Search results for: energy models

Authors: Chante Van Tonder, Bart Bossink, Chris Schachtebeck, Cecile Nieuwenhuizen

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Small and Medium-Sized Enterprises (SMEs) play a key role in national economies around the world, being contributors to economic and social well-being. Due to this, the success, growth and competitiveness of SMEs are critical. However, there are many factors that undermine this, such as resource constraints, poor information communication infrastructure (ICT), skills shortages and poor management. The Fourth Industrial Revolution offers new tools and opportunities such as digital transformation and business model innovation (BMI) to the SME sector to enhance its competitiveness. Adopting and leveraging digital technologies such as cloud, mobile technologies, big data and analytics can significantly improve business efficiencies, value proposition and customer experiences. Digital transformation can contribute to the growth and competitiveness of SMEs. However, SMEs are lagging behind in the participation of digital transformation. Extant research lacks conceptual and empirical research on how digital transformation drives BMI and the impact it has on the growth and competitiveness of SMEs. The purpose of the study is, therefore, to close this gap by developing and empirically validating a conceptual model to determine if SMEs are achieving BMI through digital transformation and how this is impacting the growth, competitiveness and overall business performance. An empirical study is being conducted on 300 SMEs, consisting of 150 South-African and 150 Dutch SMEs, to achieve this purpose. Structural equation modeling is used, since it is a multivariate statistical analysis technique that is used to analyse structural relationships and is a suitable research method to test the hypotheses in the model. Empirical research is needed to gather more insight into how and if SMEs are digitally transformed and how BMI can be driven through digital transformation. The findings of this study can be used by SME business owners, managers and employees at all levels. The findings will indicate if digital transformation can indeed impact the growth, competitiveness and overall performance of an SME, reiterating the importance and potential benefits of adopting digital technologies. In addition, the findings will also exhibit how BMI can be achieved in light of digital transformation. This study contributes to the body of knowledge in a highly relevant and important topic in management studies by analysing the impact of digital transformation on BMI on a large number of SMEs that are distinctly different in economic and cultural factors

Keywords: business models, business model innovation, digital transformation, SMEs

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Authors: Mohammed I.A. Al-Neemi, Mohammed S.B., Al-Hlawee, Ilham N. Ezaddin, Soz A. Faris, Omer E. Fakhry, Heemen S. Mageed

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This objective of this study was to measure the effect of replacing different levels of animal protein concentrate with Red Tiger shrimp meal (RTSM: 60 % crude protein, 2400 M.E kcal/kg and the source of RTSM was imported from china) in the broiler starter diets. A total 300 broiler chicks (Ross-308) were randomly assigned in treatments dietary contained three different levels of RTSM (0.00, 4.16 and 8.32 %) in experimental diet with a completely randomized design (CRD). Each treatment included four replicates (floor pens) and 25 broilers in each replication (Pen). Therefore, floor space for each boilers was 900 cm2. Initially, the broilers where exposed to a continues lighting of 23:30 hours and dark period of 30 minutes in each 24 hours. Feed and water were supplied ad libitum to the broilers throughout the experimental period (1-21 days). The results of this study indicated that body weight (B.W.), body weight gain (B.W.G), conversion ratio of feed, protein and energy (F.CR, P.C.R and E.C.R) were significantly (p ≤ 0.05) decreased by complete substituting (RTSM) for animal protein concentration (third treatment). Mortality percentage significantly (p ≤ 0.05) increased for third dietary treatment. No significant differences were found for feed, protein and energy intake among treatments during the experimental period (three weeks). In conclusion, (RTSM) could be included to 4.16% in the broiler starter diet or substitute the protein Red Tiger shrimp as alternative of protein animal protein concentrate as much as 50%.

Keywords: red tiger shrimp, broiler, starter diet, growth performance, animal protein concentrate

Procedia PDF Downloads 559

Authors: I. D. Arroyo

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This article seeks to integrate different concepts from contemporary software engineering with an agile development approach. We seek to clarify some definitions and uses, we make a difference between the Systems Development Life Cycle (SDLC) and the methodologies, we differentiate the types of frameworks such as methodological, philosophical and behavioral, standards and documentation. We define relationships based on the documentation of the development process through formal and ad hoc models, and we define the usefulness of using DevOps and Agile Modeling as integrative methodologies of principles and best practices.

Keywords: methodologies, modeling languages, agile modeling, UML

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Authors: Sepideh Samadzadehyazdi, Mohammad Javad Khalili, Sarvenaz Samadzadehyazdi, Mohammad Javad Mahdavinejad

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The term ‘Windphil Architecture’ refers to the building that facilitates natural ventilation by architectural elements. Natural ventilation uses the natural forces of wind pressure and stacks effect to direct the movement of air through buildings. Natural ventilation is increasingly being used in contemporary buildings to minimize the consumption of non-renewable energy and it is an effective way to improve indoor air quality. The main objective of this paper is to identify the strategies of using natural ventilation in Iranian modern buildings. In this regard, the research method is ‘descriptive-analytical’ that is based on comparative techniques. To simulate wind flow in the interior spaces of case studies, FLUENT software has been used. Research achievements show that it is possible to use natural ventilation to create a thermally comfortable indoor environment. The natural ventilation strategies could be classified into two groups of environmental characteristics such as public space structure, and architectural characteristics including building form and orientation, openings, central courtyards, wind catchers, roof, wall wings, semi-open spaces and the heat capacity of materials. Having investigated modern buildings of Iran, innovative elements like wind catchers and wall wings are less used than the traditional architecture. Instead, passive ventilation strategies have been more considered in the building design as for the roof structure and openings.

