Search results for: hardware in loop (HIL)

Authors: John Lamb, Robert Epstein, Vasundhara L. Bhupathi, Sanjeev Kumar Marimekala

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As we enter the new era of Artificial Intelligence (AI) and Cloud Computing, we mostly rely on the Machine and Natural Language Processing capabilities of AI, and Energy Efficient Hardware and Software Devices in almost every industry sector. In these industry sectors, much emphasis is on developing new and innovative methods for producing and conserving energy and sustaining the depletion of natural resources. The core pillars of sustainability are economic, environmental, and social, which is also informally referred to as the 3 P's (People, Planet and Profits). The 3 P's play a vital role in creating a core Sustainability Model in the Enterprise. Natural resources are continually being depleted, so there is more focus and growing demand for renewable energy. With this growing demand, there is also a growing concern in many industries on how to reduce carbon emissions and conserve natural resources while adopting sustainability in corporate business models and policies. In our paper, we would like to discuss the driving forces such as Climate changes, Natural Disasters, Pandemic, Disruptive Technologies, Corporate Policies, Scaled Business Models and Emerging social media and AI platforms that influence the 3 main pillars of Sustainability (3P’s). Through this paper, we would like to bring an overall perspective on enterprise strategies and the primary focus on bringing cultural shifts in adapting energy-efficient operational models. Overall, many industries across the globe are incorporating core sustainability principles such as reducing energy costs, reducing greenhouse gas (GHG) emissions, reducing waste and increasing recycling, adopting advanced monitoring and metering infrastructure, reducing server footprint and compute resources (Shared IT services, Cloud computing, and Application Modernization) with the vision for a sustainable environment.

Keywords: climate change, pandemic, disruptive technology, government policies, business model, machine learning and natural language processing, AI, social media platform, cloud computing, advanced monitoring, metering infrastructure

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Authors: Carolina Zambrana, Grover Zurita

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The food loss production that occurs in deficient agricultural production is one of the major problems worldwide. This puts the population's food security and the efficiency of farming investments at risk. It is to be expected that this food security will be achieved with the own and efficient production of each country. It will have an impact on the well-being of its population and, thus, also on food sovereignty. The production losses in quantity and quality occur due to the lack of efficient detection of diseases at an early stage. It is very difficult to solve the agriculture efficiency using traditional methods since it takes a long time to be carried out due to detection imprecision of the main diseases, especially when the production areas are extensive. Therefore, the main objective of this research study is to perform a systematic literature review, of the latest five years, of Precision Agriculture (PA) to be able to understand the state of the art of the set of new technologies, procedures, and optimization processes with Artificial Intelligence (AI). This study will focus on Corns, Potatoes, and Rice diagnostic diseases. The extensive literature review will be performed on Elsevier, Scopus, and IEEE databases. In addition, this research will focus on advanced digital imaging processing and the development of software and hardware for PA. The convolution neural network will be handling special attention due to its outstanding diagnostic results. Moreover, the studied data will be incorporated with artificial intelligence algorithms for the automatic diagnosis of crop quality. Finally, precision agriculture with technology applied to the agricultural sector allows the land to be exploited efficiently. This system requires sensors, drones, data acquisition cards, and global positioning systems. This research seeks to merge different areas of science, control engineering, electronics, digital image processing, and artificial intelligence for the development, in the near future, of a low-cost image measurement system that allows the optimization of crops with AI.

Keywords: precision agriculture, convolutional neural network, deep learning, artificial intelligence

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Authors: Irfan Anjum Manarvi, Zahid Ali kaimkhani

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Predicting location of the fracture in human bones has been a keen area of research for the past few decades. A variety of tests for hardness, deformation, and strain field measurement have been conducted in the past; but considered insufficient due to various limitations. Researchers, therefore, have proposed further studies due to inaccuracies in measurement methods, testing machines, and experimental errors. Advancement and availability of hardware, measuring instrumentation, and testing machines can now provide remedies to these limitations. The human foot is a critical part of the body exposed to various forces throughout its life. A number of products are developed for using it for protection and care, which many times do not provide sufficient protection and may itself become a source of stress due to non-consideration of the delicacy of bones in the feet. A continuous strain or overloading on feet may occur resulting to discomfort and even fracture. Mechanical properties of Tarsals, Metatarsals, and phalanges are, therefore, the primary area of consideration for all such design applications. Hardness is one of the mechanical properties which are considered very important to establish the mechanical resistance behavior of a material against applied loads. Past researchers have worked in the areas of investigating mechanical properties of these bones. However, their results were based on a limited number of experiments and taking average values of hardness due to either limitation of samples or testing instruments. Therefore, they proposed further studies in this area. The present research has been carried out to develop a hardness map of the human foot by measuring micro hardness at various locations of these bones. Results are compiled in the form of distance from a reference point on a bone and the hardness values for each surface. The number of test results is far more than previous studies and are spread over a typical bone to give a complete hardness map of these bones. These results could also be used to establish other properties such as stress and strain distribution in the bones. Also, industrial engineers could use it for design and development of various accessories for human feet health care and comfort and further research in the same areas.

Keywords: tarsals, metatarsals, phalanges, hardness testing, biomechanics of human foot

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Authors: Parimalah Velo, Ahmad Zakaria

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Introduction: Monte Carlo simulations of preclinical imaging systems allow opportunity to enable new research that could range from designing hardware up to discovery of new imaging application. The simulation system which could accurately model an imaging modality provides a platform for imaging developments that might be inconvenient in physical experiment systems due to the expense, unnecessary radiation exposures and technological difficulties. The aim of present study is to validate the Monte Carlo simulation of thyroid phantom imaging using Geant4-GATE for Siemen’s e-cam single head gamma camera. Upon the validation of the gamma camera simulation model by comparing physical characteristic such as energy resolution, spatial resolution, sensitivity, and dead time, the GATE simulation of thyroid phantom imaging is carried out. Methods: A thyroid phantom is defined geometrically which comprises of 2 lobes with 80mm in diameter, 1 hot spot, and 3 cold spots. This geometry accurately resembling the actual dimensions of thyroid phantom. A planar image of 500k counts with 128x128 matrix size was acquired using simulation model and in actual experimental setup. Upon image acquisition, quantitative image analysis was performed by investigating the total number of counts in image, the contrast of the image, radioactivity distributions on image and the dimension of hot spot. Algorithm for each quantification is described in detail. The difference in estimated and actual values for both simulation and experimental setup is analyzed for radioactivity distribution and dimension of hot spot. Results: The results show that the difference between contrast level of simulation image and experimental image is within 2%. The difference in the total count between simulation and actual study is 0.4%. The results of activity estimation show that the relative difference between estimated and actual activity for experimental and simulation is 4.62% and 3.03% respectively. The deviation in estimated diameter of hot spot for both simulation and experimental study are similar which is 0.5 pixel. In conclusion, the comparisons show good agreement between the simulation and experimental data.

