Search results for: MATLAB reference model

Authors: B. S. Fatoyinbo, D. Stretch, O. T. Amoo, D. Allopi

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This study extends the use of the Drainage Area Regionalization (DAR) method in generating synthetic data and calibrating PyTOPKAPI stream yield for an ungauged basin at a daily time scale. The generation of runoff in determining a river yield has been subjected to various topographic and spatial meteorological variables, which integers form the Catchment Characteristics Model (CCM). Many of the conventional CCM models adapted in Africa have been challenged with a paucity of adequate, relevance and accurate data to parameterize and validate the potential. The purpose of generating synthetic flow is to test a hydrological model, which will not suffer from the impact of very low flows or very high flows, thus allowing to check whether the model is structurally sound enough or not. The employed physically-based, watershed-scale hydrologic model (PyTOPKAPI) was parameterized with GIS-pre-processing parameters and remote sensing hydro-meteorological variables. The validation with mean annual runoff ratio proposes a decent graphical understanding between observed and the simulated discharge. The Nash-Sutcliffe efficiency and coefficient of determination (R²) values of 0.704 and 0.739 proves strong model efficiency. Given the current climate variability impact, water planner can now assert a tool for flow quantification and sustainable planning purposes.

Keywords: catchment characteristics model, GIS, synthetic data, ungauged basin

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Authors: Sandeep Kaur, Jenny Vuong, Marcel Julliard, Sean O'Donoghue

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Time-series data are useful for modelling as they can enable model-evaluation. However, when reconstructing models from phosphoproteomic data, often non-exact methods are utilised, as the knowledge regarding the network structure, such as, which kinases and phosphatases lead to the observed phosphorylation state, is incomplete. Thus, such reactions are often hypothesised, which gives rise to uncertainty. Here, we propose a framework, implemented via a web-based tool (as an extension to Minardo), which given time-series phosphoproteomic datasets, can generate κ models. The incompleteness and uncertainty in the generated model and reactions are clearly presented to the user via the visual method. Furthermore, we demonstrate, via a toy EGF signalling model, the use of algorithmic verification to verify κ models. Manually formulated requirements were evaluated with regards to the model, leading to the highlighting of the nodes causing unsatisfiability (i.e. error causing nodes). We aim to integrate such methods into our web-based tool and demonstrate how the identified erroneous nodes can be presented to the user via the visual method. Thus, in this research we present a framework, to enable a user to explore phosphorylation proteomic time-series data in the context of models. The observer can visualise which reactions in the model are highly uncertain, and which nodes cause incorrect simulation outputs. A tool such as this enables an end-user to determine the empirical analysis to perform, to reduce uncertainty in the presented model - thus enabling a better understanding of the underlying system.

Keywords: κ-models, model verification, time-series phosphoproteomic datasets, uncertainty and error visualisation

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Authors: Shady Adib, Vladimir Vinogradov, Peter Gosling

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Digital Twin (DT) technology is a new technology that appeared in the early 21st century. The DT is defined as the digital representation of living and non-living physical assets. By connecting the physical and virtual assets, data are transmitted smoothly, allowing the virtual asset to fully represent the physical asset. Although there are lots of studies conducted on the DT concept, there is still limited information about the ability of the DT models for monitoring and detecting unexpected changes in structural behaviour in real time. This is due to the large computational efforts required for the analysis and an excessively large amount of data transferred from sensors. This paper aims to develop the DT concept to be able to detect the abnormal changes in structural behaviour in real time using advanced modelling techniques, deep learning algorithms, and data acquisition systems, taking into consideration model uncertainties. finite element (FE) models were first developed offline to be used with a reduced basis (RB) model order reduction technique for the construction of low-dimensional space to speed the analysis during the online stage. The RB model was validated against experimental test results for the establishment of a DT model of a two-dimensional truss. The established DT model and deep learning algorithms were used to identify the location of damage once it has appeared during the online stage. Finally, the RB model was used again to identify the damage severity. It was found that using the RB model, constructed offline, speeds the FE analysis during the online stage. The constructed RB model showed higher accuracy for predicting the damage severity, while deep learning algorithms were found to be useful for estimating the location of damage with small severity.

