Search results for: interrupted time series designs

Authors: Pegah Ebrahimi, Farshad Oveissi, Iman Manavi-Tehrani, Sina Naficy, David F. Fletcher, Fariba Dehghani, David S. Winlaw

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Despite advances in modern surgery, congenital heart disease remains a medical challenge and a major cause of infant mortality. Cardiovascular prostheses are routinely used in surgical procedures to address congenital malformations, for example establishing a pathway from the right ventricle to the pulmonary arteries in pulmonary valvar atresia. Current off-the-shelf options including human and adult products have limited biocompatibility and durability, and their fixed size necessitates multiple subsequent operations to upsize the conduit to match with patients’ growth over their lifetime. Non-physiological blood flow is another major problem, reducing the longevity of these prostheses. These limitations call for better designs that take into account the hemodynamical and anatomical characteristics of different patients. We have integrated tissue engineering techniques with modern medical imaging and image processing tools along with mathematical modeling to optimize the design of cardiovascular grafts in a patient-specific manner. Computational Fluid Dynamics (CFD) analysis is done according to models constructed from each individual patient’s data. This allows for improved geometrical design and achieving better hemodynamic performance. Tissue engineering strives to provide a material that grows with the patient and mimic the durability and elasticity of the native tissue. Simulations also give insight on the performance of the tissues produced in our lab and reduce the need for costly and time-consuming methods of evaluation of the grafts. We are also developing a methodology for the fabrication of the optimized designs.

Keywords: computational fluid dynamics, cardiovascular grafts, design optimization, tissue engineering

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Authors: Ali A. Karakhan

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Stakeholders in the architecture, engineering, and construction (AEC) industry have been always searching for strategies to develop, design, and construct healthy and smart building projects. Healthy and smart building projects require that the building process including design and construction be altered and carefully implemented in order to bring about sustainable outcomes throughout the facility lifecycle. Healthy and smart building projects are expected to positively influence organizational success and facility performance across the project lifecycle leading to superior outcomes in terms of people, economy, and the environment. The present study aims to identify potential strategies that AEC organizations can implement to achieve healthy and smart building projects. Drivers and barriers for healthy and smart building features are also examined. The study findings indicate that there are three strategies to advance the development of healthy and smart building projects: (1) the incorporation of high-quality products and low chemical-emitting materials, (2) the integration of innovative designs, methods, and practices, and (3) the adoption of smart technology throughout the facility lifecycle. Satisfying external demands, achievement of a third-party certification, obtaining financial incentives, and a desire to fulfill professional duty are identified as the key drivers for developing healthy and smart building features; whereas, lack of knowledge and training, time/cost constrains, preference for/adherence to customary practices, and unclear business case for why healthy buildings are advantageous are recognized as the primary barriers toward a wider diffusion of healthy and smart building projects. The present study grounded in previous engineering, medical, and public health research provides valuable technical and practical recommendations for facility owners and industry professionals interested in pursuing sustainable, yet healthy and smart building projects.

Keywords: healthy buildings, smart construction, innovative designs, sustainable projects

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Authors: Sanghyeon Kim, Cheolung Cheong

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Savonius wind turbines are a drag-type of vertical-axis wind turbine that has been used most commonly as a small-scale wind generator. However, noise is a main hindrance to wide spreading of Savonius wind turbines, just like other wind turbines. Although noise levels radiating from Savonius wind turbines may be relatively low because of their small size, they induce relatively high annoyance due to their prolonged noise exposure to the near community. Therefore, aerodynamic noise of small vertical-axis wind turbines is one of most important design parameters. In this paper, aerodynamic noise characteristics of Savonius wind turbines are investigated using the hybrid CAA techniques, and their low noise designs are proposed based on understanding of noise generation mechanism. First, flow field around the turbine are analyzed by solving 3-D unsteady incompressible RANS equations. Then, noise radiation is predicted using the Ffowcs Williams and Hawkings equation. Two distinct harmonic noise components, the well-know BPF components and the harmonics whose fundamental frequency is much higher than the BPF are identified. On a basis of this finding, S-shaped blades are proposed as low noise designs and it can reduce the noise levels of Savonius wind turbines by up to 2.7 dB.

Keywords: aerodynamic noise, Savonius wind turbine, vertical-axis wind turbine

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Authors: Zhidong Zhang

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This study established a mixed method model in assessing statistics learning with Bayesian network models. There are three variants in exploratory sequential designs. There are three linked steps in one of the designs: qualitative data collection and analysis, quantitative measure, instrument, intervention, and quantitative data collection analysis. The study used a scoring model of analysis of variance (ANOVA) as a content domain. The research study is to examine students’ learning in both semantic and performance aspects at fine grain level. The ANOVA score model, y = α+ βx1 + γx1+ ε, as a cognitive task to collect data during the student learning process. When the learning processes were decomposed into multiple steps in both semantic and performance aspects, a hierarchical Bayesian network was established. This is a theory-driven process. The hierarchical structure was gained based on qualitative cognitive analysis. The data from students’ ANOVA score model learning was used to give evidence to the hierarchical Bayesian network model from the evidential variables. Finally, the assessment results of students’ ANOVA score model learning were reported. Briefly, this was a mixed method research design applied to statistics learning assessment. The mixed methods designs expanded more possibilities for researchers to establish advanced quantitative models initially with a theory-driven qualitative mode.

