Search results for: adaptive controller

Authors: Ankur Dixit, Hiroaki Wagatsuma

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The crack detection on a concrete bridge is an important and constant task in civil engineering. Chronically, humans are checking the bridge for inspection of cracks to maintain the quality and reliability of bridge. But this process is very long and costly. To overcome such limitations, we have used a drone with a digital camera, which took some images of bridge deck and these images are processed by morphological component analysis (MCA). MCA technique is a very strong application of sparse coding and it explores the possibility of separation of images. In this paper, MCA has been used to decompose the image into coarse and fine components with the effectiveness of two dictionaries namely anisotropic diffusion and wavelet transform. An anisotropic diffusion is an adaptive smoothing process used to adjust diffusion coefficient by finding gray level and gradient as features. These cracks in image are enhanced by subtracting the diffused coarse image into the original image and the results are treated by Sobel edge detector and binary filtering to exhibit the cracks in a fine way. Our results demonstrated that proposed MCA framework using anisotropic diffusion followed by Sobel operator and binary filtering may contribute to an automation of crack detection even in open field sever conditions such as bridge decks.

Keywords: anisotropic diffusion, coarse component, fine component, MCA, Sobel edge detector and wavelet transform

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Authors: C. Bala Prashanth Reddy, B. Abhinay, C. Sreekar, D. V. Shobhana Priscilla

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The project aims in designing an emergency pacemaker which is capable of giving shocks to a human heart which has stopped working suddenly. A pacemaker is a machine commonly used by cardiologists. This machine is used in order to shock a human’s heart back into usage. The way the heart works is that there are small cells called pacemakers sending electrical pulses to cardiac muscles that tell the heart when to pump blood. When these electrical pulses stop, the heart stops beating. When this happens, a pacemaker is used to shock the heart muscles and the pacemakers back into action. The way this is achieved is by rubbing the two panels of the pacemaker together to create an adequate electrical current, and then the heart gets back to the normal state. The project aims in designing a system which is capable of continuously displaying the heart beat and blood pressure of a person on LCD. The concerned doctor gets the heart beat and also the blood pressure details continuously through the GSM Modem in the form of SMS alerts. In case of abnormal condition, the doctor sends message format regarding the amount of electric shock needed. Automatically the microcontroller gives the input to the pacemaker which in turn gives the shock to the patient. Heart beat monitor and display system is a portable and a best replacement for the old model stethoscope which is less efficient. The heart beat rate is calculated manually using stethoscope where the probability of error is high because the heart beat rate lies in the range of 70 to 90 per minute whose occurrence is less than 1 sec, so this device can be considered as a very good alternative instead of a stethoscope.

Keywords: missing R wave, PWM, demand pacemaker, heart

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Authors: Stella O. Olubodun, George E. Eriyamremu

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The study examined the effect of Bonny Light whole crude oil (WC) and its water soluble fraction (WSF) on the activities of antioxidant enzymes (catalase (CAT) and superoxide dismutase (SOD)) and crude mitochondria ATPases in the radicle of germinating bean (Vigna unguiculata). The percentage germination, level of lipid peroxidation, antioxidant enzyme, and mitochondria Ca2+ and Mg2+ ATPase activities were measured in the radicle of bean after 7, 14, and 21 days post germination. Viable bean seeds were planted in soils contaminated with 10ml, 25ml, and 50ml of whole crude oil (WC) and its water soluble fraction (WSF) to obtain 2, 5, and 10% v/w crude oil contamination. There was dose dependent reduction of the number of bean seeds that germinated in the contaminated soils compared with control (p<0.001). The activities of the antioxidant enzymes, as well as, adenosine triphosphatase enzymes, were also significantly (p<0.001) altered in the radicle of the plants grown in contaminated soil compared with the control. Generally, the level of lipid peroxidation was highest after 21 days post germination when compared with control. Stress to germinating bean caused by Bonny Light crude oil or its water soluble fraction resulted in adaptive changes in crude mitochondria ATPases in the radicle.