Keywords: data acquisition system, deep learning, digital twin, model uncertainties, reduced basis, reduced order model

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Authors: Toru Shionoya, Yosuke Kurihara, Takashi Kaburagi, Kajiro Watanabe

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Mass-produced bidirectional microphones have attractive characteristics. They work as a microphone as well as a sensor with high gain over a wide frequency range; they are also highly reliable and economical. We present novel multiple functional uses of the microphones. A mathematical model for explaining the high-pass-filtering characteristics of bidirectional microphones was presented. Based on the model, the characteristics of the microphone were investigated, and a novel use for the microphone as a sensor with a wide frequency range was presented. In this study, applications for using the microphone as a security sensor and a human biosensor were introduced. The mathematical model was validated through experiments, and the feasibility of the abovementioned applications for security monitoring and the biosignal monitoring were examined through experiments.

Keywords: bidirectional microphone, low-frequency, mathematical model, frequency response

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Authors: J.Zambrano Nájera, M.Gómez Valentín

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Increases in urbanization during XX century, have brought as one major problem the increased of sediment production. Hydraulic erosion is one of the major causes of increasing of sediments in small urban catchments. Such increments in sediment yielding in header urban catchments can caused obstruction of drainage systems, making impossible to capture urban runoff, increasing runoff volumes and thus exacerbating problems of urban flooding. For these reasons, it is more and more important to study of sediment production in urban watershed for properly analyze and solve problems associated to sediments. The study of sediments production has improved with the use of mathematical modeling. For that reason, it is proposed a new physically based model applicable to small header urban watersheds that includes the advantages of distributed physically base models, but with more realistic data requirements. Additionally, in this paper the model proposed is compared with a lumped model, reviewing the results, the advantages and disadvantages between the both of them.

Keywords: erosion, hydrologic modeling, urban runoff, sediment modeling, sediment yielding, urban planning

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Authors: Lidon Lashley

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This paper presents how the social model of disability can be used to reshape inclusive education practices in Guyana. Inclusive education in Guyana is metamorphosizing but still firmly held in the tenets of the Medical Model of Disability which influences the experiences of children with Special Education Needs and/or Disabilities (SEN/D). An ethnographic approach to data gathering was employed in this study. Qualitative data was gathered from the voices of children with and without SEN/D as well as their mainstream teachers to present the interplay of discourses and subjectivities in the situation. The data was analyzed using Adele Clarke's postmodern approach to grounded theory analysis called situational analysis. The data suggest that it is possible but will be challenging to fully contextualize and adopt Loreman's synthesis and Booths and Ainscow's Index in the two mainstream schools studied. In addition, the data paved the way for the presentation of the social model framework specific to Guyana called 'Southern Inclusive Education Framework for Guyana' and its support tool called 'The Inclusive Checker created for Southern mainstream primary classrooms.

Keywords: social model of disability, medical model of disability, subjectivities, metamorphosis, special education needs, postcolonial Guyana, inclusion, culture, mainstream primary schools, Loreman's synthesis, Booths and Ainscow's index

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Authors: Giulio Mangano, Alberto De Marco, Giovanni Zenezini

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The concept of City Logistics (CL) has emerged to improve the impacts of last mile freight distribution in urban areas. In this paper, a System Dynamics (SD) model exploring the dynamics of the diffusion of a ICT platform for CL management across different populations is proposed. For the development of the model two sources have been used. On the one hand, the major diffusion variables and feedback loops are derived from a literature review of existing diffusion models. On the other hand, the parameters are represented by the value propositions delivered by the platform as a response to some of the users’ needs. To extract the most important value propositions the Business Model Canvas approach has been used. Such approach in fact focuses on understanding how a company can create value for her target customers. These variables and parameters are thus translated into a SD diffusion model with three different populations namely municipalities, logistics service providers, and own account carriers. Results show that, the three populations under analysis fully adopt the platform within the simulation time frame, highlighting a strong demand by different stakeholders for CL projects aiming at carrying out more efficient urban logistics operations.

Keywords: city logistics, simulation, system dynamics, business model

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Authors: Dongkwon Han, Sangho Kim, Sunil Kwon

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Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that applies to advanced approaches for production forecasting due to uncertainty and complexity of fluid flow. In this study, artificial neural network (ANN) model which integrates machine learning and data-driven approach was developed to predict productivity in shale gas. The database of 129 wells of Eagle Ford shale basin used for testing and training of the ANN model. The Input data related to hydraulic fracturing, well completion and productivity of shale gas were selected and the output data is a cumulative production. The performance of the ANN using all data sets, clustering and variables importance (VI) models were compared in the mean absolute percentage error (MAPE). ANN model using all data sets, clustering, and VI were obtained as 44.22%, 10.08% (cluster 1), 5.26% (cluster 2), 6.35%(cluster 3), and 32.23% (ANN VI), 23.19% (SVM VI), respectively. The results showed that the pre-trained ANN model provides more accurate results than the ANN model using all data sets.

