Search results for: predictive modeling

Authors: May M. Youssef

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This article introduces a design, for additive manufacturing technology, face shield as Personal Protective Equipment from the respiratory viruses such as coronavirus 2. The face shields help to reduce ocular exposure and play a vital role in diverting away from the respiratory COVID-19 air droplets around the users' face. The proposed face shield comprises three assembled polymer parts. The frame with a transparency overhead projector sheet visor is suitable for frontline health care workers and ordinary citizens. The frame design allows tightening the shield around the user’s head and permits rubber elastic straps to be used if required. That ergonomically designed with a unique face mask support used in case of wearing extra protective mask was created using computer aided design (CAD) software package. The finite element analysis (FEA) structural verification of the proposed design is performed by an advanced simulation technique. Subsequently, the prototype model was fabricated by a 3D printing using Fused Deposition Modeling (FDM) as a globally developed face shield product. This study provides a different face shield designs for global production, which showed to be suitable and effective toward supply chain shortages and frequent needs of personal protective goods during coronavirus disease and similar viruses.

Keywords: additive manufacturing, Coronavirus-19, face shield, personal protective equipment, 3D printing

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Authors: Wenhao Wang, Xinzhi Xu, Limin Feng, Wei Cong

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This paper comprehensively investigates current development status of global power grids and fossil energy pipelines (oil and natural gas), proposes a standard visual platform of global power and fossil energy based on Geographic Information System (GIS) technology. In this visual platform, a series of systematic visual models is proposed with global spatial data, systematic energy and power parameters. Under this visual platform, the current Global Power Grids Map and Global Fossil Energy Pipelines Map are plotted within more than 140 countries and regions across the world. Using the multi-scale fusion data processing and modeling methods, the world’s global fossil energy pipelines and power grids information system basic database is established, which provides important data supporting global fossil energy and electricity research. Finally, through the systematic and comparative study of global fossil energy pipelines and global power grids, the general status of global fossil energy and electricity development are reviewed, and energy transition in key areas are evaluated and analyzed. Through the comparison analysis of fossil energy and clean energy, the direction of relevant research is pointed out for clean development and energy transition.

Keywords: energy transition, geographic information system, fossil energy, power systems

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Authors: Jelili Kunle Adedeji, Toeb Akorede Akinbola

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The problem of vehicle mishap as a result of miscalculation, recklessness, or malfunction of some part in a vehicle is acknowledged to be a global issue. In most of the cases, it results into death or life injuries, all over the world; the issue becomes a nightmare to the stakeholders on how to curb mishaps on our roads due to these endemic factors. Hence this research typically examined the design of a device, specifically for learners that can lead to a society of intelligent vehicles (traffic) without withdrawing the driving authority from them, unlike pre-existing systems. Though ILASS shears a lot of principle with existing advance drivers assistance systems, yet there are two fundamental differences between ILASS system and existing systems. Firstly ILASS is meant to accept continuous input from the throttle at all time such that the devices will not constraint the driving process unnecessarily and ensure a change of speed at any point in time. Secondly, it made use of a variable threshold distance between the host vehicle and front vehicle which can be set by the host driver under the constraint of road maintenance agency, who communicates the minimum possible threshold for a different lane to the host vehicle. The results obtained from the simulation of the ILASS system concluded that ILASS is a good solution to road accidents, particularly road accident which occurs as a result of driving at high speed.

Keywords: front-vehicle, host-speed, threshold-distance, ILASS

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Authors: Reyhaneh Saeedi

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Iran is one of the regions which are most prone for earthquakes annually having a large number of financial and mortality and financial losses. Every year around the world, a large number of people lose their home and life due to natural disasters such as earthquakes. It is necessary to provide and specify some suitable places for settling the homeless people before the occurrence of the earthquake, one of the most important factors in crisis planning and management. Some of the natural disasters can be Modeling and shown by Geospatial Information System (GIS). By using GIS, it would be possible to manage the spatial data and reach several goals by making use of the analyses existing in it. GIS has a determining role in disaster management because it can determine the best places for temporary resettling after such a disaster. In this research QuantumGIS software is used that It is an OpenSource software so that easy to access codes and It is also free. In this system, AHP method is used as decision model and to locate the best places for temporary resettling, is done based on the related organizations criteria with their weights and buffers. Also in this research are made the buffer layers of criteria and change them to the raster layers. Later on, the raster layers are multiplied on desired weights then, the results are added together. Eventually, there are suitable places for resettling of victims by desired criteria by different colors with their optimum rate in QuantumGIS platform.