Keywords: antioxidant enzymes, bonny light crude oil, radicle, mitochondria ATPases

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Authors: Zahra Hassani

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Background and Purpose: Poststroke depression (PSD) is one of the complications of a stroke that reduces the patient's chance of recovery, becomes irritable, and changes personality. Cognitive rehabilitation is one of the non-pharmacological methods that improve deficits such as attention, memory, and symptoms of depression. Therefore, the purpose of the present study is to evaluate the Efficacy of Cognitive Rehabilitation Therapy on Poststroke Depression among Survivors of stroke. Method: In this study, a systematic review of the databases Google Scholar, PubMed, Science Direct, Elsevier between the years 2015 and 2019 with the keywords cognitive rehabilitation therapy, post-stroke, depression Search is done. In this process, studies that examined the Efficacy of Cognitive Rehabilitation Therapy on Poststroke Depression among Survivors of stroke were included in the study. Results: Inclusion criteria were full-text availability, interventional study, and non-review articles. There was a significant difference between the articles in terms of the indices studied, sample number, method of implementation, and so on. A review of studies have shown that cognitive rehabilitation therapy has a significant role in reducing the symptoms of post-stroke depression. The use of these interventions is also effective in improving problem-solving skills, improving memory, and improving attention and concentration. Conclusion: This study emphasizes on the development of efficient and flexible adaptive skills through cognitive processes and its effect on reducing depression in patients after stroke.

Keywords: cognitive therapy, depression, stroke, rehabilitation

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Authors: Tan Zhang, Zhongjian Wang, Jack Xin, Zhiwen Zhang

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We aim to efficiently compute the spreading speeds of reaction-diffusion-advection (RDA) fronts in divergence-free random flows under the Kolmogorov-Petrovsky-Piskunov (KPP) nonlinearity. We study a stochastic interacting particle method (IPM) for the reduced principal eigenvalue (Lyapunov exponent) problem of an associated linear advection-diffusion operator with spatially random coefficients. The Fourier representation of the random advection field and the Feynman-Kac (FK) formula of the principal eigenvalue (Lyapunov exponent) form the foundation of our method implemented as a genetic evolution algorithm. The particles undergo advection-diffusion and mutation/selection through a fitness function originated in the FK semigroup. We analyze the convergence of the algorithm based on operator splitting and present numerical results on representative flows such as 2D cellular flow and 3D Arnold-Beltrami-Childress (ABC) flow under random perturbations. The 2D examples serve as a consistency check with semi-Lagrangian computation. The 3D results demonstrate that IPM, being mesh-free and self-adaptive, is simple to implement and efficient for computing front spreading speeds in the advection-dominated regime for high-dimensional random flows on unbounded domains where no truncation is needed.

Keywords: KPP front speeds, random flows, Feynman-Kac semigroups, interacting particle method, convergence analysis

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Authors: Nafiseh Ebrahimi, Amir Jafari

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The study of humanoid character is of great interest to researchers in the field of robotics and biomechanics. One might want to know the forces and torques required to move a limb from an initial position to the desired destination position. Inverse dynamics is a helpful method to compute the force and torques for an articulated body limb. It enables us to know the joint torques required to rotate a link between two positions. Our goal in this study was to control a human-like articulated manipulator for a specific task of path tracking. For this purpose, the human arm was modeled with a three-link planar manipulator activated by Hill muscle model. Applying a proportional controller, values of force and torques applied to the joints were calculated by inverse dynamics, and then joints and muscle forces trajectories were computed and presented. To be more accurate to say, the kinematics of the muscle-joint space was formulated by which we defined the relationship between the muscle lengths and the geometry of the links and joints. Secondary, the kinematic of the links was introduced to calculate the position of the end-effector in terms of geometry. Then, we considered the modeling of Hill muscle dynamics, and after calculation of joint torques, finally, we applied them to the dynamics of the three-link manipulator obtained from the inverse dynamics to calculate the joint states, find and control the location of manipulator’s end-effector. The results show that the human arm model was successfully controlled to take the designated path of an ellipse precisely.