Keywords: unconventional gas, artificial neural network, machine learning, clustering, variables importance

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Authors: Prasenjit Singha, Ajay Kumar Shukla

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To produce high-quality steel in larger volumes, dynamic control of composition and temperature throughout the process is essential. In this paper, we developed a mass transfer model based on thermodynamics to simulate the ladle metallurgy steel-making process using FactSage and its macro facility. The overall heat and mass transfer processes consist of one equilibrium chamber, two non-equilibrium chambers, and one adiabatic reactor. The flow of material, as well as heat transfer, occurs across four interconnected unit chambers and a reactor. We used the macro programming facility of FactSage™ software to understand the thermochemical model of the secondary steel making process. In our model, we varied the oxygen content during the process and studied their effect on the composition of the final hot metal and slag. The model has been validated with respect to the plant data for the steel composition, which is similar to the ladle metallurgy steel-making process in the industry. The resulting composition profile serves as a guiding tool to optimize the process of ladle metallurgy in steel-making industries.

Keywords: desulphurization, degassing, factsage, reactor

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Authors: Dora Vajda, Somayyeh Mohammadi, Sandor Rozsa

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Predicting the relationship satisfaction based on the personality characteristics of both partners has a long history. The association between relationship quality and personality traits has been previously demonstrated. Personality traits are most commonly assessed using the Five-Factor Model. The present study has focused on Cloninger's psychobiological model of personality that accounts for dimensions of both temperament and character. The goal of this study was to examine the actor and partner effect of couple's personality on relationship outcomes. In total, 184 heterosexual couples completed the Temperament and Character Inventory (TCI) and the Dyadic Adjustment Scale. The analysis was based on Actor-Partner Interdependence Model (APIM) using multilevel modeling (MLwiN). Results showed that character dimensions Self-Directedness and Cooperativeness had a statistically meaningful actor and partner effect on both partner's relationship quality. However, male's personality temperament dimension Reward Dependence had an only actor effect on his relationship quality. The findings contribute to the literature by highlighting the role of character dimensions of personality in romantic relationships.

Keywords: APIM (actor-partner interdependence model), MLwiN, personality, relationship quality

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Authors: Ayesha Ashfaq, Muhammad Ajmal Ashfaq

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It has been assumed that metaphorical and symbolic contests are waged with metaphors, captions, and signs in political cartoons that play a significant role in image construction of political actors, situations or events in the political arena. This paper is an effort to explore the metaphorical devices in political cartoons related to the political confrontation in Pakistan between the ruling party Pakistan Muslim League Nawaz (PMLN) and opposition parties especially after Panama leaks. For this purpose, political cartoons sketched by five renowned political cartoonists on the basis of their belongings to the most highly circulated mainstream English newspapers of Pakistan and their professional experiences in their genre, were selected. The cartoons were analyzed through the Barthes’s model of Semiotics under the umbrella of the first level of agenda setting theory ‘framing’. It was observed that metaphorical devices in political cartoons are one of the key weapons of cartoonists’ armory. These devices are used to attack the candidates and contribute to the image and character building. It was found that all the selected political cartoonists used different forms of metaphors including situational metaphors and embodying metaphors. Not only the physical stature but also the debates and their activities were depicted metaphorically in the cartoons that create the scenario of comparison between the cartoons and their real political confrontation. It was examined that both forms of metaphors shed light on cartoonist’s perception and newspaper’s policy about political candidates, political parties and particular events. In addition, it was found that zoomorphic metaphors and metaphors of diminishments were also predominantly used to depict the conflict between two said political actors.

Keywords: metaphor, Panama leaks, political cartoons, political communication

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Authors: Zhang Tao, Si Tang, Zhang Yufeng, Jin Jiahua