Keywords: exploratory sequential design, ANOVA score model, Bayesian network model, mixed methods research design, cognitive analysis

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Authors: Pawel Pistelok

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The article presents the concept of an electromagnetic circuit of a 3-phase surface-mounted permanent magnet generator designed for a single phase operation. A cross section of electromagnetic circuit and a field-circuit model of generator used for computations are shown. The paper presents comparative analysis of simulation results obtained for two different versions of generator regarding construction of armature winding. In the first version of generator the voltages generated in each of three winding phases have different rms values (different number of turns in each of phases), three winding phases are connected in series and one phase load is connected to the two output terminals of generator. The second version of generator is very similar, i.e. three winding phases are connected in series and one phase load is powered by generator, but in this version the voltages generated in each of winding phases have exactly the same rms values (the same number of turns in each of phases). The time waveforms of voltages, currents and electromagnetic torques in the airgaps of two machine versions for rated power are shown.

Keywords: permanent magnet generator, permanent magnets, synchronous generator, vibration, course of torque, single phase work, unsymmetrical operation point, serial connection of winding phase

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Authors: Fatemeh Behbahani, Rubiyah Yusof

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To avoid collision between following vehicles and vehicles in front, it is vital to keep appropriate, safe spacing between both vehicles over all speeds. Therefore, the following vehicle needs to have exact information regarding the speed and spacing between vehicles. This project is conducted to simulate the tuning of controller gain for a vehicle-following system through the selected control strategy, spacing control policy and fixed-time headway policy. In addition, the paper simulates and designs an adaptive gain controller for a road-vehicle-following system which uses information on the spacing, velocity and also acceleration of a preceding vehicle in the proposed one-vehicle look-ahead strategy. The mathematical model is implemented using Kirchhoff and Newton’s Laws, and stability simulated. The trial-error method was used to obtain a suitable value of controller gain. However, the adaptive-based controller system was able to optimize the gain value automatically. Model Reference Adaptive Control (MRAC) is designed and utilized and based on firstly the Gradient and secondly the Lyapunov approach. The Lyapunov approach considers stability. The Gradient approach was found to improve the best value of gain in the controller system with fixed-time headway.

Keywords: one-vehicle look-ahead, model reference adaptive, stability, tuning gain controller, MRAC

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Authors: Agata Tomaszewska, Timothy Kamps, Stephan R. Turnock, Nicola Symonds

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Bob skeleton is a highly competitive sport in which an athlete reaches speeds up to 40 m/s sliding, head first, down an ice track. It is believed that the friction between the runners and ice significantly contributes to the amount of the total energy loss during a bob skeleton descent. There is only limited available experimental data regarding the friction of bob skeleton runners or indeed steel on the ice at high sliding speeds ( > 20 m/s). Testing methods used to investigate the friction of steel on ice in winter sports have been outlined, and their accuracy and repeatability discussed. A system thinking approach was used to investigate the runner-ice interaction during sliding and create concept designs of three ice tribometers. The operational envelope of the bob skeleton system has been defined through mathematical modelling. Designs of a drum, linear and inertia pin-on-disk tribometers were developed specifically for bob skeleton runner testing with the requirement of reaching up to 40 m/s speed and facilitate fresh ice sliding. The design constraints have been outline and the proposed solutions compared based on the ease of operation, accuracy and the development cost.

Keywords: bob skeleton, ice friction, high-speed tribometers, sliding friction

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Authors: J. Marx, D. Smazna, R. Adelung, B. Fiedler

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Aerographite is a 3D interconnected carbon foam. Its tetrapodal morphology is based on the zinc oxide (ZnO) template structure, which is replicated in the chemical vapour deposition (CVD) into a hollow carbon structure. This replication process is analyzed in ex-situ studies via interrupted synthesis and the observation of the reaction progress by using scanning electron (SEM), transmission electron microscopy (TEM) and Raman spectroscopy techniques. Based on the epitaxial growth process, with a layer-by-layer growth behaviour of the wall thickness or number of layers and the catalytical graphitization of the deposited amorphous carbon into graphitic carbon by zinc, a growth model is created. The properties of aerographite, such as the electrical conductivity is dependent on the graphitization and number of layer (wall thickness). Wall thicknesses between 3 nm and 22 nm are achieved by a controlled stepwise reduction of the synthesis time on the basis of the developed growth model, and by a further thermal treatment at 1800 °C the graphitization of the presented carbon foam is modified. The variation of the wall thickness leads to an optimum defect density (ID/IG ratio) and the graphitization to an improvement in the electrical conductivity. Furthermore, a metallic conducting behaviour of untreated and 1800 °C treated aerographite can be observed. Due to these structural and defective modifications, a fundamental structural-property equation for the description of their influences on the electrical conductivity is developed.