Keywords: natural ventilation strategies, wind catchers, wind flow, Iranian modern buildings

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Authors: Aina Barcelona, Carolyn Oldham, Jordi Colomer, Teresa Serra

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The loss of seagrass meadows worldwide is being tackled by formulating coastal restoration strategies. Seagrass loss results in a network of vegetated patches which are barely interconnected, and consequently, the ecological services they provide may be highly compromised. Hence, there is a need to optimize coastal management efforts in order to implement successful restoration strategies, not only through modifying the architecture of the canopies but also by gathering together information on the hydrodynamic conditions of the seabeds. To obtain information on the hydrodynamics within the patches of vegetation, this study deals with the scale analysis of the minimum lengths of patch management strategies that can be effectively used on. To this aim, a set of laboratory experiments were conducted in a laboratory flume where the plant densities, patch lengths, and hydrodynamic conditions were varied to discern the vegetated patch lengths that can provide optimal ecosystem services for canopy development. Two possible patch behaviours based on the turbulent kinetic energy (TKE) production were determined: one where plants do not interact with the flow and the other where plants interact with waves and produce TKE. Furthermore, this study determines the minimum patch lengths that can provide successful management restoration. A canopy will produce TKE, depending on its density, the length of the vegetated patch, and the wave velocities. Therefore, a vegetated patch will produce plant-wave interaction under high wave velocities when it presents large lengths and high canopy densities.

Keywords: seagrass, minimum patch size, turbulent kinetic energy, oscillatory flow

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Authors: S. Curteanu, F. Leon, M. Gavrilescu, S. A. Floria

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Optimization algorithms inspired from human behavior were applied in this approach, associated with neural networks models. The algorithms belong to human behaviors of learning and cooperation and human competitive behavior classes. For the first class, the main strategies include: random learning, individual learning, and social learning, and the selected algorithms are: simplified human learning optimization (SHLO), social learning optimization (SLO), and teaching-learning based optimization (TLBO). For the second class, the concept of learning is associated with competitiveness, and the selected algorithms are sports-inspired algorithms (with Football Game Algorithm, FGA and Volleyball Premier League, VPL) and Imperialist Competitive Algorithm (ICA). A real process, the synthesis of polyacrylamide-based multicomponent hydrogels, where some parameters are difficult to obtain experimentally, is considered as a case study. Reaction yield and swelling degree are predicted as a function of reaction conditions (acrylamide concentration, initiator concentration, crosslinking agent concentration, temperature, reaction time, and amount of inclusion polymer, which could be starch, poly(vinyl alcohol) or gelatin). The experimental results contain 175 data. Artificial neural networks are obtained in optimal form with biologically inspired algorithm; the optimization being perform at two level: structural and parametric. Feedforward neural networks with one or two hidden layers and no more than 25 neurons in intermediate layers were obtained with values of correlation coefficient in the validation phase over 0.90. The best results were obtained with TLBO algorithm, correlation coefficient being 0.94 for an MLP(6:9:20:2) – a feedforward neural network with two hidden layers and 9 and 20, respectively, intermediate neurons. Good results obtained prove the efficiency of the optimization algorithms. More than the good results, what is important in this approach is the simulation methodology, including neural networks and optimization biologically inspired algorithms, which provide satisfactory results. In addition, the methodology developed in this approach is general and has flexibility so that it can be easily adapted to other processes in association with different types of models.

Keywords: artificial neural networks, human behaviors of learning and cooperation, human competitive behavior, optimization algorithms

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Authors: Mustafa Aydın, Ali Murat Sunbul

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Hierarchical or nested data structures usually are seen in many research areas. Especially, in the field of education, if we examine most of the studies, we can see the nested structures. Students in classes, classes in schools, schools in cities and cities in regions are similar nested structures. In a hierarchical structure, students being in the same class, sharing the same physical conditions and similar experiences and learning from the same teachers, they demonstrate similar behaviors between them rather than the students in other classes.

Keywords: hierarchical linear modeling, nested data, hierarchical structure, data structure

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Authors: Anees Raza, Liu Chunyan

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Renewable energy technologies are need of the time and are already making the big impact in the climatic outlook of the world. Biogas technology is one of those, and it has a lot of benefits for its users. It is cost effective because it is produced from the raw material which is available free of cost to the livestock farmers. Bio-slurry, a by-product of biogas, is being used as fertilizer for the crops production and increasing soil fertility. There are many other household benefits of technology. Research paper discusses the benefits of biogas as perceived by the biogas users as well as non-users of Tehsil Jhang. Data were collected from 60 respondents (30 users and 30 non-users) selected purposively through validated and pre-tested interview schedule from the respondents. Collected data were analyzed by using Statistical Package for Social Sciences (SPSS). Household benefits like ‘makes cooking easy,’ ‘Less breathing issues for working women in kitchens’ and ‘Use of bio-slurry as organic fertilizer’ had the highly significant relationship between them with t-values of 3.24, 4.39 and 2.80 respectively. Responses of the respondents about environmental benefits of biogas technology showed that ‘less air pollution’ had a significant relationship between them while ‘less temperature rise up than due to the burning of wood /dung’ had the non-significant relationship in the responses of interviewed respondents. It was clear from the research that biogas users were becoming influential in convincing non-users to adopt this technology due to its noticeable benefits. Research area where people were depending on wood to be used as fire fuel could be helped in reduction of cutting of trees which will help in controlling deforestation and saving the environment.People should be encouraged in using of biogas technology through providing them subsidies and low mark up loans.

Keywords: biogas technology, deforestation, environmental benefits, renewable energy

Procedia PDF Downloads 249

Authors: Akiode Ayobami, Akiode Akinsewa, Odeku Mojisola, Salako Busola, Odutolu Omobola, Nuhu Khadija

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Purpose: Evidence exists that family planning use can contribute to reduction in infant and maternal mortality in any country. Despite these benefits, contraceptive use in Nigeria still remains very low, only 10% among married women. Understanding factors that predict contraceptive use is very important in order to improve the situation. In this paper, we analysed data from the 2013 Nigerian Demographic and Health Survey (NDHS) to better understand predictors of contraceptive use in Nigeria. The use of logistics regression and other traditional models in this type of situation is not appropriate as they do not account for social structure influence brought about by the hierarchical nature of the data on response variable. We therefore used multilevel modelling to explore the determinants of contraceptive use in order to account for the significant variation in modern contraceptive use by socio-demographic, and other proximate variables across the different Nigerian states. Method: This data has a two-level hierarchical structure. We considered the data of 26, 403 married women of reproductive age at level 1 and nested them within the 36 states and the Federal Capital Territory, Abuja at level 2. We modelled use of modern contraceptive against demographic variables, being told about FP at health facility, heard of FP on TV, Magazine or radio, husband desire for more children nested within the state. Results: Our results showed that the independent variables in the model were significant predictors of modern contraceptive use. The estimated variance component for the null model, random intercept, and random slope models were significant (p=0.00), indicating that the variation in contraceptive use across the Nigerian states is significant, and needs to be accounted for in order to accurately determine the predictors of contraceptive use, hence the data is best fitted by the multilevel model. Only being told about family planning at the health facility and religion have a significant random effect, implying that their predictability of contraceptive use varies across the states. Conclusion and Recommendation: Results showed that providing FP information at the health facility and religion needs to be considered when programming to improve contraceptive use at the state levels.