Keywords: disaster management, temporary resettlement, earthquake, QuantumGIS

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Authors: Ziba Khalili, Mohsen Sheikholeslami, Ladan Momayez

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Combining the photovoltaic/thermal (PVT) systems with a thermoelectric (TE) module can raise energy yields since the TE module boosts the system's energy conversion efficiency. In the current study, a PVT system integrated with a TE module was designed and simulated in ANSYS Fluent 19.2. A copper heat transfer tube (HTT) was employed for cooling the photovoltaic (PV) cells. Four different shapes of HTT cross-section, i.e., circular, square, elliptical, and triangular, with equal cross-section areas were investigated. Also, the influence of Cu-Al2O3/water hybrid nanofluid (0.024% volume concentration), fluid inlet velocity (uᵢ ), and amount of solar radiation (G), on the PV temperature (Tₚᵥ) and system performance were investigated. The ambient temperature (Tₐ), wind speed (u𝓌), and fluid inlet temperature (Tᵢ), were considered to be 25°C, 1 m/s, and 27°C, respectively. According to the obtained data, the triangular case had the greatest impact on reducing the compared to other cases. In the triangular case, examination of the effect of hybrid nanofluid showed that the use of hybrid nanofluid at 800 W/m2 led to a reduction of the TPV by 0.6% compared to water, at 0.19 m/s. Moreover, the thermal efficiency ( ) and the overall electrical efficiency (nₜ) of the system improved by 0.93% and 0.22%, respectively, at 0.19 m/s. In a triangular case where G and were 800 W/m2 and 19 m/s, respectively, the highest amount of, thermal power (Eₜ), and, were obtained as 72.76%, 130.84 W and 12.03%, respectively.

Keywords: electrical performance, photovoltaic/thermal, thermoelectric, hybrid nanofluid, thermal efficiency

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Authors: Zehai Yu, Hui Zhu, Linglong Lin, Huawei Liang, Biao Yu, Weixin Huang

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With the development of intelligent vehicle systems, a high-precision road map is increasingly needed in many aspects. The automatic lane lines extraction and modeling are the most essential steps for the generation of a precise lane-level road map. In this paper, an automatic lane-level road map generation system is proposed. To extract the road markings on the ground, the multi-region Otsu thresholding method is applied, which calculates the intensity value of laser data that maximizes the variance between background and road markings. The extracted road marking points are then projected to the raster image and clustered using a two-stage clustering algorithm. Lane lines are subsequently recognized from these clusters by the shape features of their minimum bounding rectangle. To ensure the storage efficiency of the map, the lane lines are approximated to cubic polynomial curves using a Bayesian estimation approach. The proposed lane-level road map generation system has been tested on urban and expressway conditions in Hefei, China. The experimental results on the datasets show that our method can achieve excellent extraction and clustering effect, and the fitted lines can reach a high position accuracy with an error of less than 10 cm.

Keywords: curve fitting, lane-level road map, line recognition, multi-thresholding, two-stage clustering

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Authors: M. R. Daneshgar, S. E. Habibi, E. Daneshgar, A. Daneshgar

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In this paper, a two-dimensional method is developed to simulate the fillet welds in a stiffened cylindrical shell, using finite element method. The stiffener material is aluminum 2519. The thermo-elasto-plastic analysis is used to analyze the thermo-mechanical behavior. Due to the high heat flux rate of the welding process, two uncouple thermal and mechanical analysis are carried out instead of performing a single couple thermo-mechanical simulation. In order to investigate the effects of the welding procedures, two different welding techniques are examined. The resulted residual stresses and distortions due to different welding procedures are obtained. Furthermore, this study employed the technique of element birth and death to simulate the weld filler variation with time in fillet welds. The obtained results are in good agreement with the published experimental and three-dimensional numerical simulation results. Therefore, the proposed 2D modeling technique can effectively give the corresponding results of 3D models. Furthermore, by inspection of the obtained residual hoop and transverse stresses and angular distortions, proper welding procedure is suggested.

Keywords: stiffened cylindrical shell, fillet welds, residual stress, angular distortion, finite element method

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Authors: Jacinta Ifeoma Obidile

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Teachers (vocational and technical educators inclusive) use Information and Communications Technology (ICT) for tasks outside of their normal working hours. This expansion of work duties to non-work time challenges their work-life balance. However, there has been inconsistency in the results on how these relationships correlate. This, therefore, calls for further research studies to examine the moderating mechanisms of such relationships. The present study, therefore, ascertained how vocational and technical educators’ technology acceptance relates to their work-related ICT use beyond their working hours and work-life balance, as well as how their integration affects these relationships. The population of the study comprised 320 Vocational and Technical Educators from the Southeast geopolitical zone of Nigeria. Data were collected from the respondents using the structured questionnaire. The questionnaire was validated by three experts. The reliability of the study was conducted using 20 vocational and technical educators from the South who were not part of the population. The overall reliability coefficient of 0.81 was established using Cronbach’s alpha method. The data collected was analyzed using Structural equation modeling. Findings, among others, revealed that vocational and technical educators’ work-life balance was mediated by increased digital learning environment use after work hours, although reduced by social influence.

Keywords: vocational and technical educators, digital learning environment, working hours, work-life balance, integration preference

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Authors: Balgaisha G. Mukanova, Yelbek B. Utepov, Aida G. Nazarova, Alisher Z. Imanov

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The problem of identifying local noise sources on a construction site using a sensor system is considered. Mathematical modeling of detected signals on sensors was carried out, considering signal decay and signal delay time between the source and detector. Recordings of noises produced by construction tools were used as a dependence of noise on time. Synthetic sensor data was constructed based on these data, and a model of the propagation of acoustic waves from a point source in the three-dimensional space was applied. All sensors and sources are assumed to be located in the same plane. A source localization method is checked based on the signal time delay between two adjacent detectors and plotting the direction of the source. Based on the two direct lines' crossline, the noise source's position is determined. Cases of one dominant source and the case of two sources in the presence of several other sources of lower intensity are considered. The number of detectors varies from three to eight detectors. The intensity of the noise field in the assessed area is plotted. The signal of a two-second duration is considered. The source is located for subsequent parts of the signal with a duration above 0.04 sec; the final result is obtained by computing the average value.