Keywords: electrical conductivity, electron microscopy (SEM/TEM), graphitization, wall thickness

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Authors: Odeyemi Ifeoluwayemi, Maha Joushua, Fulani Omoyeni

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In the search for sustainability, over time, architectural approaches to design have moved from just nature inspired design to the study of nature’s principles to produce effective designs that solve the issue of sustainability. Nature has established materials, shapes and processes that are effective right from a minor scale to an enormous scale. A branch of human knowledge that studies nature is called biology. Biology helps us to grasp and understand nature. Biomimicry is a new way of viewing and valuing nature, based not on what we can extract from the natural world but on what we can learn from it. Life has sustained on the earth for the last 3.85 billion years, and it is necessary for us to find out how life has been able to stay sustained for that long. The building must teach the society new ecological morals, thus, a better understanding of how nature works can usefully inspire architectural designs to resolve issues that have already been resolved by nature. This will not only help in creating a healthy environment but will also produce positive environmental impacts. Biomimetic Architecture connects and reproduces the ideologies found in nature in order to create built environment which benefit people and other living creatures as well as preserving it for the future. Understanding the bioprocess would lead to the establishment of ecological approaches that serve as a platform for creating a built environment that goes beyond sustaining current settings but also mimic nature’s regenerative ecosystem. This paper aims to explain these design methods under the name of biomimicry and biomimetic architecture by reviewing literature and research works done by examining these approaches classified as forms, processes and ecosystems. It is expected that this research will provide information that would, therefore, lead to the creation of buildings that are eco-friendly and provide greater comfort to the populaces.

Keywords: biomimetic architecture, biomimicry, ecological design, nature

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Authors: Muriel Canas-Walker

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The 2012 TV series "The Legend of Zhen Huan" is one of the most popular and influential historical dramas on Chinese television and is regularly discussed on Chinese social media such as Weibo. Set in the Qing dynasty, the 76 episodes series features palace intrigues focused on female characters. In the Forbidden City, concubines must survive the cruelty of an extreme polygamy system, constantly competing against each other. The patriarchal oppression of the women sequestred in the harem relies on fierce female competition and does not leave much room for compassion. Using Michel Foucault’s theory of power, feminist theories, and visual anthropology, this paper analyzes the complex relationships between the female characters, from their rise to power to their fall from grace, from alliances to betrayals, from sorority to sororicide. This analysis aims to understand what makes this series particularly popular with young female audiences in China and explain its importance in Chinese media.

Keywords: Chinese TV Drama, feminism, popular culture, Theory of Power

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Authors: Debabrata Das

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This paper explains how to design a regulation loop for a power supply circuit. It also discusses the need of a regulation loop and the improvement of a circuit with regulation loop. A sample design is used to demonstrate how to use PSpice to design feedback loop to control output voltage of a power supply and how to check if the power supply is stable or oscillatory. A sample design is made using a specific Integrated Circuit (IC) available in the PSpice library. A designer can experiment feedback loop design using Cadence Pspice tool. PSpice is easy to use, reliable, and convenient. To test a feedback loop, generally, engineers use trial and error method with the hardware which takes a lot of time and manpower. Moreover, it is expensive because component and Printed Circuit Board (PCB) may go bad. PSpice can be used by designers to test their loop designs without using hardware circuits. A designer can save time, cost, manpower and simulate his/her power supply circuit accurately before making a real hardware using this software package.

Keywords: power electronics, feedback loop, regulation, stability, pole, zero, oscillation

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Authors: Nasser Ghassembaglou, Abdullah Bolek, Oktay Yilmaz, Ertan Oznergiz, Hikmet Kocabas, Safak Yilmaz

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High quality air filters production using nanofibers, as a functional material, has frequently been investigated. As it is more environmentally friendly, melting method has been selected to produce nanofibers. Spun-bond production systems consist of extruder, spin-pump, nozzle package and attenuators. Spin-pump makes molten polymer steady, which flows through extruder. Fibers are formed by regular melts passing through nuzzle holes under high pressure. Attenuator prolongs fibers to micron size to be collected on a conveyor. Different designs of attenuator systems have been studied in this research; new analysis have been done on existed designs considering fibers effect on air flow; it was comprehended that, at fibers presence, there is an air flow which agglomerates fibers as a negative effect. So some new representations have been designed and CFD analysis have been done on them. Afterwards, one of these representations selected as the most optimum and effective design which is brought in this paper.

Keywords: attenuator, CFD, nanofiber, spun-bond

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Authors: M. C. Schloesser

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The purpose of this paper is to explore the use and impact of business analytics in European football. Despite good evidence from other major sports leagues, research on this topic in Europe is currently very scarce. This research relies on expert interviews on the use and objective of business analytics. Along with revenue data over 16 seasons spanning from 2004/05 to 2019/20 from Manchester City FC, we conducted a time series analysis to detect a structural breakpoint on the different revenue streams, i.e., sponsorship and ticketing, after analytical tools have been implemented. We not only find that business analytics have indeed been applied at Manchester City FC and revenue increase is the main objective of their utilization but also that business analytics is indeed a good means to increase revenues if applied sufficiently. We can thereby support findings from other sports leagues. Consequently, professional sports organizations are advised to apply business analytics if they aim to increase revenues. This research has shown that analytical practices do, in fact, support revenue growth and help to work more efficiently. As the knowledge of analytical practices is very confidential and not publicly available, we had to select one club as a case study which can be considered a research limitation. Other practitioners should explore other clubs or leagues. Further, there are other factors that can lead to increased revenues that need to be considered. Additionally, sports organizations need resources to be able to apply and utilize business analytics. Consequently, findings might only apply to the top teams of the European football leagues. Nonetheless, this paper combines insights and results on usage, objectives, and impact of business analytics in European professional football and thereby fills a current research gap.