Keywords: arm manipulator, hill muscle model, six-muscle model, three-link lodel

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Authors: Bohuslava Juhasova, Martin Juhas, Renata Masarova, Zuzana Sutova

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The article deals with the tool in Matlab GUI form that is designed to analyse a mechatronic system sensitivity and tolerance. In the analysed mechatronic system, a torque is transferred from the drive to the load through a coupling containing flexible elements. Different methods of control system design are used. The classic form of the feedback control is proposed using Naslin method, modulus optimum criterion and inverse dynamics method. The cascade form of the control is proposed based on combination of modulus optimum criterion and symmetric optimum criterion. The sensitivity is analysed on the basis of absolute and relative sensitivity of system function to the change of chosen parameter value of the mechatronic system, as well as the control subsystem. The tolerance is analysed in the form of determining the range of allowed relative changes of selected system parameters in the field of system stability. The tool allows to analyse an influence of torsion stiffness, torsion damping, inertia moments of the motor and the load and controller(s) parameters. The sensitivity and tolerance are monitored in terms of the impact of parameter change on the response in the form of system step response and system frequency-response logarithmic characteristics. The Symbolic Math Toolbox for expression of the final shape of analysed system functions was used. The sensitivity and tolerance are graphically represented as 2D graph of sensitivity or tolerance of the system function and 3D/2D static/interactive graph of step/frequency response.

Keywords: mechatronic systems, Matlab GUI, sensitivity, tolerance

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Authors: Kriti Upadhyay, Ashraf Ali, Puja Sohal, Randeep Guleria

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Background: In Chronic Obstructive Pulmonary diseases (COPD) pathogenesis oxidative stress plays an important role. Hypoxia-Inducible factor (HIF-1α) is a dimeric protein complex which Functions as a master transcriptional regulator of the adaptive response to hypoxiaand is a risk factor that increases when oxidative stress triggers. The role ofHIF-1αin COPD due to smoking is lacking. Aim: This study aims to evaluate the role of HIF-1α in smoker COPD patients comparing its association with diseases severity. Method: In this cross-sectional study, we recruited 87 subjects, 57 were smokers with COPD,15 were smokers without COPD and other 15 were non-smoker healthy controls. The mean age was 54.6± 9.32 (cases 57.08±8.15; controls 50.0± 9.8). There were 62%smokers, 25% non-smokers,7% tobacco chewers and 6% ex-smokers. Enzyme-linked immune sorbent assay (ELISA) method was used for analyzing serum samples wherein HIF-1α was analyzed by Sandwich-ELISA. Results: In smoker COPD patients, a significantly higher HIF-1α level showed positive association with hypoxia, smoking status and severity of disease (p=0.03). The mean value of HIF-1α was not significantly different in smokers without COPD and healthy controls. Conclusion: It is found that HIF-1α level was increased in smoker COPD, but not in smokers without COPD. This suggests that development of COPD drive the HIF-1α pathway and it correlates with the severity of diseases.

Keywords: COPD, chronic obstructive pulmonary diseases, smokers, nonsmokers, hypoxia

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Authors: Jongbae Lee, Seongsoo Lee

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Modern sensors often embed small-size digital controller for sensor control, value calibration, and signal processing. These sensors require digital data communication with host microprocessors, but conventional digital communication protocols are too heavy for price reduction. SAE J2716 SENT (single edge nibble transmission) protocol transmits direct digital waveforms instead of complicated analog modulated signals. In this paper, a SENT interface is designed in Verilog HDL (hardware description language) and implemented in FPGA (field-programmable gate array) evaluation board. The designed SENT interface consists of frame encoder/decoder, configuration register, tick period generator, CRC (cyclic redundancy code) generator/checker, and TX/RX (transmission/reception) buffer. Frame encoder/decoder is implemented as a finite state machine, and it controls whole SENT interface. Configuration register contains various parameters such as operation mode, tick length, CRC option, pause pulse option, and number of nibble data. Tick period generator generates tick signals from input clock. CRC generator/checker generates or checks CRC in the SENT data frame. TX/RX buffer stores transmission/received data. The designed SENT interface can send or receives digital data in 25~65 kbps at 3 us tick. Synthesized in 0.18 um fabrication technologies, it is implemented about 2,500 gates.