Keywords: gamma camera, Geant4 application of tomographic emission (GATE), Monte Carlo, thyroid imaging

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Authors: Faiz Khan Mohammad, Saumya Ray Chaudhari, Raghunathan Rengaswamy, Swagatika Sahoo

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Cholera caused by pathogenic gut bacteria Vibrio Cholerae (VC), is a major health problem in developing countries. Different strains of VC exhibit variable responses subject to different extracellular medium (Nag et al, Infect Immun, 2018). In this study, we present a new approach to model the variable VC responses in mono- and co-cultures, subject to continuously changing growth medium, which is otherwise difficult via simple FBA model. Nine VC strain and seven E. coli (EC) models were assembled and considered. A continuously changing medium is modelled using a new iterative-based controlled medium technique (ITC). The medium is appropriately prefixed with the VC model secretome. As the flux through the bacteria biomass increases secretes certain by-products. These products shall add-on to the medium, either deviating the nutrient potential or block certain metabolic components of the model, effectively forming a controlled feed-back loop. Different VC models were setup as monoculture of VC in glucose enriched medium, and in co-culture with VC strains and EC. Constrained to glucose enriched medium, (i) VC_Classical model resulted in higher flux through acidic secretome suggesting a pH change of the medium, leading to lowering of its biomass. This is in consonance with the literature reports. (ii) When compared for neutral secretome, flux through acetoin exchange was higher in VC_El tor than the classical models, suggesting El tor requires an acidic partner to lower its biomass. (iii) Seven of nine VC models predicted 3-methyl-2-Oxovaleric acid, mysirtic acid, folic acid, and acetate significantly affect corresponding biomass reactions. (iv) V. parhemolyticus and vulnificus were found to be phenotypically similar to VC Classical strain, across the nine VC strains. The work addresses the advantage of the ITC over regular flux balance analysis for modelling varying growth medium. Future expansion to co-cultures, potentiates the identification of novel interacting partners as effective cholera therapeutics.

Keywords: cholera, vibrio cholera El. tor, vibrio cholera classical, acetate

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Authors: Nicole Scott, Emily Dwyer, Cara Patrissy, Samantha Bonventre, Lina Begdache

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Across North America, the use and abuse of Attention Deficit Hyperactivity Disorder (ADHD) medication, cannabis, nicotine, and other psychoactive substances across college campuses have become an increasingly prevalent problem. Students frequently use these substances to aid their studying or deal with their mental health issues. However, it is still unknown what psychoactive substances are likely to be abused when college students illicitly use ADHD medication. In addition, it is not clear which psychoactive substance is associated with mental distress. Thus, the purpose of this study is to fill these gaps by assessing the use of different psychoactive substances when illicit ADHD medication is used; and how this association relates to mental stress. A total of 702 undergraduate students from different college campuses in the U.S. completed an anonymous survey distributed online. Data were self-reported on demographics, the use of ADHD medications, cannabis, nicotine, other psychoactive drugs, and mental distress, and feelings and opinions on the use of illicit study drugs were all included in the survey. Mental distress was assessed using the Kessler Psychological Distress 6 Scale. Data were analyzed in SPSS, Version 25.0, using Pearson’s Correlation Coefficient. Our results show that use of ADHD medication, cannabis use (non-frequent and very frequent), and nicotine use (non-frequent and very frequent), there were both statistically significant positive and negative correlations to specific psychoactive substances and their corresponding frequencies. Along the same lines, ADHD medication, cannabis use (non-frequent and very frequent), and nicotine use (non-frequent and very frequent) had statistically significant positive and negative correlations to specific mental distress experiences. As these findings are combined, a vicious loop can initiate a cycle where individuals who abuse psychoactive substances may or may not be inclined to use other psychoactive substances. This may later inhibit brain functions in those main areas of the brain stem, amygdala, and prefrontal cortex where this vicious cycle may or may not impact their mental distress. Addressing the impact of study drug abuse and its potential to be associated with further substance abuse may provide an educational framework and support proactive approaches to promote awareness among college students.

Keywords: stimulant, depressant, nicotine, ADHD medication, psychoactive substances, mental health, illicit, ecstasy, adrenochrome

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Authors: Miroslav Hyza, Petr Rulik, Vojtech Bednar, Jan Sury

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An early and reliable detection of an increased radioactivity level in the atmosphere is one of the key aspects of atmospheric radiological monitoring. Although the standard laboratory procedures provide detection limits as low as few µBq/m³, their major drawback is the delayed result reporting: typically a few days. This issue is the main objective of the HAMRAD project, which gave rise to a prototype of an autonomous monitoring device. It is based on the idea of sequential aerosol sampling using a carrousel sample changer combined with a gamma-ray spectrometer. In our hardware configuration, the air is drawn through a filter positioned on the carrousel so that it could be rotated into the measuring position after a preset sampling interval. Filter analysis is performed via a 50% HPGe detector inside an 8.5cm lead shielding. The spectrometer output signal is then analyzed using DSP electronics and Gamwin software with preset nuclide libraries and other analysis parameters. After the counting, the filter is placed into a storage bin with a capacity of 250 filters so that the device can run autonomously for several months depending on the preset sampling frequency. The device is connected to a central server via GPRS/GSM where the user can view monitoring data including raw spectra and technological data describing the state of the device. All operating parameters can be remotely adjusted through a simple GUI. The flow rate is continuously adjustable up to 10 m³/h. The main challenge in spectrum analysis is the natural background subtraction. As detection limits are heavily influenced by the deposited activity of radon decay products and the measurement time is fixed, there must exist an optimal sample decay time (delayed spectrum acquisition). To solve this problem, we adopted a simple procedure based on sequential spectrum acquisition and optimal partial spectral sum with respect to the detection limits for a particular radionuclide. The prototyped device proved to be able to detect atmospheric contamination at the level of mBq/m³ per an 8h sampling.

Keywords: aerosols, atmosphere, atmospheric radioactivity monitoring, autonomous sampler

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

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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

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Authors: Malcolm Dinovitzer, Calvin Miller, Adam Hacker, Gabriel Wong, Zach Annen, Padmassun Rajakareyar, Jordan Mulvihill, Mostafa S.A. ElSayed

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The research work presented in this paper is developed by the Blended Wing Body (BWB) Unmanned Aerial Vehicle (UAV) team, a fourth-year capstone project at Carleton University Department of Mechanical and Aerospace Engineering. Here, a clean sheet UAV with BWB configuration is designed and optimized using Multiscale Design Optimization (MSDO) approach employing lattice materials taking into consideration design for additive manufacturing constraints. The BWB-UAV is being developed with a mission profile designed for surveillance purposes with a minimum payload of 1000 grams. To demonstrate the design methodology, a single design loop of a sample rib from the airframe is shown in details. This includes presentation of the conceptual design, materials selection, experimental characterization and residual thermal stress distribution analysis of additively manufactured materials, manufacturing constraint identification, critical loads computations, stress analysis and design optimization. A dynamic turbulent critical load case was identified composed of a 1-g static maneuver with an incremental Power Spectral Density (PSD) gust which was used as a deterministic design load case for the design optimization. 2D flat plate Doublet Lattice Method (DLM) was used to simulate aerodynamics in the aeroelastic analysis. The aerodynamic results were verified versus a 3D CFD analysis applying Spalart-Allmaras and SST k-omega turbulence to the rigid UAV and vortex lattice method applied in the OpenVSP environment. Design optimization of a single rib was conducted using topology optimization as well as MSDO. Compared to a solid rib, weight savings of 36.44% and 59.65% were obtained for the topology optimization and the MSDO, respectively. These results suggest that MSDO is an acceptable alternative to topology optimization in weight critical applications while preserving the functional requirements.

