Search results for: predictive noise modelling

Authors: Marcin Szlachetka, Rafal Sochaczewski, Lukasz Grabowski

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This paper presents the results of the load simulations of main bearings in a two-stroke Diesel engine. A model of an engine lubrication system with connections of its main lubrication nodes, i.e., a connection of its main bearings in the engine block with the crankshaft, a connection of its crankpins with its connecting rod and a connection of its pin and its piston has been created for our calculations performed using the AVL EXCITE Designer. The analysis covers the loads given as a pressure distribution in a hydrodynamic oil film, a temperature distribution on the main bush surfaces for the specified radial clearance values as well as the impact of the force of gas on the minimum oil film thickness in the main bearings depending on crankshaft rotational speeds and temperatures of oil in the bearings. One of the main goals of the research has been to determine whether the minimum thickness of the oil film at which fluid friction occurs can be achieved for each value of crankshaft speed. Our model calculates different oil film parameters, i.e., its thickness, a pressure distribution there, the change in oil temperature. Additional enables an analysis of an oil temperature distribution on the surfaces of the bearing seats. It allows verifying the selected clearances in the bearings of the main engine under normal operation conditions and extremal ones that show a significant increase in temperature above the limit value. The research has been conducted for several engine crankshaft speeds ranging from 1000 rpm to 4000 rpm. The oil pressure in the bearings has ranged 2-5 bar according to engine speeds and the oil temperature has ranged 90-120 °C. The main bearing clearance has been adopted for the calculation and analysis as 0.025 mm. The oil classified as SAE 5W-30 has been used for the simulations. The paper discusses the selected research results referring to several specific operating points and different temperatures of the lubricating oil in the bearings. The received research results show that for the investigated main bearing bushes of the shaft, the results fall within the ranges of the limit values despite the increase in the oil temperature of the bearings reaching 120˚C. The fact that the bearings are loaded with the maximum pressure makes no excessive temperature rise on the bush surfaces. The oil temperature increases by 17˚C, reaching 137˚C at a speed of 4000 rpm. The minimum film thickness at which fluid friction occurs has been achieved for each of the operating points at each of the engine crankshaft speeds. Acknowledgement: This work has been realized in the cooperation with The Construction Office of WSK ‘PZL-KALISZ’ S.A.’ and is part of Grant Agreement No. POIR.01.02.00-00-0002/15 financed by the Polish National Centre for Research and Development.

Keywords: diesel engine, main bearings, opposing pistons, two-stroke

Procedia PDF Downloads 115

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: Piotr J. Skusiewicz, Johnathan Saul, Ijhar Rusli, Svetlana Aleksandrova, Stephen. F. Benjamin, Miroslaw Gall, Steve Pierson, Carol A. Roberts

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The application of turbocharging in automotive engines leads to swirling flow entering the catalyst. The behaviour of this type of flow within the catalyst has yet to be adequately documented. This work discusses the effect of swirling flow on the flow distribution in automotive exhaust catalysts. Compressed air supplied to a moving-block swirl generator allowed for swirling flow with variable intensities to be generated. Swirl intensities were measured at the swirl generator outlet using single-sensor hot-wire probes. The swirling flow was fed into diffusers with total angles of 10°, 30° and 180°. Downstream of the diffusers, a wash-coated diesel oxidation catalyst (DOC) of length 143.8 mm, diameter 76.2 mm and nominal cell density of 400 cpsi was fitted. Velocity profiles were measured at the outlet sleeve about 30 mm downstream of the monolith outlet using single-sensor hot-wire probes. Wall static pressure was recorded using a multi-tube manometer connected to pressure taps positioned along the diffuser walls. The results show that as swirl is increased, more of the flow is directed towards the diffuser walls. The velocity decreases around the centre-line and maximum velocities are observed close to the outer radius of the monolith for all flow rates. At the maximum swirl intensity, reversed flow was recorded near the centre of the monolith. Wall static pressure measurements in the 180° diffuser indicated no pressure recovery as the flow enters the diffuser. This is indicative of flow separation at the inlet to the diffuser. To gain insight into the flow structure, CFD simulations have been performed for the 180° diffuser for a flow rate of 63 g/s. The geometry of the model consists of the complete assembly from the upstream swirl generator to the outlet sleeve. Modelling of the flow in the monolith was achieved using the porous medium approach, where the monolith with parallel flow channels is modelled as a porous medium that resists the flow. A reasonably good agreement was achieved between the experimental and CFD results downstream of the monolith. The CFD simulations allowed visualisation of the separation zones and central toroidal recirculation zones that occur within the expansion region at certain swirl intensities which are highlighted.

Keywords: catalyst, computational fluid dynamics, diffuser, hot-wire anemometry, swirling flow

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Authors: Bryan Clark B. Hernandez, Eugene C. Herrera, Kazuo Nadaoka

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Mangrove forests thriving in intertidal zones in tropical and subtropical regions of the world offer a range of ecosystem services including carbon storage and sequestration. They can regulate the detrimental effects of climate change due to carbon releases two to four times greater than that of mature tropical rainforests. Moreover, they are effective natural defenses against storm surges and tsunamis. However, their proliferation depends significantly on the prevailing hydroperiod at the coast. In the Philippines, these coastal ecosystems have been severely threatened with a 50% decline in areal extent observed from 1918 to 2010. The highest decline occurred in 1950 - 1972 when national policies encouraged the development of fisheries and aquaculture. With the intensive land use conversion upstream, changes in the freshwater-saltwater envelope at the coast may considerably impact mangrove growth conditions. This study investigates a developing urban watershed in Kalibo, Aklan province with a 220-hectare mangrove forest replanted for over 30 years from coastal mudflats. Since then, the mangrove forest was sustainably conserved and declared as protected areas. Hybrid land cover classification technique was used to classify Landsat images for years, 1990, 2010, and 2017. Digital elevation model utilized was Interferometric Synthetic Aperture Radar (IFSAR) with a 5-meter resolution to delineate the watersheds. Using numerical modelling techniques, the hydrologic and hydraulic analysis of the influence of land cover change to flow and sediment dynamics was simulated. While significant land cover change occurred upland, thereby increasing runoff and sediment loads, the mangrove forests abundance adjacent to the coasts for the urban watershed, was somehow sustained. However, significant alteration of the coastline was observed in Kalibo through the years, probably due to the massive land-use conversion upstream and significant replanting of mangroves downstream. Understanding the hydrologic-hydraulic response of these watersheds to change land cover is essential to helping local government and stakeholders facilitate better management of these mangrove ecosystems.

Keywords: coastal mangroves, hydrologic model, land cover change, Philippines

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Authors: Soo-Yong Cho, Chong-Hyun Cho, Chae-Whan Rim, Sang-Kyu Choi, Jin-Gyun Kim, Ju-Seok Nam

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Recently, vertical axis wind turbines (VAWT) have been widely used to produce electricity even in urban. They have several merits such as low sound noise, easy installation of the generator and simple structure without yaw-control mechanism and so on. However, their blades are operated under the influence of the trailing vortices generated by the preceding blades. This phenomenon deteriorates its output power and makes difficulty predicting correctly its performance. In order to improve the performance of VAWT, wind power towers can be applied. Usually, the wind power tower can be constructed as a multi-story building to increase the frontal area of the wind stream. Hence, multiple sets of the VAWT can be installed within the wind power tower, and they can be operated at high elevation. Many different types of wind power tower can be used in the field. In this study, a wind power tower with circular column shape was applied, and the VAWT was installed at the center of the wind power tower. Seven guide walls were used as a strut between the floors of the wind power tower. These guide walls were utilized not only to increase the wind velocity within the wind power tower but also to adjust the wind direction for making a better working condition on the VAWT. Hence, some important design variables, such as the distance between the wind turbine and the guide wall, the outer diameter of the wind power tower, the direction of the guide wall against the wind direction, should be considered to enhance the output power on the VAWT. A numerical analysis was conducted to find the optimum dimension on design variables by using the computational fluid dynamics (CFD) among many prediction methods. The CFD could be an accurate prediction method compared with the stream-tube methods. In order to obtain the accurate results in the CFD, it needs the transient analysis and the full three-dimensional (3-D) computation. However, this full 3-D CFD could be hard to be a practical tool because it requires huge computation time. Therefore, the reduced computational domain is applied as a practical method. In this study, the computations were conducted in the reduced computational domain and they were compared with the experimental results in the literature. It was examined the mechanism of the difference between the experimental results and the computational results. The computed results showed this computational method could be an effective method in the design methodology using the optimization algorithm. After validation of the numerical method, the CFD on the wind power tower was conducted with the important design variables affecting the performance of VAWT. The results showed that the output power of the VAWT obtained using the wind power tower was increased compared to them obtained without the wind power tower. In addition, they showed that the increased output power on the wind turbine depended greatly on the dimension of the guide wall.