Keywords: multilevel modelling, family planning, predictors, Nigeria

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Authors: Ricky Saputra, Rashmi Walvekar, Mohammad Khalid, Kaveh Shahbaz, Suganti Ramarad

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This particular study of interest aims to study the effect of coupling ultrasonic treatment with eutectic solvents in devulcanization process of waste rubber tyre. Specifically, three different types of Deep Eutectic Solvents (DES) were utilized, namely ChCl:Urea (1:2), ChCl:ZnCl₂ (1:2) and ZnCl₂:urea (2:7) in which their physicochemical properties were analysed and proven to have permissible water content that is less than 3.0 wt%, degradation temperature below 200ᵒC and freezing point below 60ᵒC. The mass ratio of rubber to DES was varied from 1:20-1:40, sonicated for 1 hour at 37 kHz and heated at variable time of 5-30 min at 180ᵒC. Energy dispersive x-rays (EDX) results revealed that the first two DESs give the highest degree of sulphur removal at 74.44 and 76.69% respectively with optimum heating time at 15 minutes whereby if prolonged, reformation of crosslink network would be experienced. Such is supported by the evidence shown by both FTIR and FESEM results where di-sulfide peak reappears at 30 minutes and morphological structures from 15 to 30 minutes change from smooth with high voidage to rigid with low voidage respectively. Furthermore, TGA curve reveals similar phenomena whereby at 15 minutes thermal decomposition temperature is at the lowest due to the decrease of molecular weight as a result of sulphur removal but increases back at 30 minutes. Type of bond change was also analysed whereby it was found that only di-sulphide bond was cleaved and which indicates partial-devulcanization. Overall, the results show that DES has a great potential to be used as devulcanizing solvent.

Keywords: crosslink network, devulcanization, eutectic solvents, reformation, ultrasonic

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Authors: Radhamanohar Aepuru, R. V. Mangalaraja

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Flexible electronic devices have drawn potential interest and provide significant new insights to develop energy conversion and storage devices such as photodetectors and nanogenerators. Recently, self-powered electronic systems have captivated huge attention for next generation MEMS/NEMS devices that can operate independently by generating built-in field without any need of external bias voltage and have wide variety of applications in telecommunication, imaging, environmental and defence sectors. The basic physical process involved in these devices are charge generation, separation, and charge flow across the electrodes. Many inorganic nanostructures have been exploring to fabricate various optoelectronic and electromechanical devices. However, the interaction of nanostructures and their excited charge carrier dynamics, photoinduced charge separation, and fast carrier mobility are yet to be studied. The proposed research is to address one such area and to realize the self-powered electronic devices. In the present work, nanocomposites of inorganic nanostructures based on ZnO, metal halide perovskites; and polyvinylidene fluoride (PVDF) based nanocomposites are realized for photodetectors and nanogenerators. The characterization of the inorganic nanostructures is carried out through steady state optical absorption and luminescence spectroscopies as well as X-ray diffraction and high-resolution transmission electron microscopy (TEM) studies. The detailed carrier dynamics is investigated using various spectroscopic techniques. The developed composite nanostructures exhibit significant optical and electrical properties, which have wide potential applications in various MEMS/NEMS devices such as photodetectors and nanogenerators.

Keywords: dielectrics, nanocomposites, nanogenerators, photodetectors

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Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan

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In this paper, the comparison between k-Nearest Neighbor (kNN) algorithms for classifying the 3D EEG model in brain balancing is presented. The EEG signal recording was conducted on 51 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, maximum PSD values were extracted as features from the model. There are three indexes for the balanced brain; index 3, index 4 and index 5. There are significant different of the EEG signals due to the brain balancing index (BBI). Alpha-α (8–13 Hz) and beta-β (13–30 Hz) were used as input signals for the classification model. The k-NN classification result is 88.46% accuracy. These results proved that k-NN can be used in order to predict the brain balancing application.

Keywords: power spectral density, 3D EEG model, brain balancing, kNN

Procedia PDF Downloads 475

Authors: A. Fernandez Zuvich, I. Gana Watkins, H. Zolotucho, H. Troiani, A. Caneiro, M. Prado, A. L. Soldati

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The study of actinide nanoparticles (NPs) has attracted the attention of the scientific community not only because the lack of information about their ecotoxicological effects but also because the use of NPs could open a new way in the production of nuclear energy. Indeed, it was recently demonstrated that UO2 NPs sintered pellets exhibit closed porosity with improved fission gas retention and radiation-tolerance , ameliorated mechanical properties, and less detriment of the thermal conductivity upon use, making them an interesting option for new nuclear fuels. In this work, we used a combination of diffraction and microscopy tools to characterize the morphology, the crystalline structure and the composition of UO2 nanoparticles doped with 10%wt Gd2O3. The particles were synthesized by a modified sol-gel method at low temperatures. X-ray Diffraction (XRD) studies determined the presence of a unique phase with the cubic structure and Fm3m spatial group, supporting that Gd atoms substitute U atoms in the fluorite structure of UO2. In addition, Field Emission Gun Scanning (FEG-SEM) and Transmission (FEG-TEM) Electron Microscopy images revealed the presence of micrometric agglomerates of nanoparticles, with rounded morphology and an average crystallite size < 50 nm. Energy Dispersive Spectroscopy (EDS) coupled to TEM determined the presence of Gd in all the analyzed crystallites. Besides, FEG-SEM-EDS showed a homogeneous concentration distribution at the micrometer scale indicating that the small size of the crystallites compensates the variation in composition by averaging a large number of crystallites. These techniques, as combined tools resulted thus essential to find out details of morphology and composition distribution at the sub-micrometer scale, and set a standard for developing and analyzing nanoparticulated nuclear fuels.