Keywords: blended wing body, multiscale design optimization, additive manufacturing, unmanned aerial vehicle

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Authors: Jegede Oluseye Oladayo

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The study mapped innovation activities in the formal and informal mining sector in Nigeria. Data were collected through primary and secondary sources. Primary data were collected through guided questionnaire administration, guided interviews and personal observation. A purposive sampling method was adopted to select firms that are micro, small and medium enterprises. The study covered 100 (50 in the formal sector and 50 in the informal sector) purposively selected companies in south-western Nigeria. Secondary data were collected from different published sources. Data were analysed using descriptive and inferential statistics. Of the four types of technological innovations sampled, organisational innovation was found to be highest both in the formal (100%) and informal (100%) sectors, followed by process innovation: 60% in the formal sector and 28% in the informal sector, marketing innovation and diffusion based innovation were implemented by 64% and 4% respectively in the formal sector. There were no R&D activities (intramural or extramural) in both sectors, however, innovation activities occur at moderate levels in the formal sector. This is characterised by acquisition of machinery, equipment, hardware (100%), software (56), training (82%) and acquisition of external knowledge (60%) in the formal sector. In the informal sector, innovation activities were characterised by acquisition of external knowledge (100%), training/learning by experience (100%) and acquisition of tools (68%). The impact of innovation on firm’s performance in the formal sector was expressed mainly as increased capacity of production (100%), reduced production cost per unit of labour (88%), compliance with governmental regulatory requirements (72%) and entry on new markets (60%). In the informal sector, the impact of innovation was mainly expressed in improved flexibility of production (70%) and machinery/energy efficiency (70%). The important technological driver of process innovation in the mining sector was acquisition of machinery which accounts for the prevalence of 100% both in the formal and informal sectors. Next to this is training and re-training of technical staff, 74% in both the formal and the informal sector. Other factors influencing organisational innovation are skill of workforce with a prevalence of 80% in both the formal and informal sector. The important technological drivers include educational background of the manager/head of technical department (54%) for organisational innovation and (50%) for process innovation in the formal sector. The study concluded that innovation competence of the firms was mostly organisational changes.

Keywords: innovation prevalence, innovation activities, innovation performance, innovation drivers

Procedia PDF Downloads 379

Authors: O. Anwar Beg, Armghan Zubair, Sireetorn Kuharat, Meisam Babaie

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In this work, motivated by rocket channel cooling applications, we describe recent CFD simulations of turbulent convective heat transfer in mini-channels at different aspect ratios. ANSYS FLUENT software has been employed with a mean average error of 5.97% relative to Forrest’s MIT cooling channel study (2014) at a Reynolds number of 50,443 with a Prandtl number of 3.01. This suggests that the simulation model created for turbulent flow was suitable to set as a foundation for the study of different aspect ratios in the channel. Multiple aspect ratios were also considered to understand the influence of high aspect ratios to analyse the best performing cooling channel, which was determined to be the highest aspect ratio channels. Hence, the approximate 28:1 aspect ratio provided the best characteristics to ensure effective cooling. A mesh convergence study was performed to assess the optimum mesh density to collect accurate results. Hence, for this study an element size of 0.05mm was used to generate 579,120 for proper turbulent flow simulation. Deploying a greater bias factor would increase the mesh density to the furthest edges of the channel which would prove to be useful if the focus of the study was just on a single side of the wall. Since a bulk temperature is involved with the calculations, it is essential to ensure a suitable bias factor is used to ensure the reliability of the results. Hence, in this study we have opted to use a bias factor of 5 to allow greater mesh density at both edges of the channel. However, the limitations on mesh density and hardware have curtailed the sophistication achievable for the turbulence characteristics. Also only linear rectangular channels were considered, i.e. curvature was ignored. Furthermore, we only considered conventional water coolant. From this CFD study the variation of aspect ratio provided a deeper appreciation of the effect of small to high aspect ratios with regard to cooling channels. Hence, when considering an application for the channel, the geometry of the aspect ratio must play a crucial role in optimizing cooling performance.

Keywords: rocket channel cooling, ANSYS FLUENT CFD, turbulence, convection heat transfer

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Authors: Zhichao Song, Swanand Vaidya

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Nowadays, most portable (e.g., smartphones) and wearable (e.g., smartwatches and earphones) consumer hardware are designed to be dustproof following IP5 or IP6 ratings to ensure the product is able to handle potentially dusty outdoor environments. On the other hand, the design guideline is relatively vague for indoor devices (e.g., smart displays and speakers). While it is generally believed that the indoor environment is much less dusty, in certain circumstances, dust ingression is still able to cause functional failures, such as microphone frequency response shift and camera black spot, or cosmetic dissatisfaction, mainly the dust build up in visible pockets and gaps which is hard to clean. In this paper, we developed a simulation methodology to analyze dust settlement and ingression into known ports of a device. A closed system is initialized with dust particles whose sizes follow Weibull distribution based on data collected in a user study, and dust particle movement was approximated as a settlement in stationary fluid, which is governed by Stokes’ law. Following this method, we simulated dust ingression into MEMS microphone through the acoustic port and protective mesh. Various design and environmental parameters are evaluated including mesh pore size, acoustic port depth-to-diameter ratio, mass density of dust material and inclined angle of microphone port. Although the dependencies of dust resistance on these parameters are all monotonic, smaller mesh pore size, larger acoustic depth-to-opening ratio and more inclined microphone placement (towards horizontal direction) are preferred for dust resistance; these preferences may represent certain trade-offs in audio performance and compromise in industrial design. The simulation results suggest the quantitative ranges of these parameters, with more pronounced effects in the improvement of dust resistance. Based on the simulation results, we proposed several design guidelines that intend to achieve an overall balanced design from audio performance, dust resistance, and flexibility in industrial design.