Keywords: CFD, performance, VAWT, wind power tower

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Authors: Zunaira Zaman, David Bohannon

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This study explores the application of machine learning (ML) for detecting security vulnerabilities in source code. The research aims to assist organizations with large application portfolios and limited security testing capabilities in prioritizing security activities. ML-based approaches offer benefits such as increased confidence scores, false positives and negatives tuning, and automated feedback. The initial approach using natural language processing techniques to extract features achieved 86% accuracy during the training phase but suffered from overfitting and performed poorly on unseen datasets during testing. To address these issues, the study proposes using the abstract syntax tree (AST) for Java and C++ codebases to capture code semantics and structure and generate path-context representations for each function. The Code2Vec model architecture is used to learn distributed representations of source code snippets for training a machine-learning classifier for vulnerability prediction. The study evaluates the performance of the proposed methodology using two datasets and compares the results with existing approaches. The Devign dataset yielded 60% accuracy in predicting vulnerable code snippets and helped resist overfitting, while the Juliet Test Suite predicted specific vulnerabilities such as OS-Command Injection, Cryptographic, and Cross-Site Scripting vulnerabilities. The Code2Vec model achieved 75% accuracy and a 98% recall rate in predicting OS-Command Injection vulnerabilities. The study concludes that even partial AST representations of source code can be useful for vulnerability prediction. The approach has the potential for automated intelligent analysis of source code, including vulnerability prediction on unseen source code. State-of-the-art models using natural language processing techniques and CNN models with ensemble modelling techniques did not generalize well on unseen data and faced overfitting issues. However, predicting vulnerabilities in source code using machine learning poses challenges such as high dimensionality and complexity of source code, imbalanced datasets, and identifying specific types of vulnerabilities. Future work will address these challenges and expand the scope of the research.

Keywords: code embeddings, neural networks, natural language processing, OS command injection, software security, code properties

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Authors: Benoît Mary, Thibaut Gras, Gaëtan Fagot, Yvon Goth, Ilyes Mnassri-Cetim

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A Gerotor pump is composed of an external and internal gear with conjugate cycloidal profiles. From suction to delivery ports, the fluid is transported inside cavities formed by teeth and driven by the shaft. From a geometric and conceptional side it is worth to note that the internal gear has one tooth less than the external one. Simcenter Amesim v.16 includes a new submodel for modelling the hydraulic Gerotor pumps behavior (THCDGP0). This submodel considers leakages between teeth tips using Poiseuille and Couette flows contributions. From the 3D CAD model of the studied pump, the “CAD import” tool takes out the main geometrical characteristics and the submodel THCDGP0 computes the evolution of each cavity volume and their relative position according to the suction or delivery areas. This module, based on international publications, presents robust results up to 6 000 rpm for pressure greater than atmospheric level. For higher rotational speeds or lower pressures, oil aeration and cavitation effects are significant and highly drop the pump’s performance. The liquid used in hydraulic systems always contains some gas, which is dissolved in the liquid at high pressure and tends to be released in a free form (i.e. undissolved as bubbles) when pressure drops. In addition to gas release and dissolution, the liquid itself may vaporize due to cavitation. To model the relative density of the equivalent fluid, modified Henry’s law is applied in Simcenter Amesim v.16 to predict the fraction of undissolved gas or vapor. Three parietal pressure sensors have been set up upstream from the pump to estimate the sound speed in the oil. Analytical models have been compared with the experimental sound speed to estimate the occluded gas content. Simcenter Amesim v.16 model was supplied by these previous analyses marks which have successfully improved the simulations results up to 14 000 rpm. This work provides a sound foundation for designing the next Gerotor pump generation reaching high rotation range more than 25 000 rpm. This improved module results will be compared to tests on this new pump demonstrator.

Keywords: gerotor pump, high speed, numerical simulations, aeronautic, aeration, cavitation

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Authors: Thabo M. Bafitlhile, Adewole Oladele

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Botswana has been affected by floods since long ago and is still experiencing this tragic event. Flooding occurs mostly in the North-West, North-East, and parts of Central district due to heavy rainfalls experienced in these areas. The torrential rains destroyed homes, roads, flooded dams, fields and destroyed livestock and livelihoods. Palapye is one area in the central district that has been experiencing floods ever since 1995 when its greatest flood on record occurred. Heavy storms result in floods and inundation; this has been exacerbated by poor and absence of drainage structures. Since floods are a part of nature, they have existed and will to continue to exist, hence more destruction. Furthermore floods and highway plays major role in erosion and destruction of roads structures. Already today, many culverts, trenches, and other drainage facilities lack the capacity to deal with current frequency for extreme flows. Future changes in the pattern of hydro climatic events will have implications for the design and maintenance costs of roads. Increase in rainfall and severe weather events can affect the demand for emergent responses. Therefore flood forecasting and warning is a prerequisite for successful mitigation of flood damage. In flood prone areas like Palapye, preventive measures should be taken to reduce possible adverse effects of floods on the environment including road structures. Therefore this paper attempts to estimate return periods associated with huge storms of different magnitude from recorded historical rainfall depth using statistical method. The method of annual maxima was used to select data sets for the rainfall analysis. In the statistical method, the Type 1 extreme value (Gumbel), Log Normal, Log Pearson 3 distributions were all applied to the annual maximum series for Palapye area to produce IDF curves. The Kolmogorov-Smirnov test and Chi Squared were used to confirm the appropriateness of fitted distributions for the location and the data do fit the distributions used to predict expected frequencies. This will be a beneficial tool for urgent flood forecasting and water resource administration as proper drainage design will be design based on the estimated flood events and will help to reclaim and protect the road structures from adverse impacts of flood.

Keywords: drainage, estimate, evaluation, floods, flood forecasting

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Authors: Iddy Iddy, Qin Jiang, Changkuan Zhang

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This paper addresses the hydraulic performance of curtain wall breakwaters as a coastal structure protection based on the particles method modelling. The hydraulic functions of curtain wall as wave barriers by reflecting large parts of incident waves through the vertical wall, a part transmitted and a particular part was dissipating the wave energies through the eddy flows formed beneath the lower end of the plate. As a Lagrangian particle, the Moving Particle Semi-implicit (MPS) method which has a robust capability for numerical representation has proven useful for design of structures application that concern free-surface hydrodynamic flow, such as wave breaking and overtopping. In this study, a vertical two-dimensional numerical model for the simulation of violent flow associated with the interaction between the curtain-wall breakwaters and progressive water waves is developed by MPS method in which a higher precision pressure gradient model and free surface particle recognition model were proposed. The wave transmission, reflection, and energy dissipation of the vertical wall were experimentally and theoretically examined. With the numerical wave flume by particle method, very detailed velocity and pressure fields around the curtain-walls under the action of waves can be computed in each calculation steps, and the effect of different wave and structural parameters on the hydrodynamic characteristics was investigated. Also, the simulated results of temporal profiles and distributions of velocity and pressure in the vicinity of curtain-wall breakwaters are compared with the experimental data. Herein, the numerical investigation of hydraulic performance of curtain wall breakwaters indicated that the incident wave is largely reflected from the structure, while the large eddies or turbulent flows occur beneath the curtain-wall resulting in big energy losses. The improved MPS method shows a good agreement between numerical results and analytical/experimental data which are compared to related researches. It is thus verified that the improved pressure gradient model and free surface particle recognition methods are useful for enhancement of stability and accuracy of MPS model for water waves and marine structures. Therefore, it is possible for particle method (MPS method) to achieve an appropriate level of correctness to be applied in engineering fields through further study.