Keywords: acoustic model, direction of arrival, inverse source problem, sound localization, urban noises

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Authors: Samantha Shallop, Hakinya Karra, Tytus Bernas, Gladys Shaw, Gretchen Neigh, Jeffrey Dupree, Mathula Thangarajh

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Abnormal neuronal homeostasis is considered a structural correlate of cognitive deficits in Duchenne Muscular Dystrophy. Neurons are highly polarized cells with multiple dendrites but a single axon. Trafficking of cellular organelles are highly regulated, with the cargo in the somatodendritic region of the neuron not permitted to enter the axonal compartment. We investigated the molecular mechanisms that regular organelle trafficking in neurons using a multimodal approach, including high-resolution structural illumination, proteomics, immunohistochemistry, and computational modeling. We investigated the expression of ankyrin-G, the master regulator controlling neuronal polarity. The expression of ankyrin G and the morphology of the axon initial segment was profoundly abnormal in the CA1 hippocampal neurons in the mdx52 animal model of DMD. Ankyrin-G colocalized with kinesin KIF5a, the anterograde protein transporter, with higher levels in older mdx52 mice than younger mdx52 mice. These results suggest that the functional trafficking from the somatodendritic compartment is abnormal. Our data suggests that dystrophin deficiency compromised neuronal homeostasis via ankyrin-G-based mechanisms.

Keywords: neurons, axonal transport, duchenne muscular dystrophy, organelle transport

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Authors: Mehdi Boukri, Mohammed Naboussi Farsi, Mounir Naili, Omar Amellal, Mohamed Belazougui, Ahmed Mebarki, Nabila Guessoum, Brahim Mezazigh, Mounir Ait-Belkacem, Nacim Yousfi, Mohamed Bouaoud, Ikram Boukal, Aboubakr Fettar, Asma Souki

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The seismic risk to which the urban centres are more and more exposed became a world concern. A co-operation on an international scale is necessary for an exchange of information and experiments for the prevention and the installation of action plans in the countries prone to this phenomenon. For that, the 1990s was designated as 'International Decade for Natural Disaster Reduction (IDNDR)' by the United Nations, whose interest was to promote the capacity to resist the various natural, industrial and environmental disasters. Within this framework, it was launched in 1996, the RADIUS project (Risk Assessment Tools for Diagnosis of Urban Areas Against Seismic Disaster), whose the main objective is to mitigate seismic risk in developing countries, through the development of a simple and fast methodological and operational approach, allowing to evaluate the vulnerability as well as the socio-economic losses, by probable earthquake scenarios in the exposed urban areas. In this paper, we will present the adaptation and application of this methodology to the Algerian context for the seismic risk evaluation in urban areas potentially exposed to earthquakes. This application consists to perform an earthquake scenario in the urban centre of Constantine city, located at the North-East of Algeria, which will allow the building seismic damage estimation of this city. For that, an inventory of 30706 building units was carried out by the National Earthquake Engineering Research Centre (CGS). These buildings were digitized in a data base which comprises their technical information by using a Geographical Information system (GIS), and then they were classified according to the RADIUS methodology. The study area was subdivided into 228 meshes of 500m on side and Ten (10) sectors of which each one contains a group of meshes. The results of this earthquake scenario highlights that the ratio of likely damage is about 23%. This severe damage results from the high concentration of old buildings and unfavourable soil conditions. This simulation of the probable seismic damage of the building and the GIS damage maps generated provide a predictive evaluation of the damage which can occur by a potential earthquake near to Constantine city. These theoretical forecasts are important for decision makers in order to take the adequate preventive measures and to develop suitable strategies, prevention and emergency management plans to reduce these losses. They can also help to take the adequate emergency measures in the most impacted areas in the early hours and days after an earthquake occurrence.

Keywords: seismic risk, mitigation, RADIUS, urban areas, Algeria, earthquake scenario, Constantine

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Authors: Fatima Mehmood, Khalid Farooq

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After the Mangla dam raising in 2010, the maximum reservoir impoundment level of 378.5 m SPD (Survey of Pakistan Datum) was achieved in September 2014. The reservoir drawdown was started on September 29, 2014 and a landslide occurred on Mirpur-Kotli Road near Khaliqabad on November 27, 2014. This landslide took place due to the failure of a slope along the reservoir rim. This study was undertaken to investigate the causative factors of Khaliqabad landslide. Site visits were carried out for recording the field observations and collection of the soil samples. The soil was subjected to different laboratory tests for the determination of index and engineering properties. The shear strength tests were performed at various levels of density and degrees of saturation. These soil parameters were used in an integrated SEEP-SLOPE/W analysis to obtain the drop in factor of safety with time and reservoir drawdown. The results showed the factor of safety dropped from 1.28 to 0.85 over a period of 60 days. The ultimate reduction in the shear strength of soil due to saturation with the simultaneous removal of the stabilizing effect of reservoir caused the disturbing forces to increase, and thus failure happened. The findings of this study can serve as a guideline for the modeling of the slopes experiencing rapid drawdown scenario with the consideration of more realistic distribution of soil moisture/ properties across the slope