Keywords: dust settlement, numerical simulation, microphone design, Weibull distribution, Stoke's equation

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Authors: Samuel John, S. Sharanya

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Automation has become an important part of our life. It has been used to control home entertainment systems, changing the ambience of rooms for different events etc. One of the main parameters to control in a smart home is the atmospheric comfort. Atmospheric comfort mainly includes temperature and relative humidity. In homes, the desired temperature of different rooms varies from 20 °C to 25 °C and relative humidity is around 50%. However, it varies widely. Hence, automated measurement of these parameters to ensure comfort assumes significance. To achieve this, a fuzzy logic controller using Arduino was developed using MATLAB. Arduino is an open source hardware consisting of a 24 pin ATMEGA chip (atmega328), 14 digital input /output pins and an inbuilt ADC. It runs on 5v and 3.3v power supported by a board voltage regulator. Some of the digital pins in Aruduino provide PWM (pulse width modulation) signals, which can be used in different applications. The Arduino platform provides an integrated development environment, which includes support for c, c++ and java programming languages. In the present work, soft sensor was introduced in this system that can indirectly measure temperature and humidity and can be used for processing several measurements these to ensure comfort. The Sugeno method (output variables are functions or singleton/constant, more suitable for implementing on microcontrollers) was used in the soft sensor in MATLAB and then interfaced to the Arduino, which is again interfaced to the temperature and humidity sensor DHT11. The temperature-humidity sensor DHT11 acts as the sensing element in this system. Further, a capacitive humidity sensor and a thermistor were also used to support the measurement of temperature and relative humidity of the surrounding to provide a digital signal on the data pin. The comfort sensor developed was able to measure temperature and relative humidity correctly. The comfort percentage was calculated and accordingly the temperature in the room was controlled. This system was placed in different rooms of the house to ensure that it modifies the comfort values depending on temperature and relative humidity of the environment. Compared to the existing comfort control sensors, this system was found to provide an accurate comfort percentage. Depending on the comfort percentage, the air conditioners and the coolers in the room were controlled. The main highlight of the project is its cost efficiency.

Keywords: arduino, DHT11, soft sensor, sugeno

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Authors: Deeksha Karunakar

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The gaming industry is one of the biggest industries in the world. Video games are interactive works of authorship that require the execution of a computer programme on specialized hardware but which also incorporate a wide variety of other artistic mediums, such as music, scripts, stories, video, paintings, and characters, into which the player takes an active role. Therefore, video games are not made as singular, simple works but rather as a collection of elements that, if they reach a certain level of originality and creativity, can each be copyrighted on their own. A video game is made up of a wide variety of parts, all of which combine to form the overall sensation that we, the players, have while playing. The entirety of the components is implemented in the form of software code, which is then translated into the game's user interface. Even while copyright protection is already in place for the coding of software, the work that is produced because of that coding can also be protected by copyright. This includes the game's storyline or narrative, its characters, and even elements of the code on their own. In each sector, there is a potential legal framework required, and the gaming industry also requires legal frameworks. This represents the importance of intellectual property laws in each sector. This paper will explore the beginnings of video games, the various aspects of game copyrights, and the approach of the courts, including examples of a few different instances. Although the creative arts have always been known to draw inspiration from and build upon the works of others, it has not always been simple to evaluate whether a game has been cloned. The video game business is experiencing growth as it has never seen before today. The majority of today's video games are both pieces of software and works of audio-visual art. Even though the existing legal framework does not have a clause specifically addressing video games, it is clear that there is a great many alternative means by which this protection can be granted. This paper will represent the importance of copyright and trademark laws in the gaming industry and its regulations with the help of relevant case laws via utilizing doctrinal methodology to support its findings. The aim of the paper is to make aware of the applicability of intellectual property laws in the gaming industry and how the justice system is evolving to adapt to such new industries. Furthermore, it will provide in-depth knowledge of their relationship with each other.

Keywords: copyright, DMCA, gaming industry, trademark, WIPO

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Authors: Mateen A Khan, Taj Mohammad, Md. Imtaiyaz Hassan

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Alzheimer’s disease is characterized by the accumulation of the processing products of the amyloid beta peptide cleaved by amyloid precursor protein (APP). Iron increases the synthesis of amyloid beta peptides, which is why iron is present in Alzheimer's disease patients' amyloid plaques. Iron misregulation in the brain is linked to the overexpression of APP protein, which is directly related to amyloid-β aggregation in Alzheimer’s disease. The APP 5'-UTR region encodes a functional iron-responsive element (IRE) stem-loop that represents a potential target for modulating amyloid production. Targeted regulation of APP gene expression through the modulation of 5’-UTR sequence function represents a novel approach for the potential treatment of AD because altering APP translation can be used to improve both the protective brain iron balance and provide anti-amyloid efficacy. The molecular docking analysis of APP IRE RNA with eukaryotic translation initiation factors yields several models exhibiting substantial binding affinity. The finding revealed that the interaction involved a set of functionally active residues within the binding sites of eIF4F. Notably, APP IRE RNA and eIF4F interaction were stabilized by multiple hydrogen bonds with residues of APP IRE RNA and eIF4F. It was evident that APP IRE RNA exhibited a structural complementarity that tightly fit within binding pockets of eIF4F. The simulation studies further revealed the stability of the complexes formed between RNA and eIF4F, which is crucial for assessing the strength of these interactions and subsequent roles in the pathophysiology of Alzheimer’s disease. In addition, MD simulations would capture conformational changes in the IRE RNA and protein molecules during their interactions, illustrating the mechanism of interaction, conformational change, and unbinding events and how it may affect aggregation propensity and subsequent therapeutic implications. Our binding studies correlated well with the translation efficiency of APP mRNA. Overall, the outcome of this study suggests that the genomic modification and/or inhibiting the expression of amyloid protein by targeting APP IRE RNA can be a viable strategy to identify potential therapeutic targets for AD and subsequently be exploited for developing novel therapeutic approaches.

Keywords: Alzheimer's disease, Protein-RNA interaction analysis, molecular docking simulations, conformational dynamics, binding stability, binding kinetics, protein synthesis.

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Authors: Syed Masood Hussain

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An effective control method, including system-level control and pulse width modulation for quasi-Z-source cascade multilevel inverter (qZS-CMI) based grid-tie photovoltaic (PV) power system is proposed. The system-level control achieves the grid-tie current injection, independent maximum power point tracking (MPPT) for separate PV panels, and dc-link voltage balance for all quasi-Z-source H-bridge inverter (qZS-HBI) modules. A recent upsurge in the study of photovoltaic (PV) power generation emerges, since they directly convert the solar radiation into electric power without hampering the environment. However, the stochastic fluctuation of solar power is inconsistent with the desired stable power injected to the grid, owing to variations of solar irradiation and temperature. To fully exploit the solar energy, extracting the PV panels’ maximum power and feeding them into grids at unity power factor become the most important. The contributions have been made by the cascade multilevel inverter (CMI). Nevertheless, the H-bridge inverter (HBI) module lacks boost function so that the inverter KVA rating requirement has to be increased twice with a PV voltage range of 1:2; and the different PV panel output voltages result in imbalanced dc-link voltages. However, each HBI module is a two-stage inverter, and many extra dc–dc converters not only increase the complexity of the power circuit and control and the system cost, but also decrease the efficiency. Recently, the Z-source/quasi-Z-source cascade multilevel inverter (ZS/qZS-CMI)-based PV systems were proposed. They possess the advantages of both traditional CMI and Z-source topologies. In order to properly operate the ZS/qZS-CMI, the power injection, independent control of dc-link voltages, and the pulse width modulation (PWM) are necessary. The main contributions of this paper include: 1) a novel multilevel space vector modulation (SVM) technique for the single phase qZS-CMI is proposed, which is implemented without additional resources; 2) a grid-connected control for the qZS-CMI based PV system is proposed, where the all PV panel voltage references from their independent MPPTs are used to control the grid-tie current; the dual-loop dc-link peak voltage control.