Keywords: curtain wall breakwaters, free surface flow, hydraulic performance, improved MPS method

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Authors: Emiliano Matta

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Passive resonant vibration absorbers are among the most widely used dynamic control systems in civil engineering. They typically consist in a single-degree-of-freedom mechanical appendage of the main structure, tuned to one structural target mode through frequency and damping optimization. One classical scheme is the pendulum absorber, whose mass is constrained to move along a curved trajectory and is damped by viscous dashpots. Even though the principle is well known, the search for improved arrangements is still under way. In recent years this investigation inspired a type of bidirectional pendulum absorber (BPA), consisting of a mass constrained to move along an optimal three-dimensional (3D) concave surface. For such a BPA, the surface principal curvatures are designed to ensure a bidirectional tuning of the absorber to both principal modes of the main structure, while damping is produced either by horizontal viscous dashpots or by vertical friction dashpots, connecting the BPA to the main structure. In this paper, a variant of BPA is proposed, where damping originates from the variable tangential friction force which develops between the pendulum mass and the 3D surface as a result of a spatially-varying friction coefficient pattern. Namely, a friction coefficient is proposed that varies along the pendulum surface in proportion to the modulus of the 3D surface gradient. With such an assumption, the dissipative model of the absorber can be proven to be nonlinear homogeneous in the small displacement domain. The resulting homogeneous BPA (HBPA) has a fundamental advantage over conventional friction-type absorbers, because its equivalent damping ratio results independent on the amplitude of oscillations, and therefore its optimal performance does not depend on the excitation level. On the other hand, the HBPA is more compact than viscously damped BPAs because it does not need the installation of dampers. This paper presents the analytical model of the HBPA and an optimal methodology for its design. Numerical simulations of single- and multi-story building structures under wind and earthquake loads are presented to compare the HBPA with classical viscously damped BPAs. It is shown that the HBPA is a promising alternative to existing BPA types and that homogeneous tangential friction is an effective means to realize systems provided with amplitude-independent damping.

Keywords: amplitude-independent damping, homogeneous friction, pendulum nonlinear dynamics, structural control, vibration resonant absorbers

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Authors: Calister Wingang Makebe, Wilson Agwanande Ambindei, Zangue Steve Carly Desobgo, Abraham Billu, Emmanuel Jong Nso, P. Nisha

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Traditional liquid-state fermentation processes of Annona muricata L. juice can result in fluctuating product quality and quantity due to difficulties in control and scale up. This work describes a laboratory-scale batch fermentation process to produce a probiotic Annona muricata L. enzymatically extracted juice, which was modeled using the Doehlert design with independent extraction factors being incubation time, temperature, and enzyme concentration. It aimed at a better understanding of the traditional process as an initial step for future optimization. Annona muricata L. juice was fermented with L. acidophilus (NCDC 291) (LA), L. casei (NCDC 17) (LC), and a blend of LA and LC (LCA) for 72 h at 37 °C. Experimental data were fitted into mathematical models (Monod, Logistic and Luedeking and Piret models) using MATLAB software, to describe biomass growth, sugar utilization, and organic acid production. The optimal fermentation time was obtained based on cell viability, which was 24 h for LC and 36 h for LA and LCA. The model was particularly effective in estimating biomass growth, reducing sugar consumption, and lactic acid production. The values of the determination coefficient, R2, were 0.9946, 0.9913 and 0.9946, while the residual sum of square error, SSE, was 0.2876, 0.1738 and 0.1589 for LC, LA and LCA, respectively. The growth kinetic parameters included the maximum specific growth rate, µm, which was 0.2876 h-1, 0.1738 h-1 and 0.1589 h-1, as well as the substrate saturation, Ks, with 9.0680 g/L, 9.9337 g/L and 9.0709 g/L respectively for LC, LA and LCA. For the stoichiometric parameters, the yield of biomass based on utilized substrate (YXS) was 50.7932, 3.3940 and 61.0202, and the yield of product based on utilized substrate (YPS) was 2.4524, 0.2307 and 0.7415 for LC, LA, and LCA, respectively. In addition, the maintenance energy parameter (ms) was 0.0128, 0.0001 and 0.0004 with respect to LC, LA and LCA. With the kinetic model proposed by Luedeking and Piret for lactic acid production rate, the growth associated and non-growth associated coefficients were determined as 1.0028 and 0.0109, respectively. The model was demonstrated for batch growth of LA, LC, and LCA in Annona muricata L. juice. The present investigation validates the potential of Annona muricata L. based medium for heightened economical production of a probiotic medium.

Keywords: L. acidophilus, L. casei, fermentation, modelling, kinetics

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Authors: Alejandra Torres-Landa López

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Introduction: Can architecture students be creative in spaces conformed by an educational infrastructure build with paradigms of the past?, this question and others related are answered in this paper as it presents the PhD research: An anthropic conflict in Mexican Higher Education Institutes, problems and challenges of the educational infrastructure in teaching and learning History of Architecture. This research was finished in 2013 and is one of the first studies conducted nationwide in Mexico that analysis the educational infrastructure impact in learning architecture; its objective was to identify which elements of the educational infrastructure of Mexican Higher Education Institutes where architects are formed, hinder or contribute to the teaching and learning of History of Architecture; how and why it happens. The methodology: A mixed methodology was used combining quantitative and qualitative analysis. Different resources and strategies for data collection were used, such as questionnaires for students and teachers, interviews to architecture research experts, direct observations in Architecture classes, among others; the data collected was analyses using SPSS and MAXQDA. The veracity of the quantitative data was supported by the Cronbach’s Alpha Coefficient, obtaining a 0.86, figure that gives the data enough support. All the above enabled to certify the anthropic conflict in which Mexican Universities are. Major findings of the study: Although some of findings were probably not unknown, they haven’t been systematized and analyzed with the depth to which it’s done in this research. So, it can be said, that the educational infrastructure of most of the Higher Education Institutes studied, is a barrier to the educational process, some of the reasons are: the little morphological variation of space, the inadequate control of lighting, noise, temperature, equipment and furniture, the poor or none accessibility for disable people; as well as the absence, obsolescence and / or insufficiency of information technologies are some of the issues that generate an anthropic conflict understanding it as the trouble that teachers and students have to relate between them, in order to achieve significant learning). It is clear that most of the educational infrastructure of Mexican Higher Education Institutes is anchored to paradigms of the past; it seems that they respond to the previous era of industrialization. The results confirm that the educational infrastructure of Mexican Higher Education Institutes where architects are formed, is perceived as a "closed container" of people and data; infrastructure that becomes a barrier to teaching and learning process. Conclusion: The research results show it's time to change the paradigm in which we conceive the educational infrastructure, it’s time to stop seen it just only as classrooms, workshops, laboratories and libraries, as it must be seen from a constructive, urban, architectural and human point of view, taking into account their different dimensions: physical, technological, documental, social, among others; so the educational infrastructure can become a set of elements that organize and create spaces where ideas and thoughts can be shared; to be a social catalyst where people can interact between each other and with the space itself.