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Work pressure is an emerging research of organizational behavior. Many factors associated with this study also attracted the interest of scholars. Macao is surrounding by open micro-capitalist economy which has a high internationalization level and Mature operation system. And there is no doubt that tourism and hotel service industry is the pillar of the Macao economy with the developing of the mainland individual tourist visa. More and more cities are willing to inclusive culture diversity which lead to the amount of inbound tourists present high-speed up trend cause the hotel industry has a strong customer base and development space. At the same time, the hotel staff is an important role in the service. However, affected by some adverse factors, the hotel staff face a variety of pressures. This study combs the concept and theory of pressures relevant influencing factors and puts forward the purpose of this research. The focus of this study will be organizational supported by work efficiency and work pressure, using qualitative and quantitative research methods. Through questionnaires and interviews, 10 hotels in Macao were selected and 500 questionnaires were distributed to the employees. Statistical analysis software SPSS was used for descriptive statistics. By exploratory factor analysis and confirmatory factor analysis, effect. And the relevant practitioners on behalf of the interview content analysis. The innovation of this research lies in the empirical study of the relationship between the working pressure, organizational support and working efficiency of Macau hotel practitioners, and constructs and validates the structural model of the relationship among them. This model will be helpful for people to use more research methods to study hotel practitioners pressure in the future. At the same time, we can draw the following conclusions: 1. There is a significant negative correlation between salary level and job stress; 2. There is a significant negative correlation between job stress and performance; 3. Different organizational support can interfere the relationship between job stress and performance; 4. Put forward the strategy of relevance adjustment, which provides a reference value for the hotel industry in human resource management. It would be helpful to improve their service standard by training their practitioners more scientifically and rationally.

Keywords: Macau, perceived organizational support, work stress, work efficiency

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Authors: Mojtaba Farzaneh, Majid Baghaei Nejad

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This article proposes a new Flexible Capacitive Tactile Sensors based on paper sheets. This method combines the parameters of sensor's material and dielectric, and forms a new model of flexible capacitive sensors. The present article tries to present a practical explanation of this method's application and advantages. With the use of this new method, it is possible to make a more flexibility and accurate sensor in comparison with the current models. To assess the performance of this model, the common capacitive sensor is simulated and the proposed model of this article and one of the existing models are assessed. The results of this article indicate that the proposed model of this article can enhance the speed and accuracy of tactile sensor and has less error in comparison with the current models. Based on the results of this study, it can be claimed that in comparison with the current models, the proposed model of this article is capable of representing more flexibility and more accurate output parameters for touching the sensor, especially in abnormal situations and uneven surfaces, and increases accuracy and practicality.

Keywords: capacitive sensor, paper sheets, flexible, tactile, uneven

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Authors: Bilgehan Gültekin, Tuba Gültekin

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Peace diplomacy is the most important international tool to keep peace all over the world. The study titled “peace diplomacy for international relations” is consist of three part. In the first part, peace diplomacy is going to be introduced as a tool of peace communication and peace management. And, in this part, peace communication will be explained by international communication perspective. In the second part of the study,public relations events and communication campaigns will be developed originally for peace diplomacy. In this part, it is aimed original public communication dialogue management tools for peace diplomacy. the aim of the final part of the study, is to produce original public communication model for international relations. The model includes peace modules, peace management projects, original dialogue procedures and protocols, dialogue education, dialogue management strategies, peace actors, communication models, peace team management and public diplomacy steps. The creative part of the study aims to develop a model used for international relations for all countries. Creative Peace Diplomacy Model will be developed in the case of Turkey-Turkey-France and Turkey-Greece relations. So, communication and public relations events and campaigns are going to be developed as original for only this study.

Keywords: peace diplomacy, public communication model, dialogue management, international relations

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Authors: Jalal Abdulkareem Sultan, Abdulhakeem Luqman Hasan

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With the development of health care systems competition, hospitals face more and more pressures. Meanwhile, resource allocation has a vital effect on achieving competitive advantages in hospitals. Selecting the appropriate number of beds is one of the most important sections in hospital management. However, in real situation, bed allocation selection is a multiple objective problem about different items with vagueness and randomness of the data. It is very complex. Hence, research about bed allocation problem is relatively scarce under considering multiple departments, nursing hours, and stochastic information about arrival and service of patients. In this paper, we develop a fuzzy multiobjective bed allocation model for overcoming uncertainty and multiple departments. Fuzzy objectives and weights are simultaneously applied to help the managers to select the suitable beds about different departments. The proposed model is solved by using Artificial Bee Colony (ABC), which is a very effective algorithm. The paper describes an application of the model, dealing with a public hospital in Iraq. The results related that fuzzy multi-objective model was presented suitable framework for bed allocation and optimum use.