Keywords: digital sensor interface, SAE J2716, SENT, verilog HDL

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Authors: H. Sakamoto, J. Tochimoto, S. Kurosawa, M. Suzuki, S. Oguri

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Salt stress adversely affects plant growth at various stages of development including seed germination, seedling establishment, vegetative growth and finally reproduction. Because of their immobile nature, plants have evolved mechanisms to sense and respond to salt stress. Seed dormancy is an adaptive trait that enables seed germination to coincide with favorable environmental conditions. We identified a novel locus of Arabidopsis, designated SHG1 (salt hypersensitive germination 1), whose disruption leads to reduced germination rate under moderate salt stress conditions. SHG1 encodes a transmembrane protein with an ankyrin repeat motif that has been implicated in diverse cellular processes such as signal transduction. The SGH1-disrupted Arabidopsis mutant died at the cotyledon stage when sown on salt-containing medium, although wild type plants could form true leaves under the same conditions. On the other hand, this mutant showed similar phenotypes to wild type plants when sown on medium without salt and transferred to salt-containing medium at the vegetative stage. These results suggested that SHG1 played indispensable role in the seed germination and seedling establishment under moderate salt stress conditions. SHG1 may be involved in the release of seed dormancy.

Keywords: germination, ankyrin repeat, arabidopsis, salt tolerance

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Authors: Olatunbosun Samuel Adekogbe

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This paper addresses the question of musical signification, revolving around nature and its natural divides; the paper tends to examine the roles of the dispositional apparatus of listeners to react to sounding environments through music as coordinated sound that focuses on the powerful strain between vibrational occurrences of sound and potentials of being structured. This paper sets out to examine music as a simple conventional design that does not allude to something beyond music and sound as a vehicle to communicate through production, perception, translation, and reaction with regard to melodic and semiotic functions of sounds. This paper adopts the application of questionnaire and evolutionary approach methods to probe musical adaptation, reproduction, and natural selection as the basis for explaining specific human behavioural responses to musical sense-making beyond the above-sketched dichotomies, with a major focus on the transition from acoustic-emotional sensibilities to musical meaning in the selected soundscapes. It was observed that music has emancipated itself from the level of mere acoustic processing of sounds to a functional description in terms of allowing music users to share experiences and interact with the soundscaping environment. The paper, therefore, concludes that the audience as music participants and listeners in the selected soundscapes have been conceived as adaptive devices in the paradigm shift, which can build up new semiotic linkages with the sounding environments in southwestern Nigeria.

Keywords: semiotics, sound, music, soundscape, environment

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Authors: Michael Adedotun Oke

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This paper, therefore, under study the various multiplier usages of the different Animal Dungs, from the animals such as Rabbits, Cows, Fishes, Sheep, and Poultry manure in the areas council of the Federal Capital Territory Abuja, Nigeria. Thus the various observations, with the pictorial representation, that was taken with the field survey from the different farms in Gwagawalada. Shows that the rabbits dungs are being used in some of the vegetables and crop farms, which serves as the nutrients, reduces the cost of production, ensure profitability, which also increases the different vegetative growth, early maturity, and the development of the crop and this is also applicable to some crops like maize, sweet potatoes. While the manure of the poultry products are being incorporated to fish ponds and the cows dungs are being used to serve as some manure to some certain crops, e.g. Okro, Maize, Pepper. Which provides the necessary nutritious values, but the various number of quantity of different bags of the various application are lacking, and the time of usage, it is also a life germane questions, which there are needs for further adaptive research, that will be involved and the reintroduction of new technology, that will be used in terms of the different methodology such as broadcasting and ring applications, of the dungs at large, while the seasons of the various applications. Thus the paper, therefore, suggested a training programs and production of manuals that will guide the various applications and usage and the effective dissemination of the various used of the simple technology, that will advances and teaching of a new mode of and the time of applications and the various quantity to used, during the applications.