Keywords: geotechnical investigation, landslide, reservoir drawdown, shear strength, slope stability

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Authors: Zbigniew Olczykowski

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The paper presents the impact of work on the electric arc furnace power grid. The arc furnace operating will be modeled at different power conditions of steelworks. The paper will describe how to determine the increase in voltage fluctuations caused by working in parallel arc furnaces. The analysis of indicators characterizing the quality of electricity recorded during several cycles of measurement made at the same time at three points grid, with different power and different short-circuit rated voltage, will be carried out. The measurements analysis presented in this paper were conducted in the mains of one of the Polish steel. The indicators characterizing the quality of electricity was recorded during several cycles of measurement while making measurements at three points of different power network short-circuit power and various voltage ratings. Measurements of power quality indices included the one-week measurement cycles in accordance with the EN-50160. Data analysis will include the results obtained during the simultaneous measurement of three-point grid. This will determine the actual propagation of interference generated by the device. Based on the model studies and measurements of quality indices of electricity we will establish the effect of a specific arc on the mains. The short-circuit power network’s minimum value will also be estimated, this is necessary to limit the voltage fluctuations generated by arc furnaces.

Keywords: arc furnaces, long-term flicker, measurement and modeling of power quality, voltage fluctuations

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Authors: Peter L. Varkonyi, Andras A. Sipos

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The quasi-static growth of elastic fibers is studied in the presence of distributed contact with an immobile surface, subject to isotropic dry or viscous friction. Unlike classical problems of elastic stability modelled by autonomous dynamical systems with multiple time scales (slowly varying bifurcation parameter, and fast system dynamics), this problem can only be formulated as a non-autonomous system without time scale separation. It is found that the fibers initially converge to a trivial, straight configuration, which is later replaced by divergence reminiscent of buckling phenomena. In order to capture the loss of stability, a new definition of exponential stability against infinitesimal perturbations for systems defined over finite time intervals is developed. A semi-analytical method for the determination of the critical length based on eigenvalue analysis is proposed. The post-critical behavior of the fibers is studied numerically by using variational methods. The emerging post-critical shapes and the asymptotic behavior as length goes to infinity are identified for simple spatial distributions of growth. Comparison with physical experiments indicates reasonable accuracy of the theoretical model. Some applications from modeling plant root growth to the design of soft manipulators in robotics are briefly discussed.

Keywords: buckling, elastica, friction, growth

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Authors: Golaleh Ghaffari

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A basin sediment yield refers to the amount of sediment exported by a basin over a period of time, which will enter a reservoir located at the downstream limit of the basin. The Soil and Water Assessment Tool (SWAT, 2008) was used to hydrology and sediment transport modeling at daily and monthly time steps within the Gheshlagh dam basin in north-west of Iran. The SWAT model and Geographic Information System (GIS) techniques were applied to evaluate basin hydrology and sediment yield using historical flow and sediment data and to identify and prioritize critical sub-basins based on sediment transport. The results of this study indicated that simulated daily discharge and sediment values matched the observed values satisfactorily. The model predicted that mean annual basin precipitation for the total study period (413 mm) was partitioned in to evapotranspiration (36%), percolation/groundwater recharge (21%) and stream water (25%), yielding 18% surface runoff. Potential source areas of erosion were also identified with the model. The range of the annual contributing erosive zones varied spatially from 0.1 to 103 t/ha according to the slope and land use at the basin scale. Also the fifteen sub basins create the 60% of the total sediment yield between the all (102) sub basins. The results of the study indicated that SWAT can be a useful tool for assessing hydrology and sediment yield response of the watersheds in the region.

Keywords: erosion, Gheshlagh dam, sediment yield, SWAT

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Authors: Mohammad Heidari

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In this paper a method for high strength steel is proposed of residual stresses in autofrettaged tubes by combination of artificial neural networks is presented. Many different thick walled cylinders that were subjected to different conditions were studied. At first, the residual stress is calculated by analytical solution. Then by changing of the parameters that influenced in residual stresses such as percentage of autofrettage, internal pressure, wall ratio of cylinder, material property of cylinder, bauschinger and hardening effect factor, a neural network is created. These parameters are the input of network. The output of network is residual stress. Numerical data, employed for training the network and capabilities of the model in predicting the residual stress has been verified. The output obtained from neural network model is compared with numerical results, and the amount of relative error has been calculated. Based on this verification error, it is shown that the radial basis function of neural network has the average error of 2.75% in predicting residual stress of thick wall cylinder. Further analysis of residual stress of thick wall cylinder under different input conditions has been investigated and comparison results of modeling with numerical considerations shows a good agreement, which also proves the feasibility and effectiveness of the adopted approach.