Keywords: business analytics, expert interviews, revenue management, time series analysis

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Authors: Soheila Sadeghi

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Accurate forecasting of project performance metrics is crucial for successfully managing and delivering urban road reconstruction projects. Traditional methods often rely on static baseline plans and fail to consider the dynamic nature of project progress and external factors. This research proposes a machine learning-based approach to forecast project performance metrics, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category in an urban road reconstruction project. The proposed model utilizes time series forecasting techniques, including Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance based on historical data and project progress. The model also incorporates external factors, such as weather patterns and resource availability, as features to enhance the accuracy of forecasts. By applying the predictive power of machine learning, the performance forecasting model enables proactive identification of potential deviations from the baseline plan, which allows project managers to take timely corrective actions. The research aims to validate the effectiveness of the proposed approach using a case study of an urban road reconstruction project, comparing the model's forecasts with actual project performance data. The findings of this research contribute to the advancement of project management practices in the construction industry, offering a data-driven solution for improving project performance monitoring and control.

Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, earned value management

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Authors: Jenna Pyorala

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This research looks at the principles and purposes ornamental design has served in the field of textile design. Ornamental designs are characterized by richness of details, abundance of elements, vegetative motifs and organic forms that flow harmoniously in complex compositions. Research on ornamental design is significant, because ornaments have been overlooked and considered as less meaningful and aesthetically pleasing than minimalistic, modern designs. This is despite the fact that in many parts of the world ornaments have been an important part of the cultural identification and expression for centuries. Ornament has been claimed to be superficial and merely used as a decorative way to hide the faults of designs. Such generalization is an incorrect interpretation of the real purposes of ornament. Many ornamental patterns tell stories, present mythological scenes or convey symbolistic meanings. Historically, ornamental decorations have been representing ideas and characteristics such as abundance, wealth, power and personal magnificence. The production of fine ornaments required refined skill, eye for intricate detail and perseverance while compiling complex elements into harmonious compositions. For this reason, ornaments have played an important role in the advancement of craftsmanship. Even though it has been claimed that people in the western design world have lost the relationship to ornament, the relation to it has merely changed from the practice of a craftsman to conceptualisation of a designer. With the help of new technological tools the production of ornaments has become faster and more efficient, demanding less manual labour. Designers who commit to this style of organic forms and vegetative motifs embrace and respect nature by representing its organically growing forms and by following its principles. The complexity of the designs is used as a way to evoke a sense of extraordinary beauty and stimulate intellect by freeing the mind from the predetermined interpretations. Through the study of these purposes it can be demonstrated that complex and richer design styles are as valuable a part of the world of design as more modern design approaches. The study highlights the meaning of ornaments by presenting visual examples and literature research findings. The practice based part of the project is the visual analysis of historical and cultural ornamental traditions such as Indian Chikan embroidery, Persian carpets, Art Nouveau and Rococo according to the rubric created for the purpose. The next step is the creation of ornamental designs based on the key elements in different styles. Theoretical and practical parts are woven together in this study that respects respect the long traditions of ornaments and highlight the importance of these design approaches to the field, in contrast to the more commonly preferred styles.

Keywords: cultural design traditions, ornamental design, organic forms from nature, textile design

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Authors: Atish Bagchi, Siva Chandrasekaran

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Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

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Authors: Farha Lakhani, Michael J. Pont

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There are two main architectures used to develop software for modern embedded systems: these can be labelled as “event-triggered” (ET) and “time-triggered” (TT). The research presented in this paper is concerned with the issues involved in migration between these two architectures. Although TT architectures are widely used in safety-critical applications they are less familiar to developers of mainstream embedded systems. The research presented in this paper began from the premise that–for a broad class of systems that have been implemented using an ET architecture–migration to a TT architecture would improve reliability. It may be tempting to assume that conversion between ET and TT designs will simply involve converting all event-handling software routines into periodic activities. However, the required changes to the software architecture are, in many cases rather more profound. The main contribution of the work presented in this paper is to identify ways in which the significant effort involved in migrating between existing ET architectures and “equivalent” (and effective) TT architectures could be reduced. The research described in this paper has taken an innovative step in this regard by introducing the use of ‘Design patterns’ for this purpose for the first time.