Keywords: bed allocation problem, fuzzy logic, artificial bee colony, multi-objective optimization

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Authors: Eirini Konstanta, Cedric Gouedard, Aggeliki Delimitsou, Stefania Patera, Samuel Murray

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Introduction: Quality reference DNA standards (QRS) for molecular testing by next-generation sequencing (NGS) are essential for accurate quantitation of copy number variations (CNV) for germline and variant allelic frequencies (VAF) for somatic analyses. Objectives: Presently, several molecular analytics for oncology patients are reliant upon quantitative metrics. Test validation and standardisation are also reliant upon the availability of surrogate control materials allowing for understanding test LOD (limit of detection), sensitivity, specificity. We have developed a dual calibration platform allowing for QRS pairs to be included in analysed DNA samples, allowing for accurate quantitation of CNV and VAF metrics within and between patient samples. Methods: QRS™ blocks up to 500nt were designed for common NGS panel targets incorporating ≥ 2 identification tags (IDTDNA.com). These were analysed upon spiking into gDNA, somatic, and ctDNA using a proprietary CalSuite™ platform adaptable to common LIMS. Results: We demonstrate QRS™ calibration reproducibility spiked to 5–25% at ± 2.5% in gDNA and ctDNA. Furthermore, we demonstrate CNV and VAF within and between samples (gDNA and ctDNA) with the same reproducibility (± 2.5%) in a clinical sample of lung cancer and HBOC (EGFR and BRCA1, respectively). CNV analytics was performed with similar accuracy using a single pair of QRS calibrators when using multiple single targeted sequencing controls. Conclusion: Dual paired QRS™ calibrators allow for accurate and reproducible quantitative analyses of CNV, VAF, intrinsic sample allele measurement, inter and intra-sample measure not only simplifying NGS analytics but allowing for monitoring clinically relevant biomarker VAF across patient ctDNA samples with improved accuracy.

Keywords: calibrator, CNV, gene copy number, VAF

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Authors: Nagaraju Jarugu, B. R. Narendra

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This paper focused on boost rectification by Single Phase Matrix Converter with fewer numbers of switches. The conventional matrix converter consists of 4 bidirectional switches, i.e. 8 set of IGBT/MOSFET with anti-parallel diodes. In this proposed matrix converter, only six switches are used. The switch commutation arrangements are also carried out in this work. The SPMC topology has many advantages as a minimal passive device use. It is very flexible and it can be used as a lot of converters. The gate pulses to the switches are provided by the PWM techniques. The duty ratio of the switches based on Pulse Width Modulation (PWM) technique was used to produce the output waveform of the circuit, simply by turning ON and OFF the switches. The simulation results using MATLAB/Simulink were provided to validate the feasibility of this proposed method.

Keywords: single phase matrix converter, reduced switches, AC voltage regulators, boost rectifier operation

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Authors: Tiffany Gallagher, Sheila Bennett

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Based on data from a larger study, this research is based in a small school district in Ontario, Canada, that has made a transition from self-contained classes for students with exceptionalities to inclusive classroom placements for all students with their age-appropriate peers. The school board aided this transition by hiring Inclusion Coaches with a background in special education to work alongside teachers as partners and inform their inclusive practice. Based on qualitative data from four focus groups conducted with Inclusion Coaches, as well as four blog-style reflections collected at various points over two years, six principles of inclusive practice were identified for coaches. The six principles form a model during transition: pre-requisite, process, precipice, promotion, proof, and promise. These principles are encapsulated in a visual model of a spiraling staircase displaying the conditions that exist prior to coaching, during coaching interactions and considerations for the sustainability of coaching. These six principles are re-iterative and should be re-visited each time a coaching interaction is initiated. Exploring inclusion coaching as a model emulates coaching in other contexts and allows us to examine an established process through a new lens. This research becomes increasingly important as more school boards transition toward inclusive classrooms, The Six ‘P’ Model: Principles of Inclusive Practice for Inclusion Coaches allows for a unique look into a scaffolding model of building educator capacity in an inclusive setting.