Keywords: thick walled cylinder, residual stress, radial basis, artificial neural network

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Authors: Dennis Okora Amima Ondieki

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Fertility transition has been identified to be affected by numerous factors. This research aimed to investigate the most real factors affecting fertility transition in Kenya. These factors were firstly extracted from the literature convened into demographic features, social, and economic features, social-cultural features, reproductive features and modernization features. All these factors had 23 factors identified for this study. The data for this study was from the Kenya Demographic and Health Surveys (KDHS) conducted in 1999-2003 and 2003-2008/9. The data was continuous, and it involved the mean birth order for the ten periods. Principal component analysis (PCA) was utilized using 23 factors. Principal component analysis conveyed religion, region, education and marital status as the real factors. PC scores were calculated for every point. The identified principal components were utilized as forecasters in the multiple regression model, with the fertility level as the response variable. The four components were found to be affecting fertility transition differently. It was found that fertility is affected positively by factors of region and marital and negatively by factors of religion and education. These four factors can be considered in the planning policy in Kenya and Africa at large.

Keywords: fertility transition, principal component analysis, Kenya demographic health survey, birth order

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Authors: Julia Ive, Lucia Specia

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Understanding and detecting toxicity is an important problem to support safer human interactions online. Our work focuses on the important problem of contextual toxicity detection, where automated classifiers are tasked with determining whether a short textual segment (usually a sentence) is toxic within its conversational context. We use “toxicity” as an umbrella term to denote a number of variants commonly named in the literature, including hate, abuse, offence, among others. Detecting toxicity in context is a non-trivial problem and has been addressed by very few previous studies. These previous studies have analysed the influence of conversational context in human perception of toxicity in controlled experiments and concluded that humans rarely change their judgements in the presence of context. They have also evaluated contextual detection models based on state-of-the-art Deep Learning and Natural Language Processing (NLP) techniques. Counterintuitively, they reached the general conclusion that computational models tend to suffer performance degradation in the presence of context. We challenge these empirical observations by devising better contextual predictive models that also rely on NLP data augmentation techniques to create larger and better data. In our study, we start by further analysing the human perception of toxicity in conversational data (i.e., tweets), in the absence versus presence of context, in this case, previous tweets in the same conversational thread. We observed that the conclusions of previous work on human perception are mainly due to data issues: The contextual data available does not provide sufficient evidence that context is indeed important (even for humans). The data problem is common in current toxicity datasets: cases labelled as toxic are either obviously toxic (i.e., overt toxicity with swear, racist, etc. words), and thus context does is not needed for a decision, or are ambiguous, vague or unclear even in the presence of context; in addition, the data contains labeling inconsistencies. To address this problem, we propose to automatically generate contextual samples where toxicity is not obvious (i.e., covert cases) without context or where different contexts can lead to different toxicity judgements for the same tweet. We generate toxic and non-toxic utterances conditioned on the context or on target tweets using a range of techniques for controlled text generation(e.g., Generative Adversarial Networks and steering techniques). On the contextual detection models, we posit that their poor performance is due to limitations on both of the data they are trained on (same problems stated above) and the architectures they use, which are not able to leverage context in effective ways. To improve on that, we propose text classification architectures that take the hierarchy of conversational utterances into account. In experiments benchmarking ours against previous models on existing and automatically generated data, we show that both data and architectural choices are very important. Our model achieves substantial performance improvements as compared to the baselines that are non-contextual or contextual but agnostic of the conversation structure.

Keywords: contextual toxicity detection, data augmentation, hierarchical text classification models, natural language processing

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Authors: Yiea Funk Te, Daniel Mueller, Irena Pletikosa Cvijikj

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Small and medium enterprises (SMEs) play an important role in the economy of many countries. When the overall world economy is considered, SMEs represent 95% of all businesses in the world, accounting for 66% of the total employment. Existing studies show that the current business environment is characterized as highly turbulent and strongly influenced by modern information and communication technologies, thus forcing SMEs to experience more severe challenges in maintaining their existence and expanding their business. To support SMEs at improving their competitiveness, researchers recently turned their focus on applying data mining techniques to build risk and growth prediction models. However, data used to assess risk and growth indicators is primarily obtained via questionnaires, which is very laborious and time-consuming, or is provided by financial institutes, thus highly sensitive to privacy issues. Recently, web mining (WM) has emerged as a new approach towards obtaining valuable insights in the business world. WM enables automatic and large scale collection and analysis of potentially valuable data from various online platforms, including companies’ websites. While WM methods have been frequently studied to anticipate growth of sales volume for e-commerce platforms, their application for assessment of SME risk and growth indicators is still scarce. Considering that a vast proportion of SMEs own a website, WM bears a great potential in revealing valuable information hidden in SME websites, which can further be used to understand SME risk and growth indicators, as well as to enhance current SME risk and growth prediction models. This study aims at developing an automated system to collect business-relevant data from the Web and predict future growth trends of SMEs by means of WM and data mining techniques. The envisioned system should serve as an 'early recognition system' for future growth opportunities. In an initial step, we examine how structured and semi-structured Web data in governmental or SME websites can be used to explain the success of SMEs. WM methods are applied to extract Web data in a form of additional input features for the growth prediction model. The data on SMEs provided by a large Swiss insurance company is used as ground truth data (i.e. growth-labeled data) to train the growth prediction model. Different machine learning classification algorithms such as the Support Vector Machine, Random Forest and Artificial Neural Network are applied and compared, with the goal to optimize the prediction performance. The results are compared to those from previous studies, in order to assess the contribution of growth indicators retrieved from the Web for increasing the predictive power of the model.