Keywords: educational infrastructure, impact of space in learning architecture outcomes, learning environments, teaching architecture, learning architecture

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Authors: Jean Pierre Kabue, Emma Meader, Afsatou Ndama Traore, Paul R. Hunter, Natasha Potgieter

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Norovirus is now considered the most common cause of outbreaks of nonbacterial gastroenteritis. Limited data are available for Norovirus strains in Africa, especially in rural and peri-urban areas. Despite the excessive burden of diarrhea disease in developing countries, Norovirus infections have been to date mostly reported in developed countries. There is a need to investigate intensively the role of viral agents associated with diarrhea in different settings in Africa continent. To determine the prevalence and genetic diversity of Norovirus strains circulating in the rural communities in the Limpopo Province, South Africa and investigate the genetic relationship between Norovirus strains, a cross-sectional study was performed on human stools collected from rural communities. Between July 2014 and April 2015, outpatient children under 5 years of age from rural communities of Vhembe District, South Africa, were recorded for the study. A total of 303 stool specimens were collected from those with diarrhea (n=253) and without (n=50) diarrhea. NoVs were identified using real-time one-step RT-PCR. Partial Sequence analyses were performed to genotype the strains. Phylogenetic analyses were performed to compare identified NoVs genotypes to the worldwide circulating strains. Norovirus detection rate was 41.1% (104/253) in children with diarrhea. There was no significant difference (OR=1.24; 95% CI 0.66-2.33) in Norovirus detection between symptomatic and asymptomatic children. Comparison of the median CT values for NoV in children with diarrhea and without diarrhea revealed significant statistical difference of estimated GII viral load from both groups, with a much higher viral burden in children with diarrhea. To our knowledge, this is the first study reporting on the differences in estimated viral load of GII and GI NoV positive cases and controls. GII.Pe (n=9) were the predominant genotypes followed by GII.Pe/GII.4 Sydney 2012 (n=8) suspected recombinant and GII.4 Sydney 2012 variants(n=7). Two unassigned GII.4 variants and an unusual RdRp genotype GII.P15 were found. With note, the rare GIIP15 identified in this study has a common ancestor with GIIP15 strain from Japan previously reported as GII/untypeable recombinant strain implicated in a gastroenteritis outbreak. To our knowledge, this is the first report of this unusual genotype in the African continent. Though not confirmed predictive of diarrhea disease in this study, the high detection rate of NoV is an indication of subsequent exposure of children from rural communities to enteric pathogens due to poor sanitation and hygiene practices. The results reveal that the difference between asymptomatic and symptomatic children with NoV may possibly be related to the NoV genogroups involved. The findings emphasize NoV genetic diversity and predominance of GII.Pe/GII.4 Sydney 2012, indicative of increased NoV activity. An uncommon GII.P15 and two unassigned GII.4 variants were also identified from rural settings of the Vhembe District/South Africa. NoV surveillance is required to help to inform investigations into NoV evolution, and to support vaccine development programmes in Africa.

Keywords: asymptomatic, common, outpatients, norovirus genetic diversity, sporadic gastroenteritis, South African rural communities, symptomatic

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Authors: Imed Feki, Faouzi Msahli

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Selection of relevant parameters from a high dimensional process operation setting space is a problem frequently encountered in industrial process modelling. This paper presents a method for selecting the most relevant fabric physical parameters for each sensory quality feature. The proposed relevancy criterion has been developed using two approaches. The first utilizes a fuzzy sensitivity criterion by exploiting from experimental data the relationship between physical parameters and all the sensory quality features for each evaluator. Next an OWA aggregation procedure is applied to aggregate the ranking lists provided by different evaluators. In the second approach, another panel of experts provides their ranking lists of physical features according to their professional knowledge. Also by applying OWA and a fuzzy aggregation model, the data sensitivity-based ranking list and the knowledge-based ranking list are combined using our proposed percolation technique, to determine the final ranking list. The key issue of the proposed percolation technique is to filter automatically and objectively the relevant features by creating a gap between scores of relevant and irrelevant parameters. It permits to automatically generate threshold that can effectively reduce human subjectivity and arbitrariness when manually choosing thresholds. For a specific sensory descriptor, the threshold is defined systematically by iteratively aggregating (n times) the ranking lists generated by OWA and fuzzy models, according to a specific algorithm. Having applied the percolation technique on a real example, of a well known finished textile product especially the stonewashed denims, usually considered as the most important quality criteria in jeans’ evaluation, we separate the relevant physical features from irrelevant ones for each sensory descriptor. The originality and performance of the proposed relevant feature selection method can be shown by the variability in the number of physical features in the set of selected relevant parameters. Instead of selecting identical numbers of features with a predefined threshold, the proposed method can be adapted to the specific natures of the complex relations between sensory descriptors and physical features, in order to propose lists of relevant features of different sizes for different descriptors. In order to obtain more reliable results for selection of relevant physical features, the percolation technique has been applied for combining the fuzzy global relevancy and OWA global relevancy criteria in order to clearly distinguish scores of the relevant physical features from those of irrelevant ones.

Keywords: data sensitivity, feature selection, fuzzy logic, OWA operators, percolation technique

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Authors: Murray David Schane

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Though years of clinical encounters with patients with autism spectrum disorders and those with a schizoid personality the many defining diagnostic features shared between these conditions have been explored and current neurobiological differences have been reviewed; and, critical and different treatment strategies for each have been devised. The paper compares and contrasts the apparent similarities between autism spectrum disorders and the schizoid personality are found in these DSM descriptive categories: restricted range of social-emotional reciprocity; poor non-verbal communicative behavior in social interactions; difficulty developing and maintaining relationships; detachment from social relationships; lack of the desire for or enjoyment of close relationships; and preference for solitary activities. In this paper autism, fundamentally a communicative disorder, is revealed to present clinically as a pervasive aversive response to efforts to engage with or be engaged by others. Autists with the Asperger presentation typically have language but have difficulty understanding humor, irony, sarcasm, metaphoric speech, and even narratives about social relationships. They also tend to seek sameness, possibly to avoid problems of social interpretation. Repetitive behaviors engage many autists as a screen against ambient noise, social activity, and challenging interactions. Also in this paper, the schizoid personality is revealed as a pattern of social avoidance, self-sufficiency and apparent indifference to others as a complex psychological defense against a deep, long-abiding fear of appropriation and perverse manipulation. Neither genetic nor MRI studies have yet located the explanatory data that identifies the cause or the neurobiology of autism. Similarly, studies of the schizoid have yet to group that condition with those found in schizophrenia. Through presentations of clinical examples, the treatment of autists of the Asperger type is revealed to address the autist’s extreme social aversion which also precludes the experience of empathy. Autists will be revealed as forming social attachments but without the capacity to interact with mutual concern. Empathy will be shown be teachable and, as social avoidance relents, understanding of the meaning and signs of empathic needs that autists can recognize and acknowledge. Treatment of schizoids will be shown to revolve around joining empathically with the schizoid’s apprehensions about interpersonal, interactive proximity. Models of both autism and schizoid personality traits have yet to be replicated in animals, thereby eliminating the role of translational research in providing the kind of clues to behavioral patterns that can be related to genetic, epigenetic and neurobiological measures. But as these clinical examples will attest, treatment strategies have significant impact.

Keywords: autism spectrum, schizoid personality traits, neurobiological implications, critical diagnostic distinctions

Procedia PDF Downloads 90

Authors: Marita Heyns

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Job insecurity is a distressing phenomenon which has far reaching consequences for both employees and their organizations. Previously, much attention has been given to the link between job insecurity and individual level performance outcomes, while less is known about how subjectively perceived job insecurity might transfer beyond the individual level to affect performance of the organization on an aggregated level. Research focusing on how employees’ fear of job loss might affect the organization’s ability to respond proactively to volatility and drastic change through applying its capabilities of sensing, seizing, and reconfiguring, appears to be practically non-existent. Equally little is known about the potential underlying mechanisms through which job insecurity might affect the dynamic capabilities of an organization. This study examines how job insecurity might affect dynamic organizational capability through trust as an underling process. More specifically, it considered the simultaneous roles of trust at an impersonal (organizational) level as well as trust at an interpersonal level (in leaders and co-workers) as potential underlying mechanisms through which job insecurity might affect the organization’s dynamic capability to respond to opportunities and imminent, drastic change. A quantitative research approach and a stratified random sampling technique enabled the collection of data among 314 managers at four different plant sites of a large South African steel manufacturing organization undergoing dramatic changes. To assess the study hypotheses, the following statistical procedures were employed: Structural equation modelling was performed in Mplus to evaluate the measurement and structural models. The Chi-square values test for absolute fit as well as alternative fit indexes such as the Comparative Fit Index and the Tucker-Lewis Index, the Root Mean Square Error of Approximation and the Standardized Root Mean Square Residual were used as indicators of model fit. Composite reliabilities were calculated to evaluate the reliability of the factors. Finally, interaction effects were tested by using PROCESS and the construction of two-sided 95% confidence intervals. The findings indicate that job insecurity had a lower-than-expected detrimental effect on evaluations of the organization’s dynamic capability through the conducive buffering effects of trust in the organization and in its leaders respectively. In contrast, trust in colleagues did not seem to have any noticeable facilitative effect. The study proposes that both job insecurity and dynamic capability can be managed more effectively by also paying attention to factors that could promote trust in the organization and its leaders; some practical recommendations are given in this regard.