Keywords: animals, usage, livestock, dungs, feaces, gwagawalada

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Authors: Shital Suresh Borse, Vijayalaxmi Kadroli

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E-commerce industries nowadays implement the latest AI, ML Techniques to improve their own performance and prediction accuracy. This helps to gain a huge profit from the online market. Ant Colony Optimization, Genetic algorithm, Particle Swarm Optimization, Neural Network & GWO help many e-commerce industries for up-gradation of their predictive performance. These algorithms are providing optimum results in various applications, such as stock price prediction, prediction of drug-target interaction & user ratings of similar products in e-commerce sites, etc. In this study, customer reviews will play an important role in prediction analysis. People showing much interest in buying a lot of services& products suggested by other customers. This ultimately increases net profit. In this work, a convolution neural network (CNN) is proposed which further is useful to optimize the prediction accuracy of an e-commerce website. This method shows that CNN is used to optimize hyperparameters of GWO algorithm using an appropriate coding scheme. Accurate model results are verified by comparing them to PSO results whose hyperparameters have been optimized by CNN in Amazon's customer review dataset. Here, experimental outcome proves that this proposed system using the GWO algorithm achieves superior execution in terms of accuracy, precision, recovery, etc. in prediction analysis compared to the existing systems.

Keywords: prediction analysis, e-commerce, machine learning, grey wolf optimization, particle swarm optimization, CNN

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Authors: Shackira Am, Jos T. Puthur

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The phytostabilization potential of a halophyte Acanthus ilicifolius L. has been evaluated with special attention to the nutritional as well as anatomical adaptations developed by the plant. Distribution of essential elements influenced by the excess Zn²⁺ ions in the root tissue was studied by FEG-SEM EDX microanalysis. Significant variations were observed in the uptake and allocation of mineral elements like Mg, P, K, S, Na, Si and Al in the root of A. ilicifolius. The increase in S is in correlation with the increased synthesis of glutathione which might be involved in the biosynthesis of phytochelatins. This in turn might be aiding the plant to tolerate the adverse environmental conditions by stabilizing the excess Zn in the root tissue itself. Moreover it is revealed that most of the Zn were accumulated towards the central region near the vascular tissue. Treatment with ZnSO₄ in A. ilicifolius caused significant increase in the number of glandular trichomes on the adaxial leaf surface as compared to the leaves of control plants. In addition to this, A. ilicifolius when treated with ZnSO₄, exhibited a deeply stained layer of cells immediate to the endodermis, forming more or less a ring like structure around the xylem vessels. Phloem cells in these plants were crushed/reduced in numbers. There were no such deeply stained cells forming a ring around the xylem vessels in the control plants. These adaptive responses make the plant a suitable candidate for the phytostabilization of Zn. In addition the nutritional adjustment of the plant equips them for a better survival under increased concentration of Zn²⁺.

Keywords: Acanthus ilicifolius, mineral elements, phytostabilization, zinc

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Authors: Kun-Ping Cheng, Dong-Shang Chang, Rou-Wen Wang

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Pre-treatment of automobile paint-shop procedures are the preparation of warm water rinsing tank, hot water rinsing tank, degreasing tank, phosphate tank. The conventional boiler steam fuel is natural gas, producing steam to supply the heat exchange of each tank sink. In this study, the high-frequency soldering economizer is developed for recovering waste heat in the automotive paint-shop (RTO, Regenerative Thermal Oxidation). The heat recovery rate of the new economizer is 20% to 30% higher than the conventional embedded heat pipe. The adaptive control system responded to both RTO furnace exhaust gas and heat demands. In order to maintain the temperature range of the tanks, pre-treatment tanks are directly heated by waste heat recovery device (gas-to-water heat exchanger) through the hot water cycle of heat transfer. The performance of developed waste heat recovery system shows the annual recovery achieved to 1,226,411,483 Kcal of heat (137.8 thousand cubic meters of natural gas). Boiler can reduce fuel consumption by 20 to 30 percent compared to without waste heat recovery. In order to alleviate environmental impacts, the temperature at the end of the flue is further reduced from 160 to 110°C. The innovative waste heat recovery is helpful to energy savings and sustainable environment.