Keywords: embedded applications, software architectures, reliability, pattern

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Authors: Revalin Herdianto

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Recent climate changes increase uncertainties in vegetation conditions such as health and biomass globally and locally. The detection is, however, difficult due to the spatial and temporal scale of vegetation coverage. Due to unique vegetation response to its environmental conditions such as water availability, the interplay between vegetation dynamics and hydrologic conditions leave a signature in their feedback relationship. Vegetation indices (VI) depict vegetation biomass and photosynthetic capacity that indicate vegetation dynamics as a response to variables including hydrologic conditions and microclimate factors such as rainfall characteristics and land surface temperature (LST). It is hypothesized that the signature may be depicted by VI in its relationship with other variables. To study this signature, several catchments in Asia, Australia, and Indonesia were analysed to assess the variations in hydrologic characteristics with vegetation types. Methods used in this study includes geographic identification and pixel marking for studied catchments, analysing time series of VI and LST of the marked pixels, smoothing technique using Savitzky-Golay filter, which is effective for large area and extensive data. Time series of VI, LST, and rainfall from satellite and ground stations coupled with digital elevation models were analysed and presented. This study found that the hydrologic response of vegetation to rainfall variations may be shown in one hydrologic year, in which a drought event can be detected a year later as a suppressed growth. However, an annual rainfall of above average do not promote growth above average as shown by VI. This technique is found to be a robust and tractable approach for assessing catchment dynamics in changing climates.

Keywords: vegetation indices, land surface temperature, vegetation dynamics, catchment

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Authors: Sandrieli Afornali, Adriano Keijiro Maeda, Renato Fedatto Beraldo, Carlos Alberto Mattozo, Ricardo Nascimento Brito

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BACKGROUND: The most used variety in hydrocephalus treatment is the ventriculoperitoneal shunt (VPS). However, it may fails in 20 to 70% of cases. It makes necessary to have alternative cavities for the implantation of the distal catheter. Ventriculo-atrial shunting (VAS) is described as the second option. To our knowledge, there are 121 reported cases of VGB shunt in children until 2020 and a highly variable success rate, from 25 to 100%, with an average of 63% of patients presenting good long-term results. Our goal is to evaluate the epidemiological profile of patients submitted to ventriculo-gallbladder (VGB) shunt and, through a review of literature, to compare our results with others series. METHODS: a retrospective cross-sectional observational study of a case series of nine patients. The medical records of all patients were reviewed, who underwent VGB shunt at the Hospital Pequeno Príncipe from Curitiba, Paraná, Brazil, from January 2014 to October 2022. The inclusion criteria were: patients under 17 years of age with hydrocephalus of any etiology, currently using or prior to VGB shunt. RESULTS: There were 6 (66,7%) male and 3 (33,3%) female. The average age of 73.6 months or 6.1 years at the time of surgery. They were submitted on average 5.1 VPS reviews previous to VGB shunt. Five (55,5%) had complications of VGB shunt: infection (11.1%), atony (11.1%), hypodrainage due to kinking the distal catheter in the solution (11.1%) and ventriculoenteric fistula (22.2%); all these patients were cured at surgical reapproach, and in 2 of them the VGB shunt was reimplanted. Two patients died (22.2%), and five (55,5%) patients maintained the use of VGB shunt in the follow-up period; and in 4 (44.4%) there was never need for review. CONCLUSION: VGB shunt tends to be underestimated because it is still unconventional and little publicized in literature. Our article shows a lower risk of death and similar risk of complications when compared to others altenatives shunts. We emphasize VGB shunt as a safe procedure to be the second option when VPS fails or has contraindications.

Keywords: hydrocephalus, ventricular-gallbladder shunt, VGB shunt, VPS, ventriculoperitoneal shunt, ventriculoatrial shunt

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Authors: Hayriye Anıl, Görkem Kar

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In addition to being rich in renewable energy resources, Turkey is one of the countries that promise potential in geothermal energy production with its high installed power, cheapness, and sustainability. Increasing imbalance penalties become an economic burden for organizations since geothermal generation plants cannot maintain the balance of supply and demand due to the inadequacy of the production forecasts given in the day-ahead market. A better production forecast reduces the imbalance penalties of market participants and provides a better imbalance in the day ahead market. In this study, using machine learning, deep learning, and, time series methods, the total generation of the power plants belonging to Zorlu Natural Electricity Generation, which has a high installed capacity in terms of geothermal, was estimated for the first one and two weeks of March, then the imbalance penalties were calculated with these estimates and compared with the real values. These modeling operations were carried out on two datasets, the basic dataset and the dataset created by extracting new features from this dataset with the feature engineering method. According to the results, Support Vector Regression from traditional machine learning models outperformed other models and exhibited the best performance. In addition, the estimation results in the feature engineering dataset showed lower error rates than the basic dataset. It has been concluded that the estimated imbalance penalty calculated for the selected organization is lower than the actual imbalance penalty, optimum and profitable accounts.

Keywords: machine learning, deep learning, time series models, feature engineering, geothermal energy production forecasting

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Authors: Kriengkrai Assawamartbunlue, Channarong Wantha

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This paper presents the effects of the mean operating pressure on the optimal operating frequency based on temperature differences across stack ends in a thermoacoustic refrigerator. In addition to the length of the resonance tube, components of the thermoacoustic refrigerator have an influence on the operating frequency due to their acoustic properties, i.e. absorptivity, reflectivity and transmissivity. The interference of waves incurs and distorts the original frequency generated by the driver so that the optimal operating frequency differs from the designs. These acoustic properties are not parameters in the designs and it is very complicated to infer their responses. A prototype thermoacoustic refrigerator is constructed and used to investigate its optimal operating frequency compared to the design at various operating pressures. Helium and air are used as working fluids during the experiments. The results indicate that the optimal operating frequency of the prototype thermoacoustic refrigerator using helium is at 6 bar and 490Hz or approximately 20% away from the design frequency. The optimal operating frequency at other mean pressures differs from the design in an unpredictable manner, however, the optimal operating frequency and pressure can be identified by testing.