Keywords: actinide nanoparticles, burnable poison, nuclear fuel, sol-gel

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Authors: G. M. Contessa, L. Lepore, G. Gandolfo, C. Poggi, N. Cherubini, R. Remetti, S. Sandri

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Practical guidelines are provided in this work for the safe use of a portable d-t Thermo Scientific MP-320 neutron generator producing pulsed 14.1 MeV neutron beams. The neutron generator’s emission was tested experimentally and reproduced by MCNPX Monte Carlo code. Simulations were particularly accurate, even generator’s internal components were reproduced on the basis of ad-hoc collected X-ray radiographic images. Measurement campaigns were conducted under different standard experimental conditions using an LB 6411 neutron detector properly calibrated at three different energies, and comparing simulated and experimental data. In order to estimate the dose to the operator vs. the operating conditions and the energy spectrum, the most appropriate value of the conversion factor between neutron fluence and ambient dose equivalent has been identified, taking into account both direct and scattered components. The results of the simulations show that, in real situations, when there is no information about the neutron spectrum at the point where the dose has to be evaluated, it is possible - and in any case conservative - to convert the measured value of the count rate by means of the conversion factor corresponding to 14 MeV energy. This outcome has a general value when using this type of generator, enabling a more accurate design of experimental activities in different setups. The increasingly widespread use of this type of device for industrial and medical applications makes the results of this work of interest in different situations, especially as a support for the definition of appropriate radiation protection procedures and, in general, for risk analysis.

Keywords: instrumentation and monitoring, management of radiological safety, measurement of individual dose, radiation protection of workers

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Authors: Ziba Talaeizadeh, Taghi Ebadi

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Hospitals and medical centers generate a wide array of infectious waste on a daily basis, leading to pressing environmental concerns associated with proper disposal. Disposable plastic items and spun-bond clothing, commonly made from polypropylene, pose a significant risk of disease transmission, necessitating specialized waste management strategies. Incorporating these materials into bituminous asphalt production offers a potential solution, as it can modify asphalt mixtures and reduce susceptibility to cracking. This study aims to assess the crack resistance of asphalt mixtures modified with hospital spun-bond waste. Asphalt mixtures were prepared using the Marshall method, with spun-bond waste added in varying proportions (5% to 20%). The Semi-Circular Bending (SCB) test was conducted to evaluate asphalt fracture behavior under Mode I loading at controlled speeds of 5, 20, and 50 millimeters per minute and an average temperature of 25°C. Parameters such as fracture energy (FE) and Crack Resistance Index (CRI) were quantified. The results indicate that the addition of 10% to 15% spun-bond polypropylene polymer enhances the performance of the modified mixture, resulting in an 18% increase in fracture energy and an 11% reduction in cracking stiffness compared to the control sample. Further investigations involving factors like compaction level, bitumen type, and aggregate grading are recommended to address medical waste management and mitigate asphalt pavement cracking issues.

Keywords: asphalt cracking, hospital waste, semi-circular bending test, spun-bond

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Authors: Mayowa Saheed Sanusi A, Musiliu Olushola Sunmonua, Abdulquadri Alakab Owolabi Raheema, Adeyemi Ikimot Adejokea

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The development of healthy cookies for health-conscious consumers cannot be overemphasized in the present global health crisis. This study was aimed to evaluate and model the influence of ripeness levels of papaya puree (unripe, ripe and overripe), oven temperature (130°C, 150°C and 170°C) and oven rack speed (stationary, 10 and 20 rpm) on physicochemical properties of papaya-based cookies using Response Surface Methodology (RSM). The physicochemical properties (baking time, cookies mass, cookies thickness, spread ratio, proximate composition, Calcium, Vitamin C and Total Phenolic Content) were determined using standard procedures. The data obtained were statistically analysed at p≤0.05 using ANOVA. The polynomial regression model of response surface methodology was used to model the physicochemical properties. The adequacy of the models was determined using the coefficient of determination (R²) and the response optimizer of RSM was used to determine the optimum physicochemical properties for the papaya-based cookies. Cookies produced from overripe papaya puree were observed to have the shortest baking time; ripe papaya puree favors cookies spread ratio, while the unripe papaya puree gives cookies with the highest mass and thickness. The highest crude protein content, fiber content, calcium content, Vitamin C and Total Phenolic Content (TPC) were observed in papaya based-cookies produced from overripe puree. The models for baking time, cookies mass, cookies thickness, spread ratio, moisture content, crude protein and TPC were significant, with R2 ranging from 0.73 – 0.95. The optimum condition for producing papaya based-cookies with desirable physicochemical properties was obtained at 149°C oven temperature, 17 rpm oven rack speed and with the use of overripe papaya puree. The Information on the use of puree from unripe, ripe and overripe papaya can help to increase the use of underutilized unripe or overripe papaya and also serve as a strategic means of obtaining a fat substitute to produce new products with lower production cost and health benefit.

Keywords: papaya based-cookies, modeling, response surface methodology, physicochemical properties

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Authors: Massimiliano Frezza, Sergio Bianchi, Augusto Pianese

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The relation between stock price volatility and trading volume represents a controversial issue which has received a remarkable attention over the past decades. In fact, an extensive literature shows a positive relation between price volatility and trading volume in the financial markets, but the causal relationship which originates such association is an open question, from both a theoretical and empirical point of view. In this regard, various models, which can be considered as complementary rather than competitive, have been introduced to explain this relationship. They include the long debated Mixture of Distributions Hypothesis (MDH); the Sequential Arrival of Information Hypothesis (SAIH); the Dispersion of Beliefs Hypothesis (DBH); the Noise Trader Hypothesis (NTH). In this work, we analyze whether stock market efficiency can explain the diversity of results achieved during the years. For this purpose, we propose an alternative measure of market efficiency, based on the pointwise regularity of a stochastic process, which is the Hurst–H¨older dynamic exponent. In particular, we model the stock market by means of the multifractional Brownian motion (mBm) that displays the property of a time-changing regularity. Mostly, such models have in common the fact that they locally behave as a fractional Brownian motion, in the sense that their local regularity at time t0 (measured by the local Hurst–H¨older exponent in a neighborhood of t0 equals the exponent of a fractional Brownian motion of parameter H(t0)). Assuming that the stock price follows an mBm, we introduce and theoretically justify the Hurst–H¨older dynamical exponent as a measure of market efficiency. This allows to measure, at any time t, markets’ departures from the martingale property, i.e. from efficiency as stated by the Efficient Market Hypothesis. This approach is applied to financial markets; using data for the SP500 index from 1978 to 2017, on the one hand we find that when efficiency is not accounted for, a positive contemporaneous relationship emerges and is stable over time. Conversely, it disappears as soon as efficiency is taken into account. In particular, this association is more pronounced during time frames of high volatility and tends to disappear when market becomes fully efficient.