Keywords: dynamic organizational capability, impersonal trust, interpersonal trust, job insecurity

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Authors: M. J. Baum, B. Gibbes, A. Grinham, S. Albert, D. Gale, P. Fisher

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Alongside the rapid expansion of Seawater Reverse Osmosis technologies there is a concurrent increase in the production of hypersaline brine by-products. To minimize environmental impact, these by-products are commonly disposed into open-coastal environments via submerged diffuser systems as inclined dense jet outfalls. Despite the widespread implementation of this process, diffuser designs are typically based on small-scale laboratory experiments under idealistic quiescent conditions. Studies concerning diffuser performance in the field are limited. A set of experiments were conducted to assess the near field characteristics of brine disposal at the Gold Coast Desalination Plant offshore multiport diffuser. The aim of the field experiments was to determine the trajectory and dilution characteristics of the plume under various discharge configurations with production ranging 66 – 100% of plant operative capacity. The field monitoring system employed an unprecedented static array of temperature and electrical conductivity sensors in a three-dimensional grid surrounding a single diffuser port. Complimenting these measurements, Acoustic Doppler Current Profilers were also deployed to record current variability over the depth of the water column and wave characteristics. Recorded data suggested the open-coastal environment was highly active over the experimental duration with ambient velocities ranging 0.0 – 0.5 m∙s^-1, with considerable variability over the depth of the water column observed. Variations in background electrical conductivity corresponding to salinity fluctuations of ± 1.7 g∙kg^-1 were also observed. Increases in salinity were detected during plant operation and appeared to be most pronounced 10 – 30 m from the diffuser, consistent with trajectory predictions described by existing literature. Plume trajectories and respective dilutions extrapolated from salinity data are compared with empirical scaling arguments. Discharge properties were found to adequately correlate with modelling projections. Temporal and spatial variation of background processes and their subsequent influence upon discharge outcomes are discussed with a view to incorporating the influence of waves and ambient currents in the design of brine outfalls into the future.

Keywords: brine disposal, desalination, field study, negatively buoyant discharge

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Authors: Chyong-Ru Liu, Wen-Shiung Huang, Wan-Ching Tang, Shan-Pei Chen

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Two of the biggest challenges companies involved in sports and exercise information services face are how to strengthen participation in virtual sports/exercise communities and how to increase the ongoing participatoriness of those communities. In the past, relatively little research has explored mechanisms for strengthening alignment practice and community response from the perspective of self-construal, and as such this study seeks to explore the self-construal of virtual sports/exercise communities, the role it plays in the emotional commitment of forming communities, and the factor that can strengthen alignment practice. Moreover, which factor of the emotional commitment of forming virtual communities have the effect of strengthening interference in the process of transforming customer citizenship behaviors? This study collected 625 responses from the two leading websites in terms of fan numbers in the provision of information on road race and marathon events in Taiwan, with model testing conducted through linear structural equation modelling and the bootstrapping technique to test the proposed hypotheses. The results proved independent construal had a stronger positive direct effect on affective commitment to fellow customers than did interdependent construal, and the influences of affective commitment to fellow customers in enhancing customer citizenship behavior. Public self-consciousness moderates the relationships among independent self-construal and interdependent self-construal on effective commitment to fellow customers. Perceived playfulness moderates the relationships between effective commitment to fellow customers and customer citizenship behavior. The findings of this study provide significant insights for the researchers and related organizations. From the theoretical perspective, this is empirical research that investigated the self-construal theory and responses (i.e., affective commitment to fellow customers, customer citizenship behavior) in virtual sports/exercise communities. We further explore how to govern virtual sports/exercise community participants’ heterogeneity through public self-consciousness mechanism to align participants’ affective commitment. Moreover, perceived playfulness has the effect of strengthening effective commitment to fellow customers with customer citizenship behaviors. The results of this study can provide a foundation for the construction of future theories and can be provided to related organizations for reference in their planning of virtual communities.

Keywords: self-construal theory, public self-consciousness, affective commitment, customer citizenship behavior

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Authors: Dimakatso Machetele, Kowiyou Yessoufou

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Whilst several studies indicated that road accident events might be more complex than thought, we have a limited scientific understanding of this complexity in South Africa. The present project proposes and tests a more comprehensive metamodel that integrates multiple causality relationships among variables previously linked to road accidents. This was done by fitting a structural equation model (SEM) to the data collected from various sources. The study also fitted the GARCH Model (Generalized Auto-Regressive Conditional Heteroskedasticity) to predict the future of road accidents in the country. The analysis shows that the number of road accidents has been increasing since 1935. The road fatality rate follows a polynomial shape following the equation: y = -0.0114x²+1.2378x-2.2627 (R²=0.76) with y = death rate and x = year. This trend results in an average death rate of 23.14 deaths per 100,000 people. Furthermore, the analysis shows that the number of crashes could be significantly explained by the total number of vehicles (P < 0.001), number of registered vehicles (P < 0.001), number of unregistered vehicles (P = 0.003) and the population of the country (P < 0.001). As opposed to expectation, the number of driver licenses issued and total distance traveled by vehicles do not correlate significantly with the number of crashes (P > 0.05). Furthermore, the analysis reveals that the number of casualties could be linked significantly to the number of registered vehicles (P < 0.001) and total distance traveled by vehicles (P = 0.03). As for the number of fatal crashes, the analysis reveals that the total number of vehicles (P < 0.001), number of registered (P < 0.001) and unregistered vehicles (P < 0.001), the population of the country (P < 0.001) and the total distance traveled by vehicles (P < 0.001) correlate significantly with the number of fatal crashes. However, the number of casualties and again the number of driver licenses do not seem to determine the number of fatal crashes (P > 0.05). Finally, the number of crashes is predicted to be roughly constant overtime at 617,253 accidents for the next 10 years, with the worse scenario suggesting that this number may reach 1 896 667. The number of casualties was also predicted to be roughly constant at 93 531 overtime, although this number may reach 661 531 in the worst-case scenario. However, although the number of fatal crashes may decrease over time, it is forecasted to reach 11 241 fatal crashes within the next 10 years, with the worse scenario estimated at 19 034 within the same period. Finally, the number of fatalities is also predicted to be roughly constant at 14 739 but may also reach 172 784 in the worse scenario. Overall, the present study reveals the complexity of road accidents and allows us to propose several recommendations aimed to reduce the trend of road accidents, casualties, fatal crashes, and death in South Africa.