Keywords: capacity building, coaching, inclusion, special education

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Authors: Kang Lin Peng

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Space tourism emerged in 2001 and became famous in 2021, following the development of space technology. The space market is twisted because of the excess demand. Space tourism is currently rare and extremely expensive, with biased luxury product pricing, which is the seller’s market that consumers can not bargain with. Spaceship companies such as Virgin Galactic, Blue Origin, and Space X have been charged space tourism prices from 200 thousand to 55 million depending on various heights in space. There should be a reasonable price based on a fair basis. This study aims to derive a spacetime pricing model, which is different from the general pricing model on the earth’s surface. We apply general relativity theory to deduct the mathematical formula for the space tourism pricing model, which covers the traditional time-independent model. In the future, the price of space travel will be different from current flight travel when space travel is measured in lightyear units. The pricing of general commodities mainly considers the general equilibrium of supply and demand. The pricing model considers risks and returns with the dependent time variable as acceptable when commodities are on the earth’s surface, called flat spacetime. Current economic theories based on the independent time scale in the flat spacetime do not consider the curvature of spacetime. Current flight services flying the height of 6, 12, and 19 kilometers are charging with a pricing model that measures time coordinate independently. However, the emergence of space tourism is flying heights above 100 to 550 kilometers that have enlarged the spacetime curvature, which means tourists will escape from a zero curvature on the earth’s surface to the large curvature of space. Different spacetime spans should be considered in the pricing model of space travel to echo general relativity theory. Intuitively, this spacetime commodity needs to consider changing the spacetime curvature from the earth to space. We can assume the value of each spacetime curvature unit corresponding to the gradient change of each Ricci or energy-momentum tensor. Then we know how much to spend by integrating the spacetime from the earth to space. The concept is adding a price p component corresponding to the general relativity theory. The space travel pricing model degenerates into a time-independent model, which becomes a model of traditional commodity pricing. The contribution is that the deriving of the space tourism pricing model will be a breakthrough in philosophical and practical issues for space travel. The results of the space tourism pricing model extend the traditional time-independent flat spacetime mode. The pricing model embedded spacetime as the general relativity theory can better reflect the rationality and accuracy of space travel on the universal scale. The universal scale from independent-time scale to spacetime scale will bring a brand-new pricing concept for space traveling commodities. Fair and efficient spacetime economics will also bring to humans’ travel when we can travel in lightyear units in the future.

Keywords: space tourism, spacetime pricing model, general relativity theory, spacetime curvature

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Authors: Champika S. Kariyawasam

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The distribution of gorse (Ulex europaeus) plants in South Australia has been modelled using 126 presence-only location data as a function of seven climate parameters. The predicted range of U. europaeus is mainly along the Mount Lofty Ranges in the Adelaide Hills and on Kangaroo Island. Annual precipitation and yearly average aridity index appeared to be the highest contributing variables to the final model formulation. The Jackknife procedure was employed to identify the contribution of different variables to gorse model outputs and response curves were used to predict changes with changing environmental variables. Based on this analysis, it was revealed that the combined effect of one or more variables could make a completely different impact to the original variables on their own to the model prediction. This work also demonstrates the need for a careful approach when selecting environmental variables for projecting correlative models to climatically distinct area. Maxent acts as a robust model when projecting the fitted species distribution model to another area with changing climatic conditions, whereas the generalized linear model, bioclim, and domain models to be less robust in this regard. These findings are important not only for predicting and managing invasive alien gorse in South Australia and Sri Lanka but also in other countries of the invasive range.

Keywords: invasive species, Maxent, species distribution modelling, Ulex europaeus

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Authors: Huijuan Liu, Fukun Li, Hao Yuan

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The bolted spherical node is a common type of joint in space steel structures. The bolt-sphere joint portion almost always controls the bearing capacity of the bolted spherical node. The investigation of the bearing performance and progressive failure in service often requires high-fidelity numerical models. This paper focuses on the constitutive models of bolt steel and sphere steel used in China’s space structure construction. The elastoplastic model is determined by a standard tensile test and calibrated Voce saturated hardening rule. The ductile damage is found dominant based on the fractography analysis. Then Rice-Tracey ductile fracture rule is selected and the model parameters are calibrated based on tensile tests of notched specimens. These calibrated material models can benefit research or engineering work in similar fields.

Keywords: bolt-sphere joint, steel, constitutive model, ductile damage, model calibration

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Authors: Subhash Chander, Tejinder Kumar Jindal

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Due to its simplicity, Pulse detonation engine technology has recently emerged as a future aerospace propulsion technology. In this paper, we studied various parameters affecting the performance of Pulse detonation engine (PDE) like tube length for proper deflagration to detonation transition (DDT), tube diameter (combustion tube), tube length, Shelkin spiral, Cell size, Equivalence ratio of fuel used etc. We have discussed various techniques for reducing the length of pulse tube by using various DDT enhancing devices. The effect of length of the tube from 40 mm to 3000 mm and diameter from 10 mm to 100 mm has been analyzed. The fuel used is C2H2 and oxidizer is O2. The results are processed in MATLAB for drawing valid conclusions.

Keywords: pulse detonation engine (PDE), deflagration to detonation (DDT), Schelkin spiral, cell size (λ)

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Authors: Cristian F.T. Montenegro, Luís F. N. Lourenço, Maurício B. C. Salles, Renato M. Monaro

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More PV systems have been connected to the electrical network each year. As the number of PV systems increases, some issues affecting grid operations have been identified. This paper studied the impacts related to changes in solar irradiance on a distribution/sub-transmission network, considering variations due to moving clouds and daily cycles. Using MATLAB/Simulink software, a solar farm of 30 MWp was built and then implemented to a test network. From simulations, it has been determined that irradiance changes can have a significant impact on the grid by causing voltage fluctuations outside the allowable thresholds. This work discussed some local control strategies and grid reinforcements to mitigate the negative effects of the irradiance changes on the grid.