Keywords: volume–volatility relationship, efficient market hypothesis, martingale model, Hurst–Hölder exponent

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Authors: A. Chowdhury, P. Egodawatta, J. M. McGree, A. Goonetilleke

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Hydrologic models are increasingly used as tools to predict stormwater quantity and quality from urban catchments. However, due to a range of practical issues, most models produce gross errors in simulating complex hydraulic and hydrologic systems. Difficulty in finding a robust approach for model calibration is one of the main issues. Though automatic calibration techniques are available, they are rarely used in common commercial hydraulic and hydrologic modelling software e.g. MIKE URBAN. This is partly due to the need for a large number of parameters and large datasets in the calibration process. To overcome this practical issue, a framework for automatic calibration of a hydrologic model was developed in R platform and presented in this paper. The model was developed based on the time-area conceptualization. Four calibration parameters, including initial loss, reduction factor, time of concentration and time-lag were considered as the primary set of parameters. Using these parameters, automatic calibration was performed using Approximate Bayesian Computation (ABC). ABC is a simulation-based technique for performing Bayesian inference when the likelihood is intractable or computationally expensive to compute. To test the performance and usefulness, the technique was used to simulate three small catchments in Gold Coast. For comparison, simulation outcomes from the same three catchments using commercial modelling software, MIKE URBAN were used. The graphical comparison shows strong agreement of MIKE URBAN result within the upper and lower 95% credible intervals of posterior predictions as obtained via ABC. Statistical validation for posterior predictions of runoff result using coefficient of determination (CD), root mean square error (RMSE) and maximum error (ME) was found reasonable for three study catchments. The main benefit of using ABC over MIKE URBAN is that ABC provides a posterior distribution for runoff flow prediction, and therefore associated uncertainty in predictions can be obtained. In contrast, MIKE URBAN just provides a point estimate. Based on the results of the analysis, it appears as though ABC the developed framework performs well for automatic calibration.

Keywords: automatic calibration framework, approximate bayesian computation, hydrologic and hydraulic modelling, MIKE URBAN software, R platform

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Authors: David F. Nettleton, Elodie Bugnicourt, Christian Wasiak, Alejandro Rosales

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In this presentation, preliminary results are given for the modeling and calibration of two different industrial winding MIMO (Multiple Input Multiple Output) processes using machine learning techniques. In contrast to previous approaches which have typically used ‘black-box’ linear statistical methods together with a definition of the mechanical behavior of the process, we use non-linear machine learning algorithms together with a ‘white-box’ rule induction technique to create a supervised model of the fitting error between the expected and real force measures. The final objective is to build a precise model of the winding process in order to control de-tension of the material being wound in the first case, and the friction of the material passing through the die, in the second case. Case 1, Tension Control of a Winding Process. A plastic web is unwound from a first reel, goes over a traction reel and is rewound on a third reel. The objectives are: (i) to train a model to predict the web tension and (ii) calibration to find the input values which result in a given tension. Case 2, Friction Force Control of a Micro-Pullwinding Process. A core+resin passes through a first die, then two winding units wind an outer layer around the core, and a final pass through a second die. The objectives are: (i) to train a model to predict the friction on die2; (ii) calibration to find the input values which result in a given friction on die2. Different machine learning approaches are tested to build models, Kernel Ridge Regression, Support Vector Regression (with a Radial Basis Function Kernel) and MPART (Rule Induction with continuous value as output). As a previous step, the MPART rule induction algorithm was used to build an explicative model of the error (the difference between expected and real friction on die2). The modeling of the error behavior using explicative rules is used to help improve the overall process model. Once the models are built, the inputs are calibrated by generating Gaussian random numbers for each input (taking into account its mean and standard deviation) and comparing the output to a target (desired) output until a closest fit is found. The results of empirical testing show that a high precision is obtained for the trained models and for the calibration process. The learning step is the slowest part of the process (max. 5 minutes for this data), but this can be done offline just once. The calibration step is much faster and in under one minute obtained a precision error of less than 1x10-3 for both outputs. To summarize, in the present work two processes have been modeled and calibrated. A fast processing time and high precision has been achieved, which can be further improved by using heuristics to guide the Gaussian calibration. Error behavior has been modeled to help improve the overall process understanding. This has relevance for the quick optimal set up of many different industrial processes which use a pull-winding type process to manufacture fibre reinforced plastic parts. Acknowledgements to the Openmind project which is funded by Horizon 2020 European Union funding for Research & Innovation, Grant Agreement number 680820

Keywords: data model, machine learning, industrial winding, calibration

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Authors: Inigo Sanz-Pena, Shanika Arachchi, Dilani Dhammika, Sanjaya Mallikarachchi, Jeewantha S. Bandula, Alison H. McGregor, Nicolas Newell