Keywords: road accidents, South Africa, statistical modelling, trends

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Authors: Javier E. García-Gallo, Nelson J. Fonseca-Ruiz, John F. Duitama-Munoz

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Sepsis is a syndrome that occurs with physiological and biochemical abnormalities induced by severe infection and carries a high mortality and morbidity, therefore the severity of its condition must be interpreted quickly. After patient admission in an intensive care unit (ICU), it is necessary to synthesize the large volume of information that is collected from patients in a value that represents the severity of their condition. Traditional severity of illness scores seeks to be applicable to all patient populations, and usually assess in-hospital mortality. However, the use of machine learning techniques and the data of a population that shares a common characteristic could lead to the development of customized mortality prediction scores with better performance. This study presents the development of a score for the one-year mortality prediction of the patients that are admitted to an ICU with a sepsis diagnosis. 5650 ICU admissions extracted from the MIMICIII database were evaluated, divided into two groups: 70% to develop the score and 30% to validate it. Comorbidities, demographics and clinical information of the first 24 hours after the ICU admission were used to develop a mortality prediction score. LASSO (least absolute shrinkage and selection operator) and SGB (Stochastic Gradient Boosting) variable importance methodologies were used to select the set of variables that make up the developed score; each of this variables was dichotomized and a cut-off point that divides the population into two groups with different mean mortalities was found; if the patient is in the group that presents a higher mortality a one is assigned to the particular variable, otherwise a zero is assigned. These binary variables are used in a logistic regression (LR) model, and its coefficients were rounded to the nearest integer. The resulting integers are the point values that make up the score when multiplied with each binary variables and summed. The one-year mortality probability was estimated using the score as the only variable in a LR model. Predictive power of the score, was evaluated using the 1695 admissions of the validation subset obtaining an area under the receiver operating characteristic curve of 0.7528, which outperforms the results obtained with Sequential Organ Failure Assessment (SOFA), Oxford Acute Severity of Illness Score (OASIS) and Simplified Acute Physiology Score II (SAPSII) scores on the same validation subset. Observed and predicted mortality rates within estimated probabilities deciles were compared graphically and found to be similar, indicating that the risk estimate obtained with the score is close to the observed mortality, it is also observed that the number of events (deaths) is indeed increasing as the outcome go from the decile with the lowest probabilities to the decile with the highest probabilities. Sepsis is a syndrome that carries a high mortality, 43.3% for the patients included in this study; therefore, tools that help clinicians to quickly and accurately predict a worse prognosis are needed. This work demonstrates the importance of customization of mortality prediction scores since the developed score provides better performance than traditional scoring systems.

Keywords: intensive care, logistic regression model, mortality prediction, sepsis, severity of illness, stochastic gradient boosting

Procedia PDF Downloads 187

Authors: Champika Amarasinghe

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Introduction: Covid 19 pandemic was badly hit to the Sri Lankan economy during the year 2021. More than 65% of the Sri Lankan work force is engaged with small and medium scale businesses which no doubt that they had to struggle for their survival and business continuity during the pandemic. Objective: To assess the association of adherence to the new norms during the Covid 19 pandemic and maintenance of healthy working environmental conditions for business continuity. A cross sectional study was carried out to assess the OSH status and adequacy of Covid 19 preventive strategies among the 200 SME’S in selected two districts in Sri Lanka. These two districts were selected considering the highest availability of SME’s. Sample size was calculated, and probability propionate to size was used to select the SME’s which were registered with the small and medium scale development authority. An interviewer administrated questionnaire was used to collect the data, and OSH risk assessment was carried out by a team of experts to assess the OSH status in these industries. Results: According to the findings, more than 90% of the employees in these industries had a moderate awareness related to COVID 19 disease and preventive strategies such as the importance of Mask use, hand sainting practices, and distance maintenance, but the only forty percent of them were adhered to implementation of these practices. Furthermore, only thirty five percent of the employees and employers in these SME’s new the reasons behind the new norms, which may be the reason for reluctance to implement these strategies and reluctance to adhering to the new norms in this sector. The OSH risk assessment findings revealed that the working environmental organization while maintaining the distance between two employees was poor due to the inadequacy of space in these entities. More than fifty five percent of the SME’s had proper ventilation and lighting facilities. More than eighty five percent of these SME’s had poor electrical safety measures. Furthermore, eighty two percent of them had not maintained fire safety measures. Eighty five percent of them were exposed to heigh noise levels and chemicals where they were not using any personal protectives nor any other engineering controls were not imposed. Floor conditions were poor, and they were not maintaining the occupational accident nor occupational disease diseases. Conclusions: Based on the findings, proper awareness sessions were carried out by NIOSH. Six physical training sessions and continues online trainings were carried out to overcome these issues, which made a drastic change in their working environments and ended up with hundred percent implementation of the Covid 19 preventive strategies, which intern improved the worker participation in the businesses. Reduced absentees and improved business opportunities, and continued their businesses without any interruption during the third episode of Covid 19 in Sri Lanka.

Keywords: working environment, Covid 19, occupational diseases, occupational accidents

Procedia PDF Downloads 66

Authors: Christine Winberg, James Garraway

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Many key university documents, such as vision and mission statements and strategic plans, are aspirational and future-oriented. There is a wide range of future-oriented methods that are used in planning applications, ranging from mathematical modelling to expert opinions. Many of these methods have limitations, and planners using these tools might, for example, make the technical-rational assumption that their plans will unfold in a logical and inevitable fashion, thus underestimating the many complex forces that are at play in planning for an unknown future. This is the issue that this study addresses. The overall project aim was to assist a new university of technology in developing appropriate responses to its social responsibility, graduate employability and research missions in its strategic plan. The specific research question guiding the research activities and approach was: how might the use of innovative future-oriented planning tools enable or constrain a strategic planning process? The research objective was to engage collaborating groups in the use of an innovative tool to develop and assess future scenarios, for the purpose of developing deeper understandings of possible futures and their challenges. The scenario planning tool chosen was ‘fictive scripting’, an analytical technique derived from Technology Forecasting and Innovation Studies. Fictive scripts are future projections that also take into account the present shape of the world and current developments. The process thus began with a critical diagnosis of the present, highlighting its tensions and frictions. The collaborative groups then developed fictive scripts, each group producing a future scenario that foregrounded different institutional missions, their implications and possible consequences. The scripts were analyzed with a view to identifying their potential contribution to the university’s strategic planning exercise. The unfolding fictive scripts revealed a number of insights in terms of unexpected benefits, unexpected challenges, and unexpected consequences. These insights were not evident in previous strategic planning exercises. The contribution that this study offers is to show how better choices can be made and potential pitfalls avoided through a systematic foresight exercise. When universities develop strategic planning documents, they are looking into the future. In this paper it is argued that the use of appropriate tools for future-oriented exercises, can help planners to understand more fully what achieving desired outcomes might entail, what challenges might be encountered, and what unexpected consequences might ensue.

Keywords: fictive scripts, scenarios, strategic planning, technological forecasting

Procedia PDF Downloads 101

Authors: Iraklis Argyriou

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The transition to net-zero emission urban bus (ZEB) systems is receiving increased attention in research and policymaking throughout the globe. Most studies in this area tend to address techno-economic aspects and the perspectives of a narrow group of stakeholders, while they largely overlook analysis of current bus system dynamics. This offers limited insight into the types of ZEB governance challenges and opportunities that are encountered in real-world contexts, as well as into some of the immediate actions that need to be taken to set off the transition over the longer term. This research offers a multi-stakeholder perspective into both the technical and non-technical factors that influence ZEB transitions within a particular context, the UK. It does so by drawing from a recent transition visioning stakeholder workshop (June 2023) with key public, private and civic actors of the urban bus transportation system. Using NVivo software to qualitatively analyze the workshop discussions, the research examines the key technological and funding aspects, as well as the short-term actions (over the next five years), that need to be addressed for supporting the ZEB transition in UK cities. It finds that ZEB technology has reached a mature stage (i.e., high efficiency of batteries, motors and inverters), but important improvements can be pursued through greater control and integration of ZEB technological components and systems. In this regard, telemetry, predictive maintenance and adaptive control strategies pertinent to the performance and operation of ZEB vehicles have a key role to play in the techno-economic advancement of the transition. Yet, more pressing gaps were identified in the current ZEB funding regime. Whereas the UK central government supports greater ZEB adoption through a series of grants and subsidies, the scale of the funding and its fragmented nature do not match the needs for a UK-wide transition. Funding devolution arrangements (i.e., stable funding settlement deals between the central government and the devolved administrations/local authorities), as well as locally-driven schemes (i.e., congestion charging/workplace parking levy), could then enhance the financial prospects of the transition. As for short-term action, three areas were identified as critical: (1) the creation of whole value chains around the supply, use and recycling of ZEB components; (2) the ZEB retrofitting of existing fleets; and (3) integrated transportation that prioritizes buses as a first-choice, convenient and reliable mode while it simultaneously reduces car dependency in urban areas. Taken together, the findings point to the need for place-based transition approaches that create a viable techno-economic ecosystem for ZEB development but at the same time adopt a broader governance perspective beyond a ‘net-zero’ and ‘bus sectoral’ focus. As such, multi-actor collaborations and the coordination of wider resources and agency, both vertically across institutional scales and horizontally across transport, energy and urban planning, become fundamental features of comprehensive ZEB responses. The lessons from the UK case can inform a broader body of empirical contextual knowledge of ZEB transition governance within domestic political economies of public transportation.