Keywords: waste heat recovery system, sustainability, RTO (Regenerative Thermal Oxidation), economizer, automotive industry

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Authors: M. Dhana Lakshmi, S. Sakthivel Murugan

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As light passes from source to observer in the water medium, it is scattered by the suspended particulate matter. This scattering effect will plague the captured images with non-uniform illumination, blurring details, halo artefacts, weak edges, etc. To overcome this, pixel normalization with an Amended Unsharp Mask (AUM) filter is proposed to enhance the degraded image. To validate the robustness of the proposed technique irrespective of atmospheric light, the considered datasets are collected on dual locations. For those images, the maxima and minima pixel intensity value is computed and normalized; then the AUM filter is applied to strengthen the blurred edges. Finally, the enhanced image is obtained with good illumination and contrast. Thus, the proposed technique removes the effect of scattering called de-hazing and restores the perceptual information with enhanced edge detail. Both qualitative and quantitative analyses are done on considering the standard non-reference metric called underwater image sharpness measure (UISM), and underwater image quality measure (UIQM) is used to measure color, sharpness, and contrast for both of the location images. It is observed that the proposed technique has shown overwhelming performance compared to other deep-based enhancement networks and traditional techniques in an adaptive manner.

Keywords: underwater drone imagery, pixel normalization, thresholding, masking, unsharp mask filter

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Authors: Husham Bayazed

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A growing number of studies indicate that atherosclerotic coronary artery disease (CAD) has a complex pathogenesis that extends beyond cholesterol intimal infiltration. The atherosclerosis process may involve an immune micro-environmental condition driven by local activation of the adaptive and innate immunity arrays, resulting in the formation of atherosclerotic plaques. Therefore, despite the wide usage of lipid-lowering agents, these devastating coronary diseases are not averted either at primary or secondary prevention levels. Many trials have recently shown an interest in the immune targeting of the inflammatory process of atherosclerotic plaques, with the promised improvement in atherosclerotic cardiovascular disease outcomes. This recently includes the immune-modulatory drug “Canakinumab” as an anti-interleukin-1 beta monoclonal antibody in addition to "Colchicine,” which's established as a broad-effect drug in the management of other inflammatory conditions. Recent trials and studies highlight the importance of inflammation and immune reactions in the pathogenesis of atherosclerosis and plaque formation. This provides an insight to discuss and extend the therapies from old lipid-lowering drugs (statins) to anti-inflammatory drugs (colchicine) and new targeted immune-modulatory therapies like inhibitors of IL-1 beta (canakinumab) currently under investigation.

Keywords: atherosclerotic plagues, immune microenvironment, lipid-lowering agents, and immunomodulatory drugs

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Authors: Amy L. Irvine, Gabriel Reygondeau, Derek P. Tittensor

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Marine protected areas (MPAs) within Canada’s exclusive economic zone help ensure the conservation and sustainability of marine ecosystems and the continued provision of ecosystem services to society (e.g., food, carbon sequestration). With ongoing and accelerating climate change, however, MPAs may become undermined in terms of their effectiveness at fulfilling these outcomes. Many populations of species, especially those at their thermal range limits, may shift to cooler waters or become extirpated due to climate change, resulting in new species compositions and ecological interactions within static MPA boundaries. While Canadian MPA management follows international guidelines for marine conservation, no consistent approach exists for adapting MPA networks to climate change and the resulting altered ecosystem conditions. To fill this gap, projected climate-driven shifts in species distributions on Canada’s east coast were analyzed to identify when native species emigrate and novel species immigrate within the network and how high mitigation and carbon emission scenarios influence these timelines. Indicators of the ecological changes caused by these species' shifts in the biological community were also developed. Overall, our research provides projections of climate change impacts and helps to guide adaptive management responses within the Canadian east coast MPA network.