Keywords: Quzi-Z source inverter, Photo voltaic power system, space vector modulation, cascade multilevel inverter

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Authors: Christina Peristeri, Tobias Berg, Domenico Caridi, Paul Hutcheson, Robert Winstanley

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In recent years the demand for rapid innovations in the automotive industry has led to the need for accelerated simulation procedures while retaining a detailed representation of the simulated phenomena. The project’s aim is to create a fast transient workflow for external aerodynamic CFD simulations of road vehicles. The geometry used was the SAE Notchback Closed Cooling DrivAer model, and the simulation results were compared with data from wind tunnel tests. The meshes generated for this study were of two types. One was a mix of polyhedral cells near the surface and hexahedral cells away from the surface. The other was an octree hex mesh with a rapid method of fitting to the surface. Three different grid refinement levels were used for each mesh type, with the biggest total cell count for the octree mesh being close to 1 billion. A series of steady-state solutions were obtained on three different grid levels using a pseudo-transient coupled solver and a k-omega-based RANS turbulence model. A mesh-independent solution was found in all cases with a medium level of refinement with 200 million cells. Stress-Blended Eddy Simulation (SBES) was chosen for the transient simulations, which uses a shielding function to explicitly switch between RANS and LES mode. A converged pseudo-transient steady-state solution was used to initialize the transient SBES run that was set up with the SIMPLEC pressure-velocity coupling scheme to reach the fastest solution (on both CPU & GPU solvers). An important part of this project was the use of FLUENT’s Multi-GPU solver. Tesla A100 GPU has been shown to be 8x faster than an Intel 48-core Sky Lake CPU system, leading to significant simulation speed-up compared to the traditional CPU solver. The current study used 4 Tesla A100 GPUs and 192 CPU cores. The combination of rapid octree meshing and GPU computing shows significant promise in reducing time and hardware costs for industrial strength aerodynamic simulations.

Keywords: CFD, DrivAer, LES, Multi-GPU solver, octree mesh, RANS

Procedia PDF Downloads 116

Authors: Mohamed El Kory Yacoub, Ahmed Bezeid El Mamy Beyatt, Djibril Barry, Yanogo Pauline, Nicolas Meda

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Introduction: Rift Valley Fever is a zoonotic arbovirosis that severely affects ruminants, as well as humans. It causes abortions in pregnant females and deaths in young animals. The disease occurs during heavy rains followed by large numbers of mosquito vectors. The objective of this work is to evaluate the surveillance system for Rift Valley Fever. Methods: We conducted an evaluation of the Rift Valley Fiver surveillance system. Data were collected from the analysis of the national database of the Mauritanian Network of Animal Disease Epidemiological Surveillance at the Ministry of Rural Development, of RVF cases notified from the whole national territory, of questionnaires and interviews with all persons involved in RVF surveillance at the central level. The quality of the system was assessed by analyzing the quantitative attributes defined by the Centers for Disease Control and Prevention. Results: In 2019, 443 cases of RVF were notified by the surveillance system, of which 36 were positive. Among the notified cases of Rift Valley Fever, the 0- to the 3-year-old age group of small ruminants was the most represented with 49.21% of cases, followed by 33.33%, which was recorded in large ruminants in the 0 to 7-year-old age group, 11.11% of cases were older than seven years. The completeness of the data varied between 14.2% (age) and 100% (species). Most positive cases were recorded between October and November 2019 in seven different regions. Attribute analysis showed that 87% of the respondents were able to use the case definition well, and 78.8% said they were familiar with the reporting and feedback loop of the Rift Valley Fever data. 90.3% of the respondents found it easy, while 95% of them responded that it was easy for them to transmit their data to the next level. Conclusions: The epidemiological surveillance system for Rift Valley Fever in Mauritania is simple and representative. However, data quality, stability, and responsiveness are average, as the diagnosis of the disease requires laboratory confirmation and the average delay for this confirmation is long (13 days). Consequently, the lack of completeness of the recorded data and of description of cases in terms of time-place-animal, associated with the delay between the stages of the surveillance system can make prevention, early detection of epidemics, and the initiation of measures for an adequate response difficult.

Keywords: evaluation, epidemiological surveillance system, rift valley fever, mauritania, ruminants

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Authors: James Skon, Irina Beshentseva, Michelle Polak

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Wifi solutions come in two major classes. Small Office/Home Office (SOHO) WiFi, characterized by inexpensive WiFi routers, with one or two service set identifiers (SSIDs), and a single shared passphrase. These access points provide no significant user management or monitoring, and no aggregation of monitoring and control for multiple routers. The other solution class is managed enterprise WiFi solutions, which involve expensive Access Points (APs), along with (also costly) local or cloud based management components. These solutions typically provide portal based login, per user virtual local area networks (VLANs), and sophisticated monitoring and control across a large group of APs. The cost for deploying and managing such managed enterprise solutions is typically about 10 fold that of inexpensive consumer APs. Low revenue organizations, such as schools, non-profits, non-government organizations (NGO's), small businesses, and even homes cannot easily afford quality enterprise WiFi solutions, though they may need to provide quality WiFi access to their population. Using available lower cost Wifi solutions can significantly reduce their ability to provide reliable, secure network access. This project explored and created a new approach for providing secured managed enterprise WiFi based on low cost hardware combined with both new and existing (but modified) open source software. The solution provides a cloud based management interface which allows organizations to aggregate the configuration and management of small, medium and large WiFi solutions. It utilizes a novel approach for user management, giving each user a unique passphrase. It provides unlimited SSID's across an unlimited number of WiFI zones, and the ability to place each user (and all their devices) on their own VLAN. With proper configuration it can even provide user local services. It also allows for users' usage and quality of service to be monitored, and for users to be added, enabled, and disabled at will. As inferred above, the ultimate goal is to free organizations with limited resources from the expense of a commercial enterprise WiFi, while providing them with most of the qualities of such a more expensive managed solution at a fraction of the cost.