Keywords: net-zero emission transition, stakeholders, transition governance, UK, urban bus transportation

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Authors: Akshay B. Pawar, Rohit Y. Parasnis

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Heart Rate Variability (HRV) is a widely used indicator of the regulation between the autonomic nervous system (ANS) and the cardiovascular system. Besides being non-invasive, it also has the potential to predict mortality in cases involving critical injuries. The gold standard method for determining HRV is based on the analysis of RR interval time series extracted from ECG signals. However, because it is much more convenient to obtain photoplethysmogramic (PPG) signals as compared to ECG signals (which require the attachment of several electrodes to the body), many researchers have used pulse cycle intervals instead of RR intervals to estimate HRV. They have also compared this method with the gold standard technique. Though most of their observations indicate a strong correlation between the two methods, recent studies show that in healthy subjects, except for a few parameters, the pulse-based method cannot be a surrogate for the standard RR interval- based method. Moreover, the former tends to overestimate short-term variability in heart rate. This calls for improvements in or alternatives to the pulse-cycle interval method. In this study, besides the systolic peak-peak interval method (PP method) that has been studied several times, four recent PPG-based techniques, namely the first derivative peak-peak interval method (P1D method), the second derivative peak-peak interval method (P2D method), the valley-valley interval method (VV method) and the tangent-intersection interval method (TI method) were compared with the gold standard technique. ECG and PPG signals were obtained from 10 young and healthy adults (consisting of both males and females) seated in the armchair position. In order to de-noise these signals and eliminate baseline drift, they were passed through certain digital filters. After filtering, the following HRV parameters were computed from PPG using each of the five methods and also from ECG using the gold standard method: time domain parameters (SDNN, pNN50 and RMSSD), frequency domain parameters (Very low-frequency power (VLF), Low-frequency power (LF), High-frequency power (HF) and Total power or “TP”). Besides, Poincaré plots were also plotted and their SD1/SD2 ratios determined. The resulting sets of parameters were compared with those yielded by the standard method using measures of statistical correlation (correlation coefficient) as well as statistical agreement (Bland-Altman plots). From the viewpoint of correlation, our results show that the best PPG-based methods for the determination of most parameters and Poincaré plots are the P2D method (shows more than 93% correlation with the standard method) and the PP method (mean correlation: 88%) whereas the TI, VV and P1D methods perform poorly (<70% correlation in most cases). However, our evaluation of statistical agreement using Bland-Altman plots shows that none of the five techniques agrees satisfactorily well with the gold standard method as far as time-domain parameters are concerned. In conclusion, excellent statistical correlation implies that certain PPG-based methods provide a good amount of information on the pattern of heart rate variation, whereas poor statistical agreement implies that PPG cannot completely replace ECG in the determination of HRV.

Keywords: photoplethysmography, heart rate variability, correlation coefficient, Bland-Altman plot

Procedia PDF Downloads 294

Authors: Volker Landersheim, Daria Manushyna, Thinh Pham, Dai-Duong Tran, Thomas Geury, Omar Hegazy, Steven Wilkins

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Air pollution is one of the emerging problems in our society. Targets of reduction of CO₂ emissions address low-carbon and resource-efficient transport. (Plug-in) hybrid electric propulsion concepts offer the possibility to reduce total cost of ownership (TCO) and emissions for public transport vehicles (e.g., bus application). In this context, typically, diesel engines are used to form the hybrid propulsion system of the vehicle. Though the technological development of diesel engines experience major advantages, some challenges such as the high amount of particle emissions remain relevant. Gaseous fuels (i.e., compressed natural gases (CNGs) or liquefied petroleum gases (LPGs) represent an attractive alternative to diesel because of their composition. In the framework of the research project 'Optimised Real-world Cost-Competitive Modular Hybrid Architecture' (ORCA), which was funded by the EU, two different hybrid-electric propulsion concepts have been investigated: one using a diesel engine as internal combustion engine and one using CNG as fuel. The aim of the current study is to analyze specific benefits for the aforementioned hybrid propulsion systems for predefined driving scenarios with regard to emissions and total cost of ownership in bus application. Engine models based on experimental data for diesel and CNG were developed. For the purpose of designing optimal energy management strategies for each propulsion system, maps-driven or quasi-static models for specific engine types are used in the simulation framework. An analogous modelling approach has been chosen to represent emissions. This paper compares the two concepts regarding their CO₂ and NOx emissions. This comparison is performed for relevant bus missions (urban, suburban, with and without zero-emission zone) and with different energy management strategies. In addition to the emissions, also the downsizing potential of the combustion engine has been analysed to minimize the powertrain TCO (pTCO) for plug-in hybrid electric buses. The results of the performed analyses show that the hybrid vehicle concept using the CNG engine shows advantages both with respect to emissions as well as to pTCO. The pTCO is 10% lower, CO₂ emissions are 13% lower, and the NOx emissions are more than 50% lower than with the diesel combustion engine. These results are consistent across all usage profiles under investigation.

Keywords: bus transport, emissions, hybrid propulsion, pTCO, CNG

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Authors: Zheng Wang, Zhenhong Li, Jon Mills

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Ground-based synthetic aperture radar (GBSAR) represents a powerful remote sensing tool for deformation monitoring towards various geohazards, e.g. landslides, mudflows, avalanches, infrastructure failures, and the subsidence of residential areas. Unlike spaceborne SAR with a fixed revisit period, GBSAR data can be acquired with an adjustable temporal resolution through either continuous or discontinuous operation. However, challenges arise from processing high temporal-resolution continuous GBSAR data, including the extreme cost of computational random-access-memory (RAM), the delay of displacement maps, and the loss of temporal evolution. Moreover, repositioning errors between discontinuous campaigns impede the accurate measurement of surface displacements. Therefore, a versatile package with two complete chains is developed in this study in order to process both continuous and discontinuous GBSAR data and address the aforementioned issues. The first chain is based on a small-baseline subset concept and it processes continuous GBSAR images unit by unit. Images within a window form a basic unit. By taking this strategy, the RAM requirement is reduced to only one unit of images and the chain can theoretically process an infinite number of images. The evolution of surface displacements can be detected as it keeps temporarily-coherent pixels which are present only in some certain units but not in the whole observation period. The chain supports real-time processing of the continuous data and the delay of creating displacement maps can be shortened without waiting for the entire dataset. The other chain aims to measure deformation between discontinuous campaigns. Temporal averaging is carried out on a stack of images in a single campaign in order to improve the signal-to-noise ratio of discontinuous data and minimise the loss of coherence. The temporal-averaged images are then processed by a particular interferometry procedure integrated with advanced interferometric SAR algorithms such as robust coherence estimation, non-local filtering, and selection of partially-coherent pixels. Experiments are conducted using both synthetic and real-world GBSAR data. Displacement time series at the level of a few sub-millimetres are achieved in several applications (e.g. a coastal cliff, a sand dune, a bridge, and a residential area), indicating the feasibility of the developed GBSAR data processing package for deformation monitoring of a wide range of scientific and practical applications.