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The use of orthotic braces for adolescent idiopathic scoliosis (AIS) patients is the most common non-surgical treatment to prevent deformity progression. The traditional method to create an orthotic brace involves casting the patient’s torso to obtain a representative geometry, which is then rectified by an orthotist to the desired geometry of the brace. Recent improvements in 3D scanning technologies, rectification software, CNC, and additive manufacturing processes have given the possibility to compliment, or in some cases, replace manual methods with digital approaches. However, the rectification process remains dependent on the orthotist’s skills. Therefore, the rectification process needs to be carefully characterized to ensure that braces designed through a digital workflow are as efficient as those created using a manual process. The aim of this study is to compare 3D scans of patients with AIS against 3D scans of both pre- and post-rectified casts that have been manually shaped by an orthotist. Six AIS patients were recruited from the Ragama Rehabilitation Clinic, Colombo, Sri Lanka. All patients were between 10 and 15 years old, were skeletally immature (Risser grade 0-3), and had Cobb angles between 20-45°. Seven spherical markers were placed at key anatomical locations on each patient’s torso and on the pre- and post-rectified molds so that distances could be reliably measured. 3D scans were obtained of 1) the patient’s torso and pelvis, 2) the patient’s pre-rectification plaster mold, and 3) the patient’s post-rectification plaster mold using a Structure Sensor Mark II 3D scanner (Occipital Inc., USA). 3D stick body models were created for each scan to represent the distances between anatomical landmarks. The 3D stick models were used to analyze the changes in position and orientation of the anatomical landmarks between scans using Blender open-source software. 3D Surface deviation maps represented volume differences between the scans using CloudCompare open-source software. The 3D stick body models showed changes in the position and orientation of thorax anatomical landmarks between the patient and the post-rectification scans for all patients. Anatomical landmark position and volume differences were seen between 3D scans of the patient’s torsos and the pre-rectified molds. Between the pre- and post-rectified molds, material removal was consistently seen on the anterior side of the thorax and the lateral areas below the ribcage. Volume differences were seen in areas where the orthotist planned to place pressure pads (usually at the trochanter on the side to which the lumbar curve was tilted (trochanter pad), at the lumbar apical vertebra (lumbar pad), on the rib connected to the apical vertebrae at the mid-axillary line (thoracic pad), and on the ribs corresponding to the upper thoracic vertebra (axillary extension pad)). The rectification process requires the skill and experience of an orthotist; however, this study demonstrates that the brace shape, location, and volume of material removed from the pre-rectification mold can be characterized and quantified. Results from this study can be fed into software that can accelerate the brace design process and make steps towards the automated digital rectification process.

Keywords: additive manufacturing, orthotics, scoliosis brace design, sculpting software, spinal deformity

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Authors: Sih-Li Chen, Chih-Hao Chen, Chi-Tong Chan

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Poor ventilation and high carbon dioxide (CO2) concentrations lead to the formation of sick buildings. This problem cannot simply be resolved by introducing fresh air from outdoor environments because this creates extra loads on indoor air-conditioning systems. Desiccants are widely used in air conditioning systems in tropical and subtropical regions with high humidity to reduce the latent heat load from fresh air. Desiccants are usually used as a packed-bed type, which is low cost, to combine with air-conditioning systems. Nevertheless, the pressure drop of a packed bed is too high, and the heat of adsorption caused by the adsorption process lets the temperature of the outlet air increase, bringing about an extra heat load, so the high pressure drop and the increased temperature of the outlet air are energy consumption sources needing to be resolved. For this reason, the gas-solid fluidised beds that have high heat and mass transfer rates, uniform properties and low pressure drops are very suitable for use in air-conditioning systems.This study experimentally investigates the performance of silica gel fluidized bed device which applying to an air conditioning system. In the experiments, commercial silica gel particles were filled in the two beds and to form a fixed packed bed and a fluidized bed. The results indicated that compared to the fixed packed bed device, the total adsorption and desorption by amounts of fluidized bed for 40 minutes increased 20.6% and 19.9% respectively when the bed height was 10 cm and superficial velocity was set to 2 m/s. In addition, under this condition, the pressure drop and outlet air temperature raise were reduced by 36.0% and 30.0%. Given the above results, application of the silica gel fluidized bed to air conditioning systems has great energy-saving potential.

Keywords: fluidized bed, packed bed, silica gel, adsorption, desorption, pressure drop

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Authors: Ahmad Alwosheel, Ahmed Alqaraawi

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This work proposes a new speaker segmentation approach for two speakers. It is an online approach that does not require a prior information about speaker models. It has two phases, a conventional approach such as unsupervised BIC-based is utilized in the first phase to detect speaker changes and train a Neural Network, while in the second phase, the output trained parameters from the Neural Network are used to predict next incoming audio stream. Using this approach, a comparable accuracy to similar BIC-based approaches is achieved with a significant improvement in terms of computation time.

Keywords: artificial neural network, diarization, speaker indexing, speaker segmentation

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Authors: Ahmed I. Raheem

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In this thesis, stratified and stratified wavy flow regimes have been investigated numerically for the oil (1.57 mPa s viscosity and 780 kg/m3 density) and water twophase flow in small and large horizontal steel pipes with a diameter between 0.0254 to 0.508 m by ANSYS Fluent software. Volume of fluid (VOF) with two phases flows using two equations family models (Realizable k-

Keywords: CFD, two-phase flow, pressure gradient, volume of fluid, large diameter, horizontal pipe, oil-water stratified and stratified wavy flow

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Authors: Esther Cabezas-Rivas

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Ordinary differential equations (ODE) are a fundamental part of the curriculum for most engineering degrees, and students typically have difficulties in the subsequent abstract mathematical calculations. To enhance their motivation and profit that they are digital natives, we propose a teamwork project that includes the creation of a video. It should explain how to model mathematically a real-world problem transforming it into an ODE, which should then be solved using the tools learned in the lectures. This idea was indeed implemented with first-year students of a BSc in Engineering and Management during the period of online learning caused by the outbreak of COVID-19 in Spain. Each group of 4 students was assigned a different topic: model a hot water heater, search for the shortest path, design the quickest route for delivery, cooling a computer chip, the shape of the hanging cables of the Golden Gate, detecting land mines, rocket trajectories, etc. These topics should be worked out through two complementary channels: a written report describing the problem and a 10-15 min video on the subject. The report includes the following items: description of the problem to be modeled, detailed obtention of the ODE that models the problem, its complete solution, and interpretation in the context of the original problem. We report the outcomes of this teaching in context and active learning experience, including the feedback received by the students. They highlighted the encouragement of creativity and originality, which are skills that they do not typically relate to mathematics. Additionally, the video format (unlike a common presentation) has the advantage of allowing them to critically review and self-assess the recording, repeating some parts until the result is satisfactory. As a side effect, they felt more confident about their oral abilities. In short, students agreed that they had fun preparing the video. They recognized that it was tricky to combine deep mathematical contents with entertainment since, without the latter, it is impossible to engage people to view the video till the end. Despite this difficulty, after the activity, they claimed to understand better the material, and they enjoyed showing the videos to family and friends during and after the project.