Keywords: acoustic properties, Carnot’s efficiency, interference of waves, operating pressure, optimal operating frequency, stack performance, standing wave, thermoacoustic refrigerator

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Authors: Yooncheol Lee, Jeongmin Kim, Kwang Ryel Ryu

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This paper deals with the establishment of a short-term operational plan for an air conditioner for efficient energy management of exhibition hall. The short-term operational plan is composed of a time series of operational schedules, which we have searched using genetic algorithms. Establishing operational schedule should be considered the future trends of the variables affecting the exhibition hall environment. To reflect continuously changing factors such as external temperature and occupant, short-term operational plans should be updated in real time. But it takes too much time to evaluate a short-term operational plan using EnergyPlus, a building emulation tool. For that reason, it is difficult to update the operational plan in real time. To evaluate the short-term operational plan, we designed prediction models based on machine learning with fast evaluation speed. This model, which was created by learning the past operational data, is accurate and fast. The collection of operational data and the verification of operational plans were made using EnergyPlus. Experimental results show that the proposed method can save energy compared to the reactive control method.

Keywords: exhibition hall, energy management, predictive model, simulation-based optimization

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Authors: Chi-Ying Yu

Abstract:

Fashion design is, in fact, an aesthetic inquiry of fabric, style and human body. In recent years, close cooperation between the artistic circles and the fashion world has even brought fashion into the arena of contemporary art. This study offers a case study on the avant-garde fashion designer Alexander McQueen, investigating how he and his brand translate fashion into contemporary art at various levels. Firstly, in terms of his designs themselves, McQueen demonstrates through fashions his declarations on political and gender issues, demonstrating his unique barbarian aesthetics and creating an enchanting sublimity. Secondly, McQueen extends his fashion aesthetics into a cross-disciplinary performing method, and raises catwalk shows to the level of complete artistic experience. Finally, and also most importantly, the brand has been producing fashion movies for its seasonal design series. By means of an abstract, non-narrative visual language, these films essentially transform people’s experience of clothing – from the senses to the pure visual. This is not simply a cross-media artistic practice, but much more fundamentally a discourse on contemporary perceptual experience. From the case of Alexander McQueen, it can be argued that avant-garde fashion has broken through the boundary between design and art, issuing its own art manifesto through the field of art or non-art.

Keywords: Alexander McQueen, avant-garde fashion, contemporary art, fashion film

Procedia PDF Downloads 312

Authors: Gabriela Teodorescu, Ioana Daniela Dulama

Abstract:

In an ever-changing society, the education system needs to constantly evolve to meet market demands. During its 30 years of existence, Valahia University of Targoviste (VUT) tried to offer its students a series of teaching-learning schemes that would prepare them for a remarkable career. In VUT, the achievement of performance through innovation can be analyzed by reference to several key indicators (i.e., university climate, university resources, and innovative methods applied to classes), but it is possible to differentiate between activities in the classic format: participate to courses; interactive seminars and tutorials; laboratories, workshops, project-based learning; entrepreneurial activities, through simulated enterprises; mentoring activities. Thus, VUT has implemented over time a series of schemes and projects based on innovation and entrepreneurship, and in this paper, some of them will be briefly presented. All these schemes were implemented by facilitating an effective dialog with students and the opportunity to listen to their views at all levels of the University and in all fields of study, as well as by developing a partnership with students to set out priority areas. VUT demonstrates innovation and entrepreneurial capacity through its new activities for higher education, which will attract more partnerships and projects dedicated to students.

Keywords: Romania, project-based learning, entrepreneurial activities, simulated enterprises

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Authors: H. Cano, P. Ferrer, N. Garcia, M. Popovic, J. Zapata

Abstract:

Positive Reinforcement Training is a well-known methodology which has been reported frequently to be used in captive non-human primates. As a matter of fact, it is an invaluable tool for different purposes related with animal welfare, such as primate husbandry and environmental enrichment. It is also essential to perform some cognitive experiments. The main propose of this pilot study was to establish an efficient protocol to train captive olive baboons (Papio anubis). This protocol seems to be vital in the context of a larger research program in which it will be necessary to train a complete population of around 40 baboons. Baboons were studied at the Veterinary Research Farm of the University of Murcia. Temporally isolated animals were trained to perform three basic tasks. Firstly, they were required to take food prices directly from the researchers’ hands. Then a clicker sound or bridge stimulus was added each time the animal acceded to the reinforcement. Finally, they were trained to touch a target, consisted of a whip with a red ball in its end, with their hands or their nose. When the subject completed correctly this task, it was also exposed to the bridge stimulus and awarded with a food price, such as a portion of banana, orange, apple, peach or a raisin. Two protocols were tested during this experiment. In both of them, there were 6 series of 2min training periods each day. However, in the first protocol, the series consisted in 3 trials, whereas in the second one, in each series there were 5 trials. A reliable performance was obtained with only 6 days of training in the case of the 5-trials protocol. However, with the 3-trials one, 26 days of training were needed. As a result, the 5-trials protocol seems to be more effective than the 3-trials one, in order to teach these three basic tasks to olive baboons. In consequence, it will be used to train the rest of the colony.