Keywords: ground-based synthetic aperture radar, interferometry, small baseline subset algorithm, deformation monitoring

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Authors: Srushti Patil, Preethi Baligar, Gopalkrishna Joshi, Gururaj N. Bhadri

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In designing learning environments, the instructional strategies can be tailored to suit the learning style of an individual to ensure effective learning. In this study, the information shared on social media like Facebook is being used to predict learning style of a learner. Previous research studies have shown that Facebook data can be used to predict user personality. Users with a particular personality exhibit an inherent pattern in their digital footprint on Facebook. The proposed work aims to correlate the user's’ personality, predicted from Facebook data to the learning styles, predicted through questionnaires. For Millennial learners, Facebook has become a primary means for information sharing and interaction with peers. Thus, it can serve as a rich bed for research and direct the design of learning environments. The authors have conducted this study in an undergraduate freshman engineering course. Data from 320 freshmen Facebook users was collected. The same users also participated in the learning style and personality prediction survey. The Kolb’s Learning style questionnaires and Big 5 personality Inventory were adopted for the survey. The users have agreed to participate in this research and have signed individual consent forms. A specific page was created on Facebook to collect user data like personal details, status updates, comments, demographic characteristics and egocentric network parameters. This data was captured by an application created using Python program. The data captured from Facebook was subjected to text analysis process using the Linguistic Inquiry and Word Count dictionary. An analysis of the data collected from the questionnaires performed reveals individual student personality and learning style. The results obtained from analysis of Facebook, learning style and personality data were then fed into an automatic classifier that was trained by using the data mining techniques like Rule-based classifiers and Decision trees. This helps to predict the user personality and learning styles by analysing the common patterns. Rule-based classifiers applied for text analysis helps to categorize Facebook data into positive, negative and neutral. There were totally two models trained, one to predict the personality from Facebook data; another one to predict the learning styles from the personalities. The results show that the classifier model has high accuracy which makes the proposed method to be a reliable one for predicting the user personality and learning styles.

Keywords: educational data mining, Facebook, learning styles, personality traits

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Authors: H. Pegram, R. Stevens, L. De Girolamo

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Aligned electrospun nanofibres act as effective neuronal and glial cell scaffolds that can be layered to contain multiple sheets harboring different cell populations. This allows personalised biofunctional prostheses to be manufactured with both acellular and cellularised layers for the treatment of spinal cord injury. Additionally, the manufacturing route may be configured to produce in-vitro 3D cell based model of spinal cord injury to aid drug development and enhance prosthesis performance. The goal of this investigation was to optimise the multi-layer scaffold design parameters for prosthesis manufacture, to enable the development of multi-layer patient specific implant therapies. The work has also focused on the fabricating aligned nanofibre scaffolds that promote in-vitro neuronal and glial cell population growth, cell-to-cell interaction and long-term survival following trauma to mimic an in-vivo spinal cord lesion. The approach has established reproducible lesions and has identified markers of trauma and regeneration marked by effective neuronal migration across the lesion with glial support. The investigation has advanced the development of an in-vitro model of traumatic spinal cord injury and has identified a route to manufacture prostheses which target the repair spinal cord injury. Evidence collated to investigate the multi-layer concept suggests that physical cues provided by nanofibres provide both a natural extra-cellular matrix (ECM) like environment and controls cell proliferation and migration. Specifically, aligned nanofibre layers act as a guidance system for migrating and elongating neurons. On a larger scale, material type in multi-layer systems also has an influence in inter-layer migration as cell types favour different material types. Results have shown that layering nanofibre membranes create a multi-level scaffold system which can enhance or prohibit cell migration between layers. It is hypothesised that modifying nanofibre layer material permits control over neuronal/glial cell migration. Using this concept, layering of neuronal and glial cells has become possible, in the context of tissue engineering and also modelling in-vitro induced lesions.

Keywords: electrospinning, layering, lesion, modeling, nanofibre

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Authors: Azam Fazelpour, Saeed Reza Dehghani, Vlastimil Masek, Yuri S. Muzychka

Abstract:

The study uses a novel image analysis based on thermal imaging to detect temperature contours created on salt ice surface during transient phenomena. Thermal cameras detect objects by using their emissivities and IR radiance. The ice surface temperature is not uniform during transient processes. The temperature starts to increase from the boundary of ice towards the center of that. Thermal cameras are able to report temperature changes on the ice surface at every individual moment. Various contours, which show different temperature areas, appear on the ice surface picture captured by a thermal camera. Identifying the exact boundary of these contours is valuable to facilitate ice surface temperature analysis. Image processing techniques are used to extract each contour area precisely. In this study, several pictures are recorded while the temperature is increasing throughout the ice surface. Some pictures are selected to be processed by a specific time interval. An image segmentation method is applied to images to determine the contour areas. Color thermal images are used to exploit the main information. Red, green and blue elements of color images are investigated to find the best contour boundaries. The algorithms of image enhancement and noise removal are applied to images to obtain a high contrast and clear image. A novel edge detection algorithm based on differences in the color of the pixels is established to determine contour boundaries. In this method, the edges of the contours are obtained according to properties of red, blue and green image elements. The color image elements are assessed considering their information. Useful elements proceed to process and useless elements are removed from the process to reduce the consuming time. Neighbor pixels with close intensities are assigned in one contour and differences in intensities determine boundaries. The results are then verified by conducting experimental tests. An experimental setup is performed using ice samples and a thermal camera. To observe the created ice contour by the thermal camera, the samples, which are initially at -20° C, are contacted with a warmer surface. Pictures are captured for 20 seconds. The method is applied to five images ,which are captured at the time intervals of 5 seconds. The study shows the green image element carries no useful information; therefore, the boundary detection method is applied on red and blue image elements. In this case study, the results indicate that proposed algorithm shows the boundaries more effective than other edges detection methods such as Sobel and Canny. Comparison between the contour detection in this method and temperature analysis, which states real boundaries, shows a good agreement. This color image edge detection method is applicable to other similar cases according to their image properties.

Keywords: color image processing, edge detection, ice contour boundary, salt ice, thermal image

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Authors: Roshanak Afrakhteh, Abdolrasoul Salman Mahini, Mahdi Motagh, Hamidreza Kamyab

Abstract:

Urban Heat Islands (UHIs) are distinctive urban areas characterized by densely populated central cores surrounded by less densely populated peripheral lands. These areas experience elevated temperatures, primarily due to impermeable surfaces and specific land use patterns. The consequences of these temperature variations are far-reaching, impacting the environment and society negatively, leading to increased energy consumption, air pollution, and public health concerns. This paper emphasizes the need for simplified approaches to comprehend UHI temperature dynamics and explains how urban development patterns contribute to land surface temperature variation. To illustrate this relationship, the study focuses on the Guilan Plain, utilizing techniques like principal component analysis and generalized additive models. The research centered on mapping land use and land surface temperature in the low-lying area of Guilan province. Satellite data from Landsat sensors for three different time periods (2002, 2012, and 2021) were employed. Using eCognition software, a spatial unit known as a "city block" was utilized through object-based analysis. The study also applied the normalized difference vegetation index (NDVI) method to estimate land surface radiance. Predictive variables for urban land surface temperature within residential city blocks were identified categorized as intrinsic (related to the block's structure) and neighboring (related to adjacent blocks) variables. Principal Component Analysis (PCA) was used to select significant variables, and a Generalized Additive Model (GAM) approach, implemented using R's mgcv package, modeled the relationship between urban land surface temperature and predictor variables.Notable findings included variations in urban temperature across different years attributed to environmental and climatic factors. Block size, shared boundary, mother polygon area, and perimeter-to-area ratio were identified as main variables for the generalized additive regression model. This model showed non-linear relationships, with block size, shared boundary, and mother polygon area positively correlated with temperature, while the perimeter-to-area ratio displayed a negative trend. The discussion highlights the challenges of predicting urban surface temperature and the significance of block size in determining urban temperature patterns. It also underscores the importance of spatial configuration and unit structure in shaping urban temperature patterns. In conclusion, this study contributes to the growing body of research on the connection between land use patterns and urban surface temperature. Block size, along with block dispersion and aggregation, emerged as key factors influencing urban surface temperature in residential areas. The proposed methodology enhances our understanding of parameter significance in shaping urban temperature patterns across various regions, particularly in Iran.

Keywords: urban heat island, land surface temperature, LST modeling, GAM, Gilan province

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