Keywords: reactive power control, solar irradiance, utility-scale PV systems, voltage fluctuations

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Authors: Longqing Li

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The paper addresses the inefficiency of the classical model in measuring the Value-at-Risk (VaR) using a normal distribution or a Student’s t distribution. Specifically, the paper focuses on the one day ahead Value-at-Risk (VaR) of major stock market’s daily returns in US, UK, China and Hong Kong in the most recent ten years under 95% confidence level. To improve the predictable power and search for the best performing model, the paper proposes using two leading alternatives, Extreme Value Theory (EVT) and a family of GARCH models, and compares the relative performance. The main contribution could be summarized in two aspects. First, the paper extends the GARCH family model by incorporating EGARCH and TGARCH to shed light on the difference between each in estimating one day ahead Value-at-Risk (VaR). Second, to account for the non-normality in the distribution of financial markets, the paper applies Generalized Error Distribution (GED), instead of the normal distribution, to govern the innovation term. A dynamic back-testing procedure is employed to assess the performance of each model, a family of GARCH and the conditional EVT. The conclusion is that Exponential GARCH yields the best estimate in out-of-sample one day ahead Value-at-Risk (VaR) forecasting. Moreover, the discrepancy of performance between the GARCH and the conditional EVT is indistinguishable.

Keywords: Value-at-Risk, Extreme Value Theory, conditional EVT, backtesting

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Authors: Bo Hu, Shibo Wang, Haoyang Zhang, Jie Shi

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With the development of sonar detection technology, the acoustic stealth technology of underwater vehicles is facing severe challenges. The underwater acoustic coating is developing towards the direction of low-frequency absorption capability and broad absorption frequency bandwidth. In this paper, an acoustic model of underwater acoustic coating of composite material embedded with periodical steel structure is presented. The model has multiple high absorption peaks in the frequency range of 1kHz-8kHz, where achieves high sound absorption and broad bandwidth performance. It is found that the frequencies of the absorption peaks are related to the classic half-wavelength transmission principle. The sound absorption performance of the acoustic model is investigated by the finite element method using COMSOL software. The sound absorption mechanism of the proposed model is explained by the distributions of the displacement vector field. The influence of geometric parameters of periodical steel structure, including thickness and distance, on the sound absorption ability of the proposed model are further discussed. The acoustic model proposed in this study provides an idea for the design of underwater low-frequency broadband acoustic coating, and the results shows the possibility and feasibility for practical underwater application.

Keywords: acoustic coating, composite material, broad frequency bandwidth, sound absorption performance

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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The most aggressive form of brain tumor is called glioma. Glioma is kind of tumor that arises from glial tissue of the brain and occurs quite often. A fully automatic 2D-CNN model for brain tumor segmentation is presented in this paper. We performed pre-processing steps to remove noise and intensity variances using N4ITK and standard intensity correction, respectively. We used Keras open-source library with Theano as backend for fast implementation of CNN model. In addition, we used BRATS 2015 MRI dataset to evaluate our proposed model. Furthermore, we have used SimpleITK open-source library in our proposed model to analyze images. Moreover, we have extracted random 2D patches for proposed 2D-CNN model for efficient brain segmentation. Extracting 2D patched instead of 3D due to less dimensional information present in 2D which helps us in reducing computational time. Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.77 for complete, 0.76 for core, 0.77 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, LGG

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Authors: Angelo Lerro, Manuela Battipede, Piero Gili, Alberto Brandl

Abstract:

Redundancy requirements for UAV (Unmanned Aerial Vehicle) are hardly faced due to the generally restricted amount of available space and allowable weight for the aircraft systems, limiting their exploitation. Essential equipment as the Air Data, Attitude and Heading Reference Systems (ADAHRS) require several external probes to measure significant data as the Angle of Attack or the Sideslip Angle. Previous research focused on the analysis of a patented technology named Smart-ADAHRS (Smart Air Data, Attitude and Heading Reference System) as an alternative method to obtain reliable and accurate estimates of the aerodynamic angles. This solution is based on an innovative sensor fusion algorithm implementing soft computing techniques and it allows to obtain a simplified inertial and air data system reducing external devices. In fact, only one external source of dynamic and static pressures is needed. This paper focuses on the benefits which would be gained by the implementation of this system in UAV applications. A simplification of the entire ADAHRS architecture will bring to reduce the overall cost together with improved safety performance. Smart-ADAHRS has currently reached Technology Readiness Level (TRL) 6. Real flight tests took place on ultralight aircraft equipped with a suitable Flight Test Instrumentation (FTI). The output of the algorithm using the flight test measurements demonstrates the capability for this fusion algorithm to embed in a single device multiple physical and virtual sensors. Any source of dynamic and static pressure can be integrated with this system gaining a significant improvement in terms of versatility.