Keywords: wifi, enterprise, cloud, managed

Procedia PDF Downloads 99

Authors: Vinod Ponnagandla, Brenton McLaury, Siamack Shirazi

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Sand production can lead to deposition of particles or erosion. Low production rates resulting in deposition can partially clog systems and cause under deposit corrosion. Commercially available nonintrusive acoustic sand detectors are attractive as they claim to detect sand production. Acoustic sand detectors are used during oil and gas production; however, operators often do not know the threshold detection limits of these devices. It is imperative to know the detection limits to appropriately plan for cleaning of separation equipment or examine risk of erosion. These monitors are based on detecting the acoustic signature of sand as the particles impact the pipe walls. The objective of this work is to determine threshold detection limits for acoustic sand monitors that are commercially available. The minimum threshold sand concentration that can be detected in a pipe are determined as a function of flowing gas and liquid velocities. A large scale flow loop with a 4-inch test section is utilized. Commercially available sand monitors (ClampOn and Roxar) are evaluated for different flow regimes, sand sizes and pipe orientation (vertical and horizontal). The manufacturers’ recommend that the monitors be placed on a bend to maximize the number of particle impacts, so results are shown for monitors placed at 45 and 90 degree positions in a bend. Acoustic sand monitors that clamp to the outside of pipe are passive and listen for solid particle impact noise. The threshold sand rate is calculated by eliminating the background noise created by the flow of gas and liquid in the pipe for various flow regimes that are generated in horizontal and vertical test sections. The average sand sizes examined are 150 and 300 microns. For stratified and bubbly flows the threshold sand rates are much higher than other flow regimes such as slug and annular flow regimes that are investigated. However, the background noise generated by slug flow regime is very high and cause a high uncertainty in detection limits. The threshold sand rates for annular flow and dry gas conditions are the lowest because of high gas velocities. The effects of monitor placement around elbows that are in vertical and horizontal pipes are also examined for 150 micron. The results show that the threshold sand rates that are detected in vertical orientation are generally lower for all various flow regimes that are investigated.

Keywords: acoustic monitor, sand, multiphase flow, threshold

Procedia PDF Downloads 409

Authors: Yonggyu Lee, Byungkyu Jung, Bom Yoon, Jongil Yoon

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MR-based simulation devices have been recently used in various fields such as entertainment, medicine, manufacturing, and education. Different simulation devices are also being developed for military equipment training. This is to address the concerns regarding safety accidents as well as cost issues associated with training with expensive equipment. An important aspect of developing simulation devices to replicate military training is that trainees experience the same effect as training with real devices. In this study, the criteria for performance evaluation are established to compare the training effect of an MR-based simulation device to that of an actual device. K-9 Self-propelled artillery (SPA) operators are selected as training subjects. First, MR-based software is developed to simulate the training ground and training scenarios currently used for training SPA operators in South Korea. Hardware that replicates the interior of SPA is designed, and a simulation device that is linked to the software is developed. Second, criteria are established to evaluate the simulation device based on real-life training scenarios. A total of nine performance evaluation criteria were selected based on the actual SPA operation training scenarios. Evaluation items were selected to evaluate whether the simulation device was designed such that trainees would experience the same effect as training in the field with a real SPA. To eval-uate the level of replication by the simulation device of the actual training environments (driving and passing through trenches, pools, protrusions, vertical obstacles, and slopes) and driving conditions (rapid steering, rapid accelerating, and rapid braking) as per the training scenarios, tests were performed under the actual training conditions and in the simulation device, followed by the comparison of the results. In addition, the level of noise felt by operators during training was also selected as an evaluation criterion. Due to the nature of the simulation device, there may be data latency between HW and SW. If the la-tency in data transmission is significant, the VR image information delivered to trainees as they maneuver HW might not be consistent. This latency in data transmission was also selected as an evaluation criterion to improve the effectiveness of the training. Through this study, the key evaluation metrics were selected to achieve the same training effect as training with real equipment in a training ground during the develop-ment of the simulation device for military equipment training.

Keywords: K-9 self-propelled artillery, mixed reality, simulation device, synchronization

Procedia PDF Downloads 67

Authors: Chih-Chung Huang, Po-Hsun Peng

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Ultrasound transient elastography has become a valuable tool for many clinical diagnoses, such as liver diseases and breast cancer. The pathological tissue can be distinguished by elastography due to its stiffness is different from surrounding normal tissues. An ultrafast frame rate of ultrasound imaging is needed for transient elastography modality. The elastography obtained in the ultrafast system suffers from a low quality for resolution, and affects the robustness of the transient elastography. In order to overcome these problems, a coherent plane wave compounding technique has been proposed for conventional ultrasound system which the operating frequency is around 3-15 MHz. The purpose of this study is to develop a novel beamforming technique for high frequency ultrasound coherent plane-wave compounding imaging and the simulated results will provide the standards for hardware developments. Plane-wave compounding imaging produces a series of low-resolution images, which fires whole elements of an array transducer in one shot with different inclination angles and receives the echoes by conventional beamforming, and compounds them coherently. Simulations of plane-wave compounding image and focused transmit image were performed using Field II. All images were produced by point spread functions (PSFs) and cyst phantoms with a 64-element linear array working at 35MHz center frequency, 55% bandwidth, and pitch of 0.05 mm. The F number is 1.55 in all the simulations. The simulated results of PSFs and cyst phantom which were obtained using single, 17, 43 angles plane wave transmission (angle of each plane wave is separated by 0.75 degree), and focused transmission. The resolution and contrast of image were improved with the number of angles of firing plane wave. The lateral resolutions for different methods were measured by -10 dB lateral beam width. Comparison of the plane-wave compounding image and focused transmit image, both images exhibited the same lateral resolution of 70 um as 37 angles were performed. The lateral resolution can reach 55 um as the plane-wave was compounded 47 angles. All the results show the potential of using high-frequency plane-wave compound imaging for realizing the elastic properties of the microstructure tissue, such as eye, skin and vessel walls in the future.

Keywords: plane wave imaging, high frequency ultrasound, elastography, beamforming

Procedia PDF Downloads 541

Authors: Pei-Ru Yang, Yu-Chen Lin, Jia-Min Wu

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Background: A 58-year-old man with a history of osteoporosis and diabetes presented with chronic pain in his left knee due to severe knee joint degeneration. The knee replacement surgery was recommended by the doctor. But the patient suffered from low pain tolerance and wondered if virtual reality could relieve acute postoperative wound pain. Methods: We used the PICO (patient, intervention, comparison, and outcome) approach to generate indexed keywords and searched systematic review articles from 2017 to 2021 on the Cochran Library, PubMed, and Clinical Key databases. Results: The initial literature results included 38 articles, including 12 Cochrane library articles and 26 PubMed articles. One article was selected for further analysis after removing duplicates and off-topic articles. The eight trials included in this article were published between 2013 and 2019 and recruited a total of 723 participants. The studies, conducted in India, Lebanon, Iran, South Korea, Spain, and China, included adults who underwent hemorrhoidectomy, dental surgery, craniotomy or spine surgery, episiotomy repair, and knee surgery, with a mean age (24.1 ± 4.1 to 73.3 ± 6.5). Virtual reality is an emerging non-drug postoperative analgesia method. The findings showed that pain control was reduced by a mean of 1.48 points (95% CI: -2.02 to -0.95, p-value < 0.0001) in minor surgery and 0.32 points in major surgery (95% CI: -0.53 to -0.11, p-value < 0.03), and the overall postoperative satisfaction has improved. Discussion: Postoperative pain is a common clinical problem in surgical patients. Research has confirmed that virtual reality can create an immersive interactive environment, communicate with patients, and effectively relieve postoperative pain. However, virtual reality requires the purchase of hardware and software and other related computer equipment, and its high cost is a disadvantage. We selected the best literature based on clinical questions to answer the patient's question and used share decision making (SDM) to help the patient make decisions based on the clinical situation after knee replacement surgery to improve the quality of patient-centered care.