Keywords: climate change, ecosystem modeling, marine protected areas, management

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Authors: Panpan Fan, Bo Ming, Niels Anten, Jochem Evers, Yaoyao Li, Shaokun Li, Ruizhi xie

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Nitrogen (N) utilization for crop production under N deficiency conditions is subject to a trade-off between maintaining specific leaf N content (SLN), important for radiation-use efficiency (RUE), versus maintaining leaf area (LA) development, important for light capture. This paper aims to explore how maize deals with this trade-off through responses in SLN, LA and their underlying traits during the vegetative and reproductive growth stages. In a ten-year N fertilization trial in Jilin province, Northeast China, three N fertilizer levels have been maintained: N-deficiency (N0), low N supply (N1), and high N supply (N2). We analyzed data from years 8 and 10 of this experiment for two common hybrids. Under N deficiency, maize plants maintained LA and decreased SLN during vegetative stages, while both LA and SLN decreased comparably during reproductive stages. Canopy-average specific leaf area (SLA) decreased sharply during vegetative stages and slightly during reproductive stages, mainly because senesced leaves in the lower canopy had a higher SLA. In the vegetative stage, maize maintained leaf area at low N by maintaining leaf biomass (albeit hence having N content/mass) and slightly increasing SLA. These responses to N deficiency were stronger in maize hybrid XY335 than in ZD958. We conclude the main strategy of maize to cope with low N is to maintain plant growth, mainly by increasing SLA throughout the plant during early growth. N was too limiting for either strategy to be followed during later growth stages.

Keywords: leaf N content per unit leaf area, N deficiency, specific leaf area, maize strateg

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Authors: Masahiro Miyaji

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When a driver happens to be involved in some traffic congestion or after traffic incidents, the driver may fall in a state of anger. State of anger may encounter decisive risk resulting in severer traffic accidents. Preventive safety function using driver’s psychosomatic state with regard to anger may be one of solutions which would avoid that kind of risks. Identifying driver’s anger state is important to create countermeasures to prevent the risk of traffic accidents. As a first step, this research figured out root cause of traffic incidents by means of using Internet survey. From statistical analysis of the survey, dominant psychosomatic states immediately before traffic incidents were haste, distraction, drowsiness and anger. Then, we replicated anger state of a driver while driving, and then, replicated it by means of using driving simulator on bench test basis. Six types of facial expressions including anger were introduced as alternative characteristics. Kohonen neural network was adopted to classify anger state. Then, we created a methodology to detect anger state of a driver in high accuracy. We presented a driving support safety function. The function adapts driver’s anger state in cooperation with an autonomous driving unit to reduce the number of traffic accidents. Consequently, e evaluated reduction rate of driver’s anger in the traffic accident. To validate the estimation results, we referred the reduction rate of Advanced Safety Vehicle (ASV) as well as Intelligent Transportation Systems (ITS).

Keywords: Kohonen neural network, driver’s anger state, reduction of traffic accidents, driver’s state adaptive driving support safety

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Authors: Sabahat Nadeem, Farman Ali Khan

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Emotions are considered as a vital factor affecting the process of information handling, level of attention, memory capacity and decision making. Latest e-Learning systems are therefore taking into consideration the effective state of learners to make the learning process more effective and enjoyable. One such use of user’s affective information is in the systems that tend to regulate users’ emotions to a state optimally desirable for learning. So for, this objective has been tried to be achieved with the help of teaching strategies, background music, guided imagery, video clips and odors. Nevertheless, we know that colors can affect human emotions. Relationship between color and emotions has a strong influence on how we perceive our environment. Similarly, the colors of the interface can also affect the user positively as well as negatively. This affective behavior of color and its use as emotion regulation agent is not yet exploited. Therefore, this research proposes a Color-based Emotion Regulation Model (CERM), a new framework that can automatically adapt its colors according to user’s emotional state and her personality type and can help in producing a desirable emotional effect, aiming at providing an unobtrusive emotional support to the users of e-learning environment. The evaluation of CERM is carried out by comparing it with classical non-adaptive, static colored learning management system. Results indicate that colors of the interface, when carefully selected has significant positive impact on learner’s emotions.