Keywords: captive primates, olive baboon, positive reinforcement training, Papio anubis, training

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Authors: Weili Jiang, Simon Cadavid Lopera, Klaus Drechsler

Abstract:

Fuel cell vehicle has become the most competitive solution for the transportation sector in the hydrogen economy. Type IV pressure vessel is currently the most popular and widely developed technology for the on-board storage, based on their high reliability and relatively low cost. Due to the stringent requirement on mechanical performance, the pressure vessel is subject to great amount of composite material, a major cost driver for the hydrogen tanks. Evidently, the optimization of composite layup design shows great potential in reducing the overall material usage, yet requires comprehensive understanding on underlying mechanisms as well as the influence of different design parameters on mechanical performance. Given the type of materials and manufacturing processes by which the type IV pressure vessels are manufactured, the design and optimization are a nuanced subject. The manifold of stacking sequence and fiber orientation variation possibilities have an out-standing effect on vessel strength due to the anisotropic property of carbon fiber composites, which make the design space high dimensional. Each variation of design parameters requires computational resources. Using finite element analysis to evaluate different designs is the most common method, however, the model-ing, setup and simulation process can be very time consuming and result in high computational cost. For this reason, it is necessary to build a reliable automation scheme to set up and analyze the di-verse composite layups. In this research, the simulation process of different tank designs regarding various parameters is conducted and automatized in a commercial finite element analysis framework Abaqus. Worth mentioning, the modeling of the composite overwrap is automatically generated using an Abaqus-Python scripting interface. The prediction of the winding angle of each layer and corresponding thickness variation on dome region is the most crucial step of the modeling, which is calculated and implemented using analytical methods. Subsequently, these different composites layups are simulated as axisymmetric models to facilitate the computational complexity and reduce the calculation time. Finally, the results are evaluated and compared regarding the ultimate tank strength. By automatically modeling, evaluating and comparing various composites layups, this system is applicable for the optimization of the tanks structures. As mentioned above, the mechanical property of the pressure vessel is highly dependent on composites layup, which requires big amount of simulations. Consequently, to automatize the simulation process gains a rapid way to compare the various designs and provide an indication of the optimum one. Moreover, this automation process can also be operated for creating a data bank of layups and corresponding mechanical properties with few preliminary configuration steps for the further case analysis. Subsequently, using e.g. machine learning to gather the optimum by the data pool directly without the simulation process.

Keywords: type IV pressure vessels, carbon composites, finite element analy-sis, automation of simulation process

Procedia PDF Downloads 111

Authors: Ji-yang Yu, Dan Huang, Guo-ping Feng, Xin Li, Lu-yuan Wang

Abstract:

The navigation satellite network, especially the Beidou MEO Constellation, can relay data effectively with wide coverage and is applied in navigation, detection, and position widely. But the constellation has not been completed, and the amount of satellites on-board is not enough to cover the earth, which makes the data-relay disrupted or delayed in the transition process. The data-relay function needs to tolerant the delay or disruption in some extension, which make the Beidou MEO Constellation a delay/disruption-tolerant network (DTN). The traditional DTN designs mainly employ the relay table as the basic of data path schedule computing. But in practical application, especially in critical condition, such as the war-time or the infliction heavy losses on the constellation, parts of the nodes may become invalid, then the traditional DTN design could be useless. Furthermore, when transmitting the critical message in the navigation system, the maximum priority strategy is used, but the nodes still inquiry the relay table to design the path, which makes the delay more than minutes. Under this circumstances, it needs a function which could compute the optimum data path on-board in real-time according to the constellation states. The on-board critical message transmission design for navigation satellite delay/disruption-tolerant network (DTN) is proposed, according to the characteristics of navigation satellite network. With the real-time computation of parameters in the network link, the least-delay transition path is deduced to retransmit the critical message in urgent conditions. First, the DTN model for constellation is established based on the time-varying matrix (TVM) instead of the time-varying graph (TVG); then, the least transition delay data path is deduced with the parameters of the current node; at last, the critical message transits to the next best node. For the on-board real-time computing, the time delay and misjudges of constellation states in ground stations are eliminated, and the residual information channel for each node can be used flexibly. Compare with the minute’s delay of traditional DTN; the proposed transmits the critical message in seconds, which improves the re-transition efficiency. The hardware is implemented in FPGA based on the proposed model, and the tests prove the validity.