Keywords: active learning, contextual teaching, models in differential equations, student-produced videos

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Authors: S. Delgado, C. Cerrada, R. S. Gómez

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This research introduces an approach to voxelizing the surfaces of triangular meshes with efficiency and accuracy. Our method leverages parallel equidistant scan-lines and introduces a Gap Detection technique to address the limitations of existing approaches. We present a comprehensive study showcasing the method's effectiveness, scalability, and versatility in different scenarios. Voxelization is a fundamental process in computer graphics and simulations, playing a pivotal role in applications ranging from scientific visualization to virtual reality. Our algorithm focuses on enhancing the voxelization process, especially for complex models and high resolutions. One of the major challenges in voxelization in the Graphics Processing Unit (GPU) is the high cost of discovering the same voxels multiple times. These repeated voxels incur in costly memory operations with no useful information. Our scan-line-based method ensures that each voxel is detected exactly once when processing the triangle, enhancing performance without compromising the quality of the voxelization. The heart of our approach lies in the use of parallel, equidistant scan-lines to traverse the interiors of triangles. This minimizes redundant memory operations and avoids revisiting the same voxels, resulting in a significant performance boost. Moreover, our method's computational efficiency is complemented by its simplicity and portability. Written as a single compute shader in Graphics Library Shader Language (GLSL), it is highly adaptable to various rendering pipelines and hardware configurations. To validate our method, we conducted extensive experiments on a diverse set of models from the Stanford repository. Our results demonstrate not only the algorithm's efficiency, but also its ability to produce 26 tunnel free accurate voxelizations. The Gap Detection technique successfully identifies and addresses gaps, ensuring consistent and visually pleasing voxelized surfaces. Furthermore, we introduce the Slope Consistency Value metric, quantifying the alignment of each triangle with its primary axis. This metric provides insights into the impact of triangle orientation on scan-line based voxelization methods. It also aids in understanding how the Gap Detection technique effectively improves results by targeting specific areas where simple scan-line-based methods might fail. Our research contributes to the field of voxelization by offering a robust and efficient approach that overcomes the limitations of existing methods. The Gap Detection technique fills a critical gap in the voxelization process. By addressing these gaps, our algorithm enhances the visual quality and accuracy of voxelized models, making it valuable for a wide range of applications. In conclusion, "Closing the Gap: Efficient Voxelization with Equidistant Scan-lines and Gap Detection" presents an effective solution to the challenges of voxelization. Our research combines computational efficiency, accuracy, and innovative techniques to elevate the quality of voxelized surfaces. With its adaptable nature and valuable innovations, this technique could have a positive influence on computer graphics and visualization.

Keywords: voxelization, GPU acceleration, computer graphics, compute shaders

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Authors: Juan F. P. Ramírez, Jésica A. L. Isaza, Benjamín A. Rojano

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This study proposes a novel use of a method to determine the mechanical properties of fruits by the use of the indentation tests. The method combines experimental results with a numerical finite elements model. The results presented correspond to a simplified numerical modeling of banana. The banana was assumed as one-layer material with an isotropic linear elastic mechanical behavior, the Young’s modulus found is 0.3Mpa. The method will be extended to multilayer models in further studies.

Keywords: finite element method, fruits, inverse analysis, mechanical properties

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Authors: Chongtham Jiten, K. Chandramani Singh, Radhapiyari Laishram

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Nanocrystalline powders of the lead-free piezoelectric material, tantalum-substituted potassium sodium niobate (K0.5Na0.5)(Nb0.9Ta0.1)O3 (KNNT), were produced using a Retsch PM100 planetary ball mill by setting the milling time to 15h, 20h, 25h, 30h, 35h and 40h, at a fixed speed of 250rpm. The average particle size of the milled powders was found to decrease from 12nm to 3nm as the milling time increases from 15h to 25h, which is in agreement with the existing theoretical model. An anomalous increase to 98nm and then a drop to 3nm in the particle size were observed as the milling time further increases to 30h and 40h respectively. Various sizes of these starting KNNT powders were used to investigate the effect of milling time on the microstructure, dielectric properties, phase transitions and piezoelectric properties of the resulting KNNT ceramics. The particle size of starting KNNT was somewhat proportional to the grain size. As the milling time increases from 15h to 25h, the resulting ceramics exhibit enhancement in the values of relative density from 94.8% to 95.8%, room temperature dielectric constant (εRT) from 878 to 1213, and piezoelectric charge coefficient (d33) from 108pC/N to 128pC/N. For this range of ceramic samples, grain size refinement suppresses the maximum dielectric constant (εmax), shifts the Curie temperature (Tc) to a lower temperature and the orthorhombic-tetragonal phase transition (Tot) to a higher temperature. Further increase of milling time from 25h to 40h produces a gradual degradation in the values of relative density, εRT, and d33 of the resulting ceramics.

Keywords: perovskite, dielectric, ceramics, high-energy milling

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Authors: Surupa Shaw, Debjyoti Banerjee