Keywords: data mining, SME growth, success factors, web mining

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Authors: Alvaro Jose Cordova, Hsuan Teh Hu

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The use of concrete masonry constructions in developing countries has become very frequent, especially for domestic purpose. Most of them with asymmetric wall configurations in plan resulting in significant torsional actions when subjected to seismic loads. The study consisted on the finding of a material model for hollow unreinforced concrete masonry and a validation with experimental data found in literature. Numerical simulations were performed to 20 buildings with variations in wall distributions and heights. Results were analyzed by inspection and with a non-linear static method. The findings revealed that eccentricities as well as structure rigidities have a strong influence on the overall response of concrete masonry buildings. In addition, slab rotations depicted more accurate information about the torsional behavior than maximum versus average displacement ratios. The failure modes in low buildings were characterized by high tensile strains in the first floor. Whereas in tall buildings these strains were lowered significantly by higher compression stresses due to a higher self-weight. These tall buildings developed multiple plastic hinges along the height. Finally, the non-linear static analysis exposed a brittle response for all masonry assemblies. This type of behavior is undesired in any construction and the need for a material model for reinforced masonry is pointed out.

Keywords: concrete damaged plasticity, concrete masonry, macro-modeling, nonlinear static analysis, torsional capacity

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Authors: Greg Turner, Bin Lu, Cheer-Sun Yang

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As computing technology advances, smartphone applications can assist in student learning in a pervasive way. For example, the idea of using a mobile apps for the PA Common Trees, Pests, Pathogens, in the field as a reference tool allows middle school students to learn about trees and associated pests/pathogens without bringing a textbook. In the past, some researches study the mobile software Mobile Application Software Development Life Cycle (MADLC) including traditional models such as the waterfall model, or more recent Agile Methods. Others study the issues related to the software development process. Very little research is on the development of three heterogenous mobile systems simultaneously in a small university where the availability of developers is an issue. In this paper, we propose to use a hybride model of Waterfall Model and the Agile Model, known as the Relay Race Methodology (RRM) in practice, to reflect the concept of racing and relaying for scheduling. Based on the development project, we observe that the modeling of the transition between any two phases is manifested naturally. Thus, we claim that the RRM model can provide a de fecto rather than a de jure basis for the core concept in the MADLC. In this paper, the background of the project is introduced first. Then, the challenges are pointed out followed by our solutions. Finally, the experiences learned and the future work are presented.

Keywords: agile methods, mobile apps, software process model, waterfall model

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Authors: Rômulo Eustáquio Martins de Souza, Paulo Alexandre Rodrigues de Vasconcelos Figueiredo

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In recent years, there has been a surge in interest in applying artificial intelligence techniques, particularly machine learning algorithms. Machine learning is a data-analysis technique that automates the creation of analytical models, making it especially useful for designing complex situations. As a result, this technology aids in reducing human intervention while producing accurate results. This methodology is also extensively used in aerospace engineering since this is a field that encompasses several high-complexity operations, such as rocket propulsion. Rocket propulsion is a high-risk operation in which engine failure could result in the loss of life. As a result, it is critical to use computational methods capable of precisely representing the spacecraft's analytical model to guarantee its security and operation. Thus, this paper describes the use of machine learning algorithms for rocket propulsion to aid the realization that this technique is an efficient way to deal with challenging and restrictive aerospace engineering activities. The paper focuses on three machine-learning-aided rocket propulsion applications: set-point control of an expander-bleed rocket engine, supersonic retro-propulsion of a small-scale rocket, and leak detection and isolation on rocket engine data. This paper describes the data-driven methods used for each implementation in depth and presents the obtained results.

Keywords: data analysis, modeling, machine learning, aerospace, rocket propulsion

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Authors: Justine Ugochukwu Osuagwu, Sazali Abd Wahab

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The performance and operation of NNPC have faced series of attacks by all stakeholders as many have observed lots of inefficiency not only on the part of the management but the staff. This has raised questions of whether their operations and performance are being seriously affected by lack of transformational leadership, and the political competition prevalent in the country. The author has applied the administrative leadership theory and institutional theory as a guide to this study and empirically relates such theories to the study. The study also has utilized the quantitative approach where questionnaires were distributed to 370 participants, and the correctly filled and returned questionnaires were used for the analysis using structural equation modeling. The path coefficient of transformational leadership to performance is strong and positive with β = 0.672; t-value = 14.245; p-value = 0.000. Also, the result found that political competition does not mediate the relationship between transformational leadership and performance of NNPC. (β = -0.008; t-value = -0.600; p- value > 0.05). However, the indirect path is all insignificant, meaning that transformational leadership has relationship with corporate performance.The study found that,while political competition does not serve as a mediator in the relationship between transformational leadership and corporate performance, these styles of leadership have a direct and positive impact on corporate performance. The direct relationship between transformational leadership and political competition was not discovered, despite the fact that political competition has a direct and significant impact, both positive and negative, on corporate performance. As a result, both political competition and transformational leadership have the potential to significantly alter corporate performance.

