(k= γ2,3, γ4) X-rays have been measured for some compounds of 66Dy, namely, Dy2O3, Dy2(CO3)3, Dy2(SO4)3.8H2O, DyI2 and Dy metal by tuning the incident photon energies few eV above the L1 absorption-edge energy in order to investigate the influence of chemical effects on these cross sections in presence of the many body effects which become significant at photon energies close to the absorption-edge energies. The present measurements have been performed under vacuum at the IAEA end-station of the X-ray fluorescence beam line (10.1L) of ELETTRA synchrotron radiation facility (Trieste, Italy) using self-supporting pressed pellet targets (1.3 cm diameter, nominal thicknesses ~ 176 mg/cm2) of 66Dy compounds (procured from Sigma Aldrich) and a metallic foil of 66Dy (nominal thickness ~ 3.9 mg/cm2, procured from Good Fellow, UK). The present measured cross sections have been compared with theoretical values calculated using the Dirac-Hartree-Slater(DHS) model based fluorescence and Coster-Kronig yields, Dirac-Fock(DF) model based X-ray emission rates and two sets of L1 sub-shell photoionization cross sections based on the non-relativistic Hartree-Fock-Slater(HFS) model and those deduced from the self-consistent Dirac-Hartree-Fock(DHF) model based total photoionization cross sections. The present measured XRP cross sections for 66Dy as well as for its compounds for the L2,3 and L4 X-rays, are found to be higher by ~14-36% than the two calculated set values. It is worth to be mentioned that L2,3 and L4 X-ray lines are originated by filling up of the L1 sub-shell vacancies by the outer sub-shell (N2,3 and O2,3) electrons which are much more sensitive to the chemical environment around the central atom. The present observed differences between measured and theoretical values are expected due to combined influence of the many-body effects and the chemical effects.

Keywords: chemical effects, L X-ray production cross sections, Many body effects, Synchrotron radiation

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Authors: Sujata Kulkarni, Udhav Bhosle, Vijaykumar T.

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Due to the closeness between seismic signals and non-seismic signals, it is vital to detect earthquakes using conventional methods. In order to distinguish between seismic events and non-seismic events depending on their amplitude, our study processes the data that come from seismic sensors. The authors suggest a robust noise suppression technique that makes use of a bandpass filter, an IIR Wiener filter, recursive short-term average/long-term average (STA/LTA), and Carl short-term average (STA)/long-term average for event identification (LTA). The trigger ratio used in the proposed study to differentiate between seismic and non-seismic activity is determined. The proposed work focuses on significant feature extraction for machine learning-based seismic event detection. This serves as motivation for compiling a dataset of all features for the identification and forecasting of seismic signals. We place a focus on feature vector dimension reduction techniques due to the temporal complexity. The proposed notable features were experimentally tested using a machine learning model, and the results on unseen data are optimal. Finally, a presentation using a hybrid dataset (captured by different sensors) demonstrates how this model may also be employed in a real-time setting while lowering false alarm rates. The planned study is based on the examination of seismic signals obtained from both individual sensors and sensor networks (SN). A wideband seismic signal from BSVK and CUKG station sensors, respectively located near Basavakalyan, Karnataka, and the Central University of Karnataka, makes up the experimental dataset.

Keywords: Carl STA/LTA, features extraction, real time, dataset, machine learning, seismic detection

Procedia PDF Downloads 133

Authors: N. P. Patidar, J. Earnest, Laxmikant Nagar, Akshay Sharma

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This paper describes the diligence of a new input signal based fuzzy power system stabilizer in multi-machine power system. Instead of conventional input pairs like speed deviation (∆ω) and derivative of speed deviation i.e. acceleration (∆ω ̇) or speed deviation and accelerating power deviation of each machine, in this paper, deviation of active power through the tie line colligating two areas is used as one of the inputs to the fuzzy logic controller in concurrence with the speed deviation. Fuzzy Logic has the features of simple concept, easy effectuation, and computationally efficient. The advantage of this input is that, the same signal can be fed to each of the fuzzy logic controller connected with each machine. The simulated system comprises of two fully symmetrical areas coupled together by two 230 kV lines. Each area is equipped with two superposable generators rated 20 kV/900MVA and area-1 is exporting 413 MW to area-2. The effectiveness of the proposed control scheme has been assessed by performing small signal stability assessment and transient stability assessment. The proposed control scheme has been compared with a conventional PSS. Digital simulation is used to demonstrate the performance of fuzzy logic controller.

Keywords: Power System Stabilizer (PSS), small signal stability, inter-area oscillation, fuzzy logic controller, membership function, rule base

Procedia PDF Downloads 537

Authors: Nasibeh Mohammadpour, Ali Rajabzadeh, Adel Azar, Hamid Zargham Borujeni,

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Generally, various industries development depends on their stakeholders and beneficiaries supports. One of the most important stakeholders in tourism industry ( which has become one of the most important lucrative and employment-generating activities at the international level these days) are host communities in tourist destination which are affected and effect on this industry development. Recognizing host community and its segmentations can be important to get their support for future decisions and policy making. In order to identify these segments, in this study, clustering of the residents has been done by using some tools that are designed to encounter human complexities and have ability to model and generalize complex systems without any needs for the initial clusters’ seeds like classic methods. Neural networks can help to meet these expectations. The research have been planned to design neural networks-based mathematical model for clustering the host community effectively according to multi criteria, and identifies differences among segments. In order to achieve this goal, the residents’ segmentation has been done by demographic characteristics, their attitude towards the tourism development, the level of satisfaction and the type of their support in this field. The applied method is self-organized neural networks and the results have compared with K-means. As the results show, the use of Self- Organized Map (SOM) method provides much better results by considering the Cophenetic correlation and between clusters variance coefficients. Based on these criteria, the host community is divided into five sections with unique and distinctive features, which are in the best condition (in comparison other modes) according to Cophenetic correlation coefficient of 0.8769 and between clusters variance of 0.1412.

Keywords: Artificial Nural Network, Clustering , Resident, SOM, Tourism

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Authors: Rajinder Pal Kaur, Amit Sharma, Anuj Kumar Sharma, Govind Prasad Sahu

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The existence of chaos in the marine ecosystems may cause planktonic blooms, disease outbreaks, extinction of some plankton species, or some complex dynamics in oceans, which can adversely affect the sustainable marine ecosystem. The control of the chaotic plankton-fish dynamics is one of the main motives of marine ecologists. In this paper, we have studied the impact of phytoplankton refuge, zooplankton refuge, and fear effect on the chaotic plankton-fish dynamics incorporating phytoplankton, zooplankton, and fish biomass. The fear of fish predation transfers the unpredictable(chaotic) behavior of the plankton system to a stable orbit. The defense mechanism developed by prey species due to fear of the predator population can also terminate chaos from the given dynamics. Moreover, the impact of external disturbances like seasonality, noise, periodic fluctuations, and time delay on the given chaotic plankton system has also been discussed. We have applied feedback mechanisms to control the complexity of the system through the parameter noise. The non-feedback schemes are implemented to observe the role of seasonal force, periodic fluctuations, and time delay in suppressing the given chaotic system. Analytical results are substantiated by numerical simulation.

Keywords: plankton, chaos, noise, seasonality, fluctuations, fear effect, prey refuge

Procedia PDF Downloads 89