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Enhancing heat transfer in compact volumes is a challenge when constrained by cost issues, especially those associated with requirements for minimizing pumping power consumption. This is particularly acute for electronic chip cooling applications. Technological advancements in microelectronics have led to development of chip architectures that involve increased power consumption. As a consequence packaging, technologies are saddled with needs for higher rates of power dissipation in smaller form factors. The increasing circuit density, higher heat flux values for dissipation and the significant decrease in the size of the electronic devices are posing thermal management challenges that need to be addressed with a better design of the cooling system. Maximizing surface area for heat exchanging surfaces (e.g., extended surfaces or “fins”) can enable dissipation of higher levels of heat flux. Fractal structures have been shown to maximize surface area in compact volumes. Self-replicating structures at multiple length scales are called “Fractals” (i.e., objects with fractional dimensions; unlike regular geometric objects, such as spheres or cubes whose volumes and surface area values scale as integer values of the length scale dimensions). Fractal structures are expected to provide an appropriate technology solution to meet these challenges for enhanced heat transfer in the microelectronic devices by maximizing surface area available for heat exchanging fluids within compact volumes. In this study, the effect of different fractal micro-channel architectures and flow structures on the enhancement of transport phenomena in heat exchangers is explored by parametric variation of fractal dimension. This study proposes a model that would enable cost-effective solutions for thermal-fluid transport for energy applications. The objective of this study is to ascertain the sensitivity of various parameters (such as heat flux and pressure gradient as well as pumping power) to variation in fractal dimension. The role of the fractal parameters will be instrumental in establishing the most effective design for the optimum cooling of microelectronic devices. This can help establish the requirement of minimal pumping power for enhancement of heat transfer during cooling. Results obtained in this study show that the proposed models for fractal architectures of microchannels significantly enhanced heat transfer due to augmentation of surface area in the branching networks of varying length-scales.

Keywords: fractals, microelectronics, constructal theory, heat transfer enhancement, pumping power enhancement

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Authors: Julian Iliev

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The recent release of The Matrix Resurrections persuaded many film scholars that The Matrix trilogy had lost its appeal and its concepts were largely outdated. This study examines the human pods and growing fields in the trilogy. Their functionality is compared to Michel Foucault’s concept of docile bodies: linking fictional and contemporary worlds. This paradigm is scrutinized through surveillance literature. The analogy brings to light common elements of hidden surveillance practices in technologies. The comparison illustrates the effects of body manipulation portrayed in the movies and their relevance with contemporary surveillance practices. Many scholars have utilized a close reading methodology in film studies (J.Bizzocchi, J.Tanenbaum, P.Larsen, S. Herbrechter, and Deacon et al.). The use of a particular lens through which media text is examined is an indispensable factor that needs to be incorporated into the methodology. The study spotlights both scenes from the trilogy depicting the human pods and growing fields. The functionality of the pods and the fields compare directly with Foucault’s concept of docile bodies. By utilizing Foucault’s study as a lens, the research will unearth hidden components and insights into the films. Foucault recognizes three disciplines that produce docile bodies: 1) manipulation and the interchangeability of individual bodies, 2) elimination of unnecessary movements and management of time, and 3) command system guaranteeing constant supervision and continuity protection. These disciplines can be found in the pods and growing fields. Each body occupies a single pod aiding easier manipulation and fast interchangeability. The movement of the bodies in the pods is reduced to the absolute minimum. Thus, the body is transformed into the ultimate object of control – minimum movement correlates to maximum energy generation. Supervision is exercised by wiring the body with numerous types of cables. This ultimate supervision of body activity reduces the body’s purpose to mere functioning. If a body does not function as an energy source, then it’s unplugged, ejected, and liquefied. The command system secures the constant supervision and continuity of the process. To Foucault, the disciplines are distinctly different from slavery because they stop short of a total takeover of the bodies. This is a clear difference from the slave system implemented in the films. Even though their system might lack sophistication, it makes up for it in the elevation of functionality. Further, surveillance literature illustrates the connection between the generation of body energy in The Matrix trilogy to the generation of individual data in contemporary society. This study found that the three disciplines producing docile bodies were present in the portrayal of the pods and fields in The Matrix trilogy. The above comparison combined with surveillance literature yields insights into analogous processes and contemporary surveillance practices. Thus, the constant generation of energy in The Matrix trilogy can be equated to the consistent data generation in contemporary society. This essay shows the relevance of the body manipulation concept in the Matrix films with contemporary surveillance practices.

Keywords: docile bodies, film trilogies, matrix movies, michel foucault, privacy loss, surveillance

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Authors: Heather Mroz

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Geothermal fluids can provide a nearly unlimited source of renewable energy but are often highly corrosive due to dissolved carbon dioxide (CO2), hydrogen sulphide (H2S), Ammonia (NH3) and chloride ions. The corrosive environment drives material selection for many components, including piping, heat exchangers and pressure vessels, to higher alloys of stainless steel, nickel-based alloys and titanium. The use of these alloys is cost-prohibitive and does not offer the pressure rating of carbon steel. One solution, explosion cladding, has been proven to reduce the capital cost of the geothermal equipment while retaining the mechanical and corrosion properties of both the base metal and the cladded surface metal. Explosion cladding is a solid-state welding process that uses precision explosions to bond two dissimilar metals while retaining the mechanical, electrical and corrosion properties. The process is commonly used to clad steel with a thin layer of corrosion-resistant alloy metal, such as stainless steel, brass, nickel, silver, titanium, or zirconium. Additionally, explosion welding can join a wider array of compatible and non-compatible metals with more than 260 metal combinations possible. The explosion weld is achieved in milliseconds; therefore, no bulk heating occurs, and the metals experience no dilution. By adhering to a strict set of manufacturing requirements, both the shear strength and tensile strength of the bond will exceed the strength of the weaker metal, ensuring the reliability of the bond. For over 50 years, explosion cladding has been used in the oil and gas and chemical processing industries and has provided significant economic benefit in reduced maintenance and lower capital costs over solid construction. The focus of this paper will be on the many benefits of the use of explosion clad in process equipment instead of more expensive solid alloy construction. The method of clad-plate production with explosion welding as well as the methods employed to ensure sound bonding of the metals. It will also include the origins of explosion cladding as well as recent technological developments. Traditionally explosion clad plate was formed into vessels, tube sheets and heads but recent advances include explosion welded piping. The final portion of the paper will give examples of the use of explosion-clad metals in geothermal energy recovery. The classes of materials used for geothermal brine will be discussed, including stainless steels, nickel alloys and titanium. These examples will include heat exchangers (tube sheets), high pressure and horizontal separators, standard pressure crystallizers, piping and well casings. It is important to educate engineers and designers on material options as they develop equipment for geothermal resources. Explosion cladding is a niche technology that can be successful in many situations, like geothermal energy recovery, where high temperature, high pressure and corrosive environments are typical. Applications for explosion clad metals include vessel and heat exchanger components as well as piping.

Keywords: clad metal, explosion welding, separator material, well casing material, piping material

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