Keywords: performance, transformational leadership, political competition, corporation performance, Nigeria national petroleum corporation

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Authors: M. Mohsin Munir, Taimoor Ahmad, Javed Munir, Usman Rashid

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Determination of maximum elevation of a flowing fluid due to sudden rejection of load in a hydropower facility is of great interest to hydraulic engineers to ensure safety of the hydraulic structures. Several mathematical models exist that employ one-dimensional modeling for the determination of surge but none of these perfectly simulate real-time circumstances. The paper envisages investigation of surge inception and propagation for a Low Head Hydropower project using Computational Fluid Dynamics (CFD) analysis on FLOW-3D software package. The fluid dynamic model utilizes its analysis for surge by employing Reynolds’ Averaged Navier-Stokes Equations (RANSE). The CFD model is designed for a case study at Taunsa hydropower Project in Pakistan. Various scenarios have run through the model keeping in view upstream boundary conditions. The prototype results were then compared with the results of physical model testing for the same scenarios. The results of the numerical model proved quite accurate coherence with the physical model testing and offers insight into phenomenon which are not apparent in physical model and shall be adopted in future for the similar low head projects limiting delays and cost incurred in the physical model testing.

Keywords: surge, FLOW-3D, numerical model, Taunsa, RANSE

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Authors: Marina Shargorodsky

Abstract:

Aim: Gestational weight gain (GWG) has been related to altering future weight-gain curves and increased risks of obesity later in life. Obesity may contribute to vascular atherosclerotic changes as well as excess cardiovascular morbidity and mortality observed in these patients. Noninvasive arterial testing, such as ultrasonographic measurement of carotid IMT, is considered a surrogate for systemic atherosclerotic disease burden and is predictive of cardiovascular events in asymptomatic individuals as well as recurrent events in patients with known cardiovascular disease. Currently, there is no consistent evidence regarding the vascular impact of excessive GWG. The present study was designed to investigate the impact of GWG on early atherosclerotic changes during late pregnancy, using intima-media thickness, as well as placental vascular circulation and inflammatory lesions and pregnancy outcomes. Methods: The study group consisted of 59 pregnant women who gave birth and underwent a placental histopathological examination at the Department of Obstetrics and Gynecology, Edith Wolfson Medical Center, Israel, in 2019. According to the IOM guidelines the study group has been divided into two groups: Group 1 included 32 women with pregnancy weight gain within recommended range; Group 2 included 27 women with excessive weight gain during pregnancy. The IMT was measured from non-diseased intimal and medial wall layers of the carotid artery on both sides, visualized by high-resolution 7.5 MHz ultrasound (Apogee CX Color, ATL). Placental histology subdivided placental findings to lesions consistent with maternal vascular and fetal vascular malperfusion according to the criteria of the Society for Pediatric Pathology, subdividing placental findings to lesions consistent with maternal vascular and fetal vascular malperfusion, as well as the inflammatory response of maternal and fetal origin. Results: IMT levels differed between groups and were significantly higher in Group 1 compared to Group 2 (0.7+/-0.1 vs 0.6+/-0/1, p=0.028). Multiple linear regression analysis of IMT included variables based on their associations in univariate analyses with a backward approach. Included in the model were pre-gestational BMI, HDL cholesterol and fasting glucose. The model was significant (p=0.001) and correctly classified 64.7% of study patients. In this model, pre-pregnancy BMI remained a significant independent predictor of subclinical atherosclerosis assessed by IMT (OR 4.314, 95% CI 0.0599-0.674, p=0.044). Among placental lesions related to fetal vascular malperfusion, villous changes consistent with fetal thrombo-occlusive disease (FTOD) were significantly higher in Group 1 than in Group 2, p=0.034). In Conclusion, the present study demonstrated that excessive weight gain during pregnancy is associated with an adverse effect on early stages of subclinical atherosclerosis, placental vascular circulation and neonatal complications. The precise mechanism for these vascular changes, as well as the overall clinical impact of weight control during pregnancy on IMT, placental vascular circulation as well as pregnancy outcomes, deserves further investigation.