Keywords: knee replacement surgery, postoperative pain, share decision making, virtual reality

Procedia PDF Downloads 69

Authors: Ju Peng Poh, Jun Yu Charles Lee, Jonathan Chew Hoe Khoo

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The emergence of digital twin technology, a digital replica of physical world, has improved the real-time access to data from sensors about the performance of buildings. This digital transformation has opened up many opportunities to improve the management of the building by using the data collected to help monitor consumption patterns and energy leakages. One example is the integration of predictive models for anomaly detection. In this paper, we use the GAM (Generalised Additive Model) for the anomaly detection of Air Handling Units (AHU) power consumption pattern. There is ample research work on the use of GAM for the prediction of power consumption at the office building and nation-wide level. However, there is limited illustration of its anomaly detection capabilities, prescriptive analytics case study, and its integration with the latest development of digital twin technology. In this paper, we applied the general GAM modelling framework on the historical data of the AHU power consumption and cooling load of the building between Jan 2018 to Aug 2019 from an education campus in Singapore to train prediction models that, in turn, yield predicted values and ranges. The historical data are seamlessly extracted from the digital twin for modelling purposes. We enhanced the utility of the GAM model by using it to power a real-time anomaly detection system based on the forward predicted ranges. The magnitude of deviation from the upper and lower bounds of the uncertainty intervals is used to inform and identify anomalous data points, all based on historical data, without explicit intervention from domain experts. Notwithstanding, the domain expert fits in through an optional feedback loop through which iterative data cleansing is performed. After an anomalously high or low level of power consumption detected, a set of rule-based conditions are evaluated in real-time to help determine the next course of action for the facilities manager. The performance of GAM is then compared with other approaches to evaluate its effectiveness. Lastly, we discuss the successfully deployment of this approach for the detection of anomalous power consumption pattern and illustrated with real-world use cases.

Keywords: anomaly detection, digital twin, generalised additive model, GAM, power consumption, supervised learning

Procedia PDF Downloads 156

Authors: Zongmin Ma, Shaowen Zhang, Yueping Fu, Jun Tang, Yunbo Shi, Jun Liu

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Solid-state quantum sensors are attracting wide interest because of their high sensitivity at room temperature. In particular, spin properties of nitrogen–vacancy (NV) color centres in diamond make them outstanding sensors of magnetic fields, electric fields and temperature under ambient conditions. Much of the work on NV magnetic sensing has been done so as to achieve the smallest volume, high sensitivity of NV ensemble-based magnetometry using micro-cavity, light-trapping diamond waveguide (LTDW), nano-cantilevers combined with MEMS (Micro-Electronic-Mechanical System) techniques. Recently, frequency-modulated microwaves with continuous optical excitation method have been proposed to achieve high sensitivity of 6 μT/√Hz using individual NV centres at nanoscale. In this research, we built-up an experiment to measure static magnetic field through continuous wave optical excitation with frequency-modulated microwaves method under continuous illumination with green pump light at 532 nm, and bulk diamond sample with a high density of NV centers (1 ppm). The output of the confocal microscopy was collected by an objective (NA = 0.7) and detected by a high sensitivity photodetector. We design uniform and efficient excitation of the micro strip antenna, which is coupled well with the spin ensembles at 2.87 GHz for zero-field splitting of the NV centers. Output of the PD signal was sent to an LIA (Lock-In Amplifier) modulated signal, generated by the microwave source by IQ mixer. The detected signal is received by the photodetector, and the reference signal enters the lock-in amplifier to realize the open-loop detection of the NV atomic magnetometer. We can plot ODMR spectra under continuous-wave (CW) microwave. Due to the high sensitivity of the lock-in amplifier, the minimum detectable value of the voltage can be measured, and the minimum detectable frequency can be made by the minimum and slope of the voltage. The magnetic field sensitivity can be derived from η = δB√T corresponds to a 10 nT minimum detectable shift in the magnetic field. Further, frequency analysis of the noise in the system indicates that at 10Hz the sensitivity less than 10 nT/√Hz.

Keywords: nitrogen-vacancy (NV) centers, frequency-modulated microwaves, magnetic field sensitivity, noise density

Procedia PDF Downloads 440

Authors: Kari Bjorn

Abstract:

Team learning has been studied and modeled as double loop model and its variations. Also, metacognition has been suggested as a concept to describe the nature of team learning to be more than a simple sum of individual learning of the team members. Team learning has a positive correlation with both individual motivation of its members, as well as the collective factors within the team. Team learning of previously very independent members of two teaching teams is analyzed. Applied Science Universities are training future professionals with ever more diversified and multidisciplinary skills. The size of the units of teaching and learning are increasingly larger for several reasons. First, multi-disciplinary skill development requires more active learning and richer learning environments and learning experiences. This occurs on students teams. Secondly, teaching of multidisciplinary skills requires a multidisciplinary and team-based teaching from the teachers as well. Team formation phases have been identifies and widely accepted. Team role stress has been analyzed in project teams. Projects typically have a well-defined goal and organization. This paper explores team stress of two teacher teams in a parallel running two course units in engineering education. The first is an Industrial Automation Technology and the second is Development of Medical Devices. The courses have a separate student group, and they are in different campuses. Both are run in parallel within 8 week time. Both of them are taught by a group of four teachers with several years of teaching experience, but individually. The team role stress scale items - the survey is done to both teaching groups at the beginning of the course and at the end of the course. The inventory of questions covers the factors of ambiguity, conflict, quantitative role overload and qualitative role overload. Some comparison to the study on project teams can be drawn. Team development stage of the two teaching groups is different. Relating the team role stress factors to the development stage of the group can reveal the potential of management actions to promote team building and to understand the maturity of functional and well-established teams. Mature teams indicate higher job satisfaction and deliver higher performance. Especially, teaching teams who deliver highly intangible results of learning outcome are sensitive to issues in the job satisfaction and team conflicts. Because team teaching is increasing, the paper provides a review of the relevant theories and initial comparative and longitudinal results of the team role stress factors applied to teaching teams.

Keywords: engineering education, stress, team role, team teaching

Procedia PDF Downloads 225

Authors: Ammar Y. Alqahtani

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In order to minimize the negative impact on the environment, it is essential to manage the waste that generated from the premature disposal of end-of-life (EOL) products properly. Consequently, government and international organizations introduced new policies and regulations to minimize the amount of waste being sent to landfills. Moreover, the consumers’ awareness regards environment has forced original equipment manufacturers to consider being more environmentally conscious. Therefore, manufacturers have thought of different ways to deal with waste generated from EOL products viz., remanufacturing, reusing, recycling, or disposing of EOL products. The rate of depletion of virgin natural resources and their dependency on the natural resources can be reduced by manufacturers when EOL products are treated as remanufactured, reused, or recycled, as well as this will cut on the amount of harmful waste sent to landfills. However, disposal of EOL products contributes to the problem and therefore is used as a last option. Number of EOL need to be estimated in order to fulfill the components demand. Then, disassembly process needs to be performed to extract individual components and subassemblies. Smart products, built with sensors embedded and network connectivity to enable the collection and exchange of data, utilize sensors that are implanted into products during production. These sensors are used for remanufacturers to predict an optimal warranty policy and time period that should be offered to customers who purchase remanufactured components and products. Sensor-provided data can help to evaluate the overall condition of a product, as well as the remaining lives of product components, prior to perform a disassembly process. In this paper, a multi-period disassembly-to-order (DTO) model is developed that takes into consideration the different system uncertainties. The DTO model is solved using Nonlinear Programming (NLP) in multiple periods. A DTO system is considered where a variety of EOL products are purchased for disassembly. The model’s main objective is to determine the best combination of EOL products to be purchased from every supplier in each period which maximized the total profit of the system while satisfying the demand. This paper also addressed the impact of sensor embedded products on the cost of warranties. Lastly, this paper presented and analyzed a case study involving various simulation conditions to illustrate the applicability of the model.