Keywords: critical message, DTN, navigation satellite, on-board, real-time

Procedia PDF Downloads 330

Authors: Abhishek Kumar Chandra, Kaushal Kishor, Wasim Khan, Dhananjay Singh, M. S. Alam

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Single phase fluid flow through series of uniform microchannels connected via transition section (converging-diverging section with or without throat) was analytically and numerically studied to characterize the flow within the channel and in the transition sections. Three sets of microchannels of diameters 100, 184, and 249 μm were considered for investigation. Each set contains 10 numbers of microchannels of length 20 mm, connected to each other in series via transition sections. Transition section consists of either converging-diverging section with throat or without throat. The effect of non-uniformity in microchannels on pressure drop was determined by passing water/air through the set of channels for Reynolds number 50 to 1000. Compressibility and rarefaction effects in transition sections were also tested analytically and numerically for air flow. The analytical and numerical results show that these configurations can be used in enhancement of transport processes. However, converging-diverging section without throat shows superior performance over with throat configuration.

Keywords: contraction-expansion flow, integrated microchannel, microchannel network, single phase flow

Procedia PDF Downloads 263

Authors: Rachid Essamoud, Abdelkrim Afenzar, Ahmed Belqadi

Abstract:

During the Early Mesozoic, the northwestern part of the African continent was affected by initial fracturing associated with the early stages of the opening of the Central Atlantic (Atlantic Rift). During this rifting phase, the Moroccan Meseta experienced an extensive tectonic regime. This extension favored the formation of a set of rift-type basins, including the Mohammedia-Benslimane-ElGara-Berrechid basin. Thus, it is essential to know the nature of the deposits in this basin and their evolution over time as well as their relationship with the basaltic effusion of the Central Atlantic Magmatic Province (CAMP). These deposits are subdivided into two large series: The Lower clay-salt series attributed to the Triassic and the Upper clay-salt series attributed to the Liassic. The two series are separated by the Upper Triassic-Lower Liassic basaltic complex. The detailed sedimentological analysis made it possible to characterize four mega-sequences, fifteen types of facies and eight architectural elements and facies associations in the Triassic series. A progressive decrease observed in paleo-slope over time led to the evolution of the paleoenvironment from a proximal system of alluvial fans to a braided fluvial style, then to an anastomosed system. These environments eventually evolved into an alluvial plain associated with a coastal plain where playa lakes, mudflats and lagoons had developed. The pure and massive halitic facies at the top of the series probably indicate an evolution of the depositional environment towards a shallow subtidal environment. The presence of these evaporites indicates a climate that favored their precipitation, in this case, a fairly hot and humid climate. The sedimentological analysis of the supra-basaltic part shows that during the Lower Liassic, the paleopente after basaltic effusion remained weak with distal environments. The faciological analysis revealed the presence of four major sandstone, silty, clayey and evaporitic lithofacies organized in two mega-sequences: the sedimentation of the first rock-salt mega-sequence took place in a brine depression system free, followed by saline mudflats under continental influences. The upper clay mega-sequence displays facies documenting sea level fluctuations from the final transgression of the Tethys or the opening Atlantic. Saliferous sedimentation is therefore favored from the Upper Triassic, but experienced a sudden rupture by the emission of basaltic flows which are interstratified in the azoic salt clays of very shallow seas. This basaltic emission which belongs to the CAMP would come from a fissural volcanism probably carried out through transfer faults located in the NW and SE of the basin. Their emplacement is probably subaquatic to subaerial. From a chronological and paleogeographic point of view, this main volcanism, dated between the Upper Triassic and the Lower Liassic (180-200 MA), is linked to the fragmentation of Pangea and managed by a progressive expansion triggered in the West in close relation with the initial phases of Central Atlantic rifting and seems to coincide with the major mass extinction at the Triassic-Jurassic boundary.

Keywords: Basalt, CAMP, Liassic, sedimentology, Triassic, Morocco

Procedia PDF Downloads 55

Authors: Ersilio Tushaj

Abstract:

The efficient solution that satisfies the optimal condition is an important issue in the structural engineering design problem. The new codes of structural design consist in design methodology that looks after the exploitation of the total resources of the construction material. In recent years some non-deterministic or meta-heuristic structural optimization algorithms have been developed widely in the research community. These methods search the optimum condition starting from the simulation of a natural phenomenon, such as survival of the fittest, the immune system, swarm intelligence or the cooling process of molten metal through annealing. Among these techniques the most known are: the genetic algorithms, simulated annealing, evolution strategies, particle swarm optimization, tabu search, ant colony optimization, harmony search and big bang crunch optimization. In this study, five of these algorithms are applied for the optimum weight design of a steel truss structure with variable geometry but fixed topology. The design process selects optimum distances and size sections from a set of commercial steel profiles. In the formulation of the design problem are considered deflection limitations, buckling and allowable stress constraints. The approach is repeated starting from different initial populations. The design problem topology is taken from an existing steel structure. The optimization process helps the engineer to achieve good final solutions, avoiding the repetitive evaluation of alternative designs in a time consuming process. The algorithms used for the application, the results of the optimal solutions, the number of iterations and the minimal weight designs, will be reported in the paper. Based on these results, it would be estimated, the amount of the steel that could be saved by applying structural analysis combined with non-deterministic optimization methods.

Keywords: structural optimization, non-deterministic methods, truss structures, steel truss

Procedia PDF Downloads 207