Keywords: aerodynamic angles, air data system, flight test, neural network, unmanned aerial vehicle, virtual sensor

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Authors: Kanika Saxena, Sunita Balani

Abstract:

Purpose - The aim of the study is to compare the reported sustainability activities in areas of emission, water management and gender equality, currently undertaken by the seven major pharmaceutical companies. Methodology: The published corporate sustainability activity reports for the year 2017 for seven pharmaceutical companies have been studied. The two main criteria for the inclusion of pharmaceutical companies in this study are that they are globally recognized and active in the field of sustainability reporting. Company’s actions and initiatives have been grouped under three categories: (i) Emissions (ii) Water management (iii) Gender Equality in terms of employee workforce. Findings: Based on the sustainability reports, quantification and grading of the companies showed interesting results. Johnson & Johnson and Bayer are leading their activities under emissions and water management categories. The number of activities under emission and water management in case of Eli Lily, Roche, Sanofi, Pfizer and GlaxoSmithKline were 19, 16, 16, 11 and 6 respectively. Johnson & Johnson and Eli Lily are leading in taking the initiatives to curb the problem of emissions as compared with other 5 companies. Under the category of gender equality in terms of employee workforce, Eli Lily is leading the group of sampled companies with 47% of women employee workforce globally followed by Sanofi with 46.2% (42.2% of managers) female employees. It has also been observed that in some of the reports, gender diversification in the workforce has not been mentioned though the total number of employees were mentioned. Conclusion: This study could serve as the informative material for future in-depth industry-specific studies in order to find out the participation of the pharmaceutical companies in the reporting of the sustainability activities especially in reference to emission, water management and gender equality in the workforce. In addition to it, this can be helpful as a reference point for other companies in the pharmaceutical sector who are yet to explore the field of sustainability initiatives and reporting. Due to the limited scope of this study, only seven major players of the pharmaceutical sector who are active in the field of sustainability have been considered.

Keywords: emission, gender equality workforce, pharmaceutical, sustainability, water management

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Authors: Neerav Kumar, Naumaan Nayyar, Sharath Kashyap

Abstract:

Most companies see an increase in the adoption of machine learning (ML) applications across internal and external-facing use cases. ML applications vend output either in batch or real-time patterns. A complete batch ML pipeline architecture comprises data sourcing, feature engineering, model training, model deployment, model output vending into a data store for downstream application. Due to unclear role expectations, we have observed that scientists specializing in building and optimizing models are investing significant efforts into building the other components of the architecture, which we do not believe is the best use of scientists’ bandwidth. We propose a system architecture created using AWS services that bring industry best practices to managing the workflow and simplifies the process of model deployment and end-to-end data integration for an ML application. This narrows down the scope of scientists’ work to model building and refinement while specialized data engineers take over the deployment, pipeline orchestration, data quality, data permission system, etc. The pipeline infrastructure is built and deployed as code (using terraform, cdk, cloudformation, etc.) which makes it easy to replicate and/or extend the architecture to other models that are used in an organization.

Keywords: data pipeline, machine learning, AWS, architecture, batch machine learning

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Authors: Kannapha Amaruchkul

Abstract:

We formulate a dynamic overbooking model for a tour operator, in which most reservations contain at least two people. The cancellation rate and the timing of the cancellation may depend on the group size. We propose two overbooking policies, namely economic- and service-based. In an economic-based policy, we want to minimize the expected oversold and underused cost, whereas, in a service-based policy, we ensure that the probability of an oversold situation does not exceed the pre-specified threshold. To illustrate the applicability of our approach, we use tour package data in 2016-2018 from a tour operator in Thailand to build a data-driven robust optimization model, and we tested the proposed overbooking policy in 2019. We also compare the data-driven approach to the conventional approach of fitting data into a probability distribution.

Keywords: applied stochastic model, data-driven robust optimization, overbooking, revenue management, tour operator

Procedia PDF Downloads 116