Keywords: closed-loop supply chains, environmentally conscious manufacturing, product recovery, reverse logistics

Procedia PDF Downloads 138

Authors: Jayati Bhattacharjee

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Teaching is a very dynamic profession. Teaching Science is as much challenging as Learning the subject if not more. For instance teaching of Chemistry. From the introductory concepts of subatomic particles to atoms of elements and their symbols and further presenting the chemical equation and so forth is a challenge on both side of the equation Teaching Learning. This paper combines the Neuroscience of Learning and memory with the knowledge of Learning style (VAK) and presents an effective tool for the teacher to authenticate Learning. The model of ‘Working Memory’, the Visio-spatial sketchpad, the central executive and the phonological loop that transforms short-term memory to long term memory actually supports the psychological theory of Learning style i.e. Visual –Auditory-Kinesthetic. A closer examination of David Kolbe’s learning model suggests that learning requires abilities that are polar opposites, and that the learner must continually choose which set of learning abilities he or she will use in a specific learning situation. In grasping experience some of us perceive new information through experiencing the concrete, tangible, felt qualities of the world, relying on our senses and immersing ourselves in concrete reality. Others tend to perceive, grasp, or take hold of new information through symbolic representation or abstract conceptualization – thinking about, analyzing, or systematically planning, rather than using sensation as a guide. Similarly, in transforming or processing experience some of us tend to carefully watch others who are involved in the experience and reflect on what happens, while others choose to jump right in and start doing things. The watchers favor reflective observation, while the doers favor active experimentation. Any lesson plan based on the model of Prescriptive design: C+O=M (C: Instructional condition; O: Instructional Outcome; M: Instructional method). The desired outcome and conditions are independent variables whereas the instructional method is dependent hence can be planned and suited to maximize the learning outcome. The assessment for learning rather than of learning can encourage, build confidence and hope amongst the learners and go a long way to replace the anxiety and hopelessness that a student experiences while learning Science with a human touch in it. Application of this model has been tried in teaching chemistry to high school students as well as in workshops with teachers. The response received has proven the desirable results.

Keywords: working memory model, learning style, prescriptive design, assessment for learning

Procedia PDF Downloads 352

Authors: Mario Sandro F. Rocha, Carlos S. Ande, Anderson A. Oliveira, Felipe M. Bersotti, Lucas O. Venzel

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The inertial motion capture systems (mocap) are among the most suitable tools for quantitative clinical analysis in rehabilitation and sports medicine. The inertial measuring units (IMUs), composed by accelerometers, gyroscopes, and magnetometers, are able to measure spatial orientations and calculate displacements with sufficient precision for applications in biomechanical analysis of movement. Furthermore, this type of system is relatively affordable and has the advantages of portability and independence from external references. In this work, we present the last version of our inertial motion capture system, based on the foregoing technology, with a unity interface designed for rehabilitation and sports. In our hardware architecture, only one serial port is required. First, the board client must be connected to the computer by a USB cable. Next, an available serial port is configured and opened to establish the communication between the client and the application, and then the client starts scanning for the active MOCAP_S servers around. The servers play the role of the inertial measuring units that capture the movements of the body and send the data to the client, which in turn create a package composed by the ID of the server, the current timestamp, and the motion capture data defined in the client pre-configuration of the capture session. In the current version, we can measure the game rotation vector (grv) and linear acceleration (lacc), and we also have a step detector that can be abled or disabled. The grv data are processed and directly linked to the bones of the 3D model, and, along with the data of lacc and step detector, they are also used to perform the calculations of displacements and other variables shown on the graphical user interface. Our user interface was designed to calculate and present variables that are important for rehabilitation and sports, such as cadence, speed, total gait cycle, gait cycle length, obliquity and rotation, and center of gravity displacement. Our goal is to present a low-cost portable and wearable system with a friendly interface for application in biomechanics and sports, which also performs as a product of high precision and low consumption of energy.

Keywords: biomechanics, inertial sensors, motion capture, rehabilitation

Procedia PDF Downloads 141

Authors: Bao Li, Aike Qiao, Gaoyang Li, Youjun Liu

Abstract:

Background: Lumped parameter model (LPM) is a common numerical model for hemodynamic calculation. LPM uses circuit elements to simulate the human blood circulatory system. Physiological indicators and characteristics can be acquired through the model. However, due to the different physiological indicators of each individual, parameters in LPM should be personalized in order for convincing calculated results, which can reflect the individual physiological information. This study aimed to develop an automatic and effective optimization method to personalize the parameters in LPM of the blood circulatory system, which is of great significance to the numerical simulation of individual hemodynamics. Methods: A closed-loop LPM of the human blood circulatory system that is applicable for most persons were established based on the anatomical structures and physiological parameters. The patient-specific physiological data of 5 volunteers were non-invasively collected as personalized objectives of individual LPM. In this study, the blood pressure and flow rate of heart, brain, and limbs were the main concerns. The collected systolic blood pressure, diastolic blood pressure, cardiac output, and heart rate were set as objective data, and the waveforms of carotid artery flow and ankle pressure were set as objective waveforms. Aiming at the collected data and waveforms, sensitivity analysis of each parameter in LPM was conducted to determine the sensitive parameters that have an obvious influence on the objectives. Simulated annealing was adopted to iteratively optimize the sensitive parameters, and the objective function during optimization was the root mean square error between the collected waveforms and data and simulated waveforms and data. Each parameter in LPM was optimized 500 times. Results: In this study, the sensitive parameters in LPM were optimized according to the collected data of 5 individuals. Results show a slight error between collected and simulated data. The average relative root mean square error of all optimization objectives of 5 samples were 2.21%, 3.59%, 4.75%, 4.24%, and 3.56%, respectively. Conclusions: Slight error demonstrated good effects of optimization. The individual modeling algorithm developed in this study can effectively achieve the individualization of LPM for the blood circulatory system. LPM with individual parameters can output the individual physiological indicators after optimization, which are applicable for the numerical simulation of patient-specific hemodynamics.

Keywords: blood circulatory system, individual physiological indicators, lumped parameter model, optimization algorithm

Procedia PDF Downloads 138