Keywords: obesity, pregnancy, complications, weight gain

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Authors: Zerzouri Nora, Benalia Nadia, Bensiali Nadia

Abstract:

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

Procedia PDF Downloads 482

Authors: Porntip Ruengtam

Abstract:

This article is an extension of previous research presenting the relevant factors related to environmental perceptions, residential community, and the design of a healing environment, which have effects on the well-being and requirements of Thai elderly. Research methodology began with observations and interviews in three case studies in terms of the management processes and environment design of similar existing projects in Thailand. The interview results were taken to summarize with related theories and literature. A questionnaire survey was designed for data collection to confirm the factors of requirements in a residential community intended for the Thai elderly. A structural equation model (SEM) was formulated to explain the cause-effect factors for the requirements of a residential community for Thai elderly. The research revealed that the requirements of a residential community for Thai elderly were classified into three groups when utilizing a technique for exploratory factor analysis. The factors were comprised of (1) requirements for general facilities and activities, (2) requirements for facilities related to health and security, and (3) requirements for facilities related to physical exercise in the residential community. The results from the SEM showed the background of elderly people had a direct effect on their requirements for a residential community from various aspects. The results should lead to the formulation of policies for design and management of residential communities for the elderly in order to enhance quality of life as well as both the physical and mental health of the Thai elderly.

Keywords: elderly, environmental design, residential community, structural equation modeling

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Authors: Najrullah Khan, Athar Ali Khan

Abstract:

The Topp-Leone distribution was introduced by Topp- Leone in 1955. In this paper, an attempt has been made to fit Topp-Leone Generalized exponential (TPGE) distribution. A real survival data set is used for illustrations. Implementation is done using R and JAGS and appropriate illustrations are made. R and JAGS codes have been provided to implement censoring mechanism using both optimization and simulation tools. The main aim of this paper is to describe and illustrate the Bayesian modelling approach to the analysis of survival data. Emphasis is placed on the modeling of data and the interpretation of the results. Crucial to this is an understanding of the nature of the incomplete or 'censored' data encountered. Analytic approximation and simulation tools are covered here, but most of the emphasis is on Markov chain based Monte Carlo method including independent Metropolis algorithm, which is currently the most popular technique. For analytic approximation, among various optimization algorithms and trust region method is found to be the best. In this paper, TPGE model is also used to analyze the lifetime data in Bayesian paradigm. Results are evaluated from the above mentioned real survival data set. The analytic approximation and simulation methods are implemented using some software packages. It is clear from our findings that simulation tools provide better results as compared to those obtained by asymptotic approximation.

Keywords: Bayesian Inference, JAGS, Laplace Approximation, LaplacesDemon, posterior, R Software, simulation

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Authors: Ashish Kumar Agrahari, Amit Kumar

Abstract:

Paroxysmal nocturnal hemoglobinuria (PNH) is an acquired clonal blood disorder that manifests with hemolytic anemia, thrombosis, and peripheral blood cytopenias. The disease is caused by the deficiency of two glycosylphosphatidylinositols (GPI)-anchored proteins (CD55 and CD59) in the hemopoietic stem cells. The deficiency of GPI-anchored proteins has been associated with the somatic mutations in phosphatidylinositol glycan class A (PIGA). However, the mutations that do not cause PNH is associated with the multiple congenital anomalies-hypotonia-seizures syndrome 2 (MCAHS2). To best of our knowledge, no computational study has been performed to explore the atomistic level impact of PIGA mutations on the structure and dynamics of the protein. In the current work, we are mainly interested to get insights into the molecular mechanism of PIGA mutations. In the initial step, we screened the most pathogenic mutations from the pool of publicly available mutations. Further, to get a better understanding, pathogenic mutations were mapped to the modeled structure and subjected to 50ns molecular dynamics simulation. Our computational study suggests that four mutations are highly vulnerable to altering the structural conformation and stability of the PIGA protein, which illustrates its association with PNH and MCAHS2 phenotype.

Keywords: homology modeling, molecular dynamics simulation, missense mutations PNH, MCAHS2, PIGA

Procedia PDF Downloads 143

Authors: Amokrane Boufares, Elise Provost, Veronique Osswald, Pascal Clain, Anthony Delahaye, Laurence Fournaison, Didier Dalmazzone

Abstract:

Gas hydrates have long been considered as problematic for flow assurance in natural gas and oil transportation. On the other hand, they are now seen as future promising materials for various applications (i.e. desalination of seawater, natural gas and hydrogen storage, gas sequestration, gas combustion separation and cold storage and transport). Nonetheless, a better understanding of the crystallization mechanism of gas hydrate and of their formation kinetics is still needed for a better comprehension and control of the process. To that purpose, measuring the real-time evolution of the dissolved gas concentration in the aqueous phase during hydrate formation is required. In this work, CO₂ hydrates were formed in a stirred reactor equipped with an Attenuated Total Reflection (ATR) probe coupled to a Fourier Transform InfraRed (FTIR) spectroscopy analyzer. A method was first developed to continuously measure in-situ the CO₂ concentration in the liquid phase during solubilization, supersaturation, hydrate crystallization and dissociation steps. Thereafter, the measured concentration data were compared with those of equilibrium concentrations. It was observed that the equilibrium is instantly reached in the liquid phase due to the fast consumption of dissolved gas by the hydrate crystallization. Consequently, it was shown that hydrate crystallization kinetics is limited by the gas transfer at the gas-liquid interface. Finally, we noticed that the liquid-hydrate equilibrium during the hydrate crystallization is governed by the temperature of the experiment under the tested conditions.

Keywords: gas hydrate, dissolved gas, crystallization, infrared spectroscopy

Procedia PDF Downloads 280