Keywords: effective learning, e-learning, emotion regulation, emotional design

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Authors: Zeyu Zhou, Xiaojun Bi

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Due to the limited environmental parameters and the limited resolution of the sensor, the universal existence of the mixed pixels in the process of remote sensing images restricts the spatial resolution of the remote sensing images. Sub-pixel mapping technology can effectively improve the spatial resolution. As the bilinear interpolation algorithm inevitably produces the edge blur effect, which leads to the inaccurate sub-pixel mapping results. In order to avoid the edge blur effect that affects the sub-pixel mapping results in the interpolation process, this paper presents a new edge-directed interpolation algorithm which uses the covariance adaptive interpolation algorithm on the edge of the low-resolution image and uses bilinear interpolation algorithm in the low-resolution image smooth area. By using the edge-directed interpolation algorithm, the super-resolution of the image with low resolution is obtained, and we get the percentage of each sub-pixel under a certain type of high-resolution image. Then we rely on the probability value as a soft attribute estimate and carry out sub-pixel scale under the ‘hard classification’. Finally, we get the result of sub-pixel mapping. Through the experiment, we compare the algorithm and the bilinear algorithm given in this paper to the results of the sub-pixel mapping method. It is found that the sub-pixel mapping method based on the edge-directed interpolation algorithm has better edge effect and higher mapping accuracy. The results of the paper meet our original intention of the question. At the same time, the method does not require iterative computation and training of samples, making it easier to implement.

Keywords: remote sensing images, sub-pixel mapping, bilinear interpolation, edge-directed interpolation

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Authors: Mirvat Shamseddine, Issam Lakkis

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We present an efficient, three-dimensional parallel multi-scale Direct Simulation Monte Carlo (DSMC) algorithm for the simulation of unsteady rarefied gas flows in micro/nanosystems. The algorithm employs a novel spatiotemporal adaptivity scheme. The scheme performs a fully dynamic multi-level grid adaption based on the gradients of flow macro-parameters and an automatic temporal adaptation. The computational domain consists of a hierarchical octree-based Cartesian grid representation of the flow domain and a triangular mesh for the solid object surfaces. The hybrid mesh, combined with the spatiotemporal adaptivity scheme, allows for increased flexibility and efficient data management, rendering the framework suitable for efficient particle-tracing and dynamic grid refinement and coarsening. The parallel algorithm is optimized to run DSMC simulations of strongly unsteady, non-equilibrium flows over multiple cores. The presented method is validated by comparing with benchmark studies and then employed to improve the design of micro-scale hotwire thermal sensors in rarefied gas flows.

Keywords: DSMC, oct-tree hierarchical grid, ray tracing, spatial-temporal adaptivity scheme, unsteady rarefied gas flows

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Authors: Fatemeh Keshavarz

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Background: Schizophrenia is a disease of the nervous system, and immune system disorders can affect its pathogenesis. Activation of microglia, proinflammatory cytokines, disruption of the blood-brain barrier (BBB) due to inflammation, activation of autoreactive B cells, and consequently the production of autoantibodies against system antigens are among the immune processes involved in neurological diseases. interleukin 32 (IL-32) a proinflammatory cytokine that important player in the activation of the innate and adaptive immune responses. This study aimed to measure the serum level of IL-32 as well as the frequency of autoantibody positivity against several nervous system antigens in patients with schizophrenia. Material and Methods: This study was conducted on 40 patients with schizophrenia and 40 healthy individuals in the control group. Serum IL-32 levels were measured by ELISA. The frequency of autoantibodies against Hu, Ri, Yo, Tr, CV2, Amphiphysin, SOX1, Zic4, ITPR1, CARP, GAD, Recoverin, Titin, and Ganglioside antigens were measured by indirect immunofluorescence method. Results: Serum IL-32 levels in patients with schizophrenia were significantly higher compared to the control group. Autoantibodies were positive in 8 patients for GAD antigen and 5 patients for Ri antigen, which showed a significant relationship compared to the control group. Autoantibodies were also positive in 2 patients for CV2, in 1 patient for Hu, and in 1 patient for CARP. Negative results were reported for other antigens. Conclusion: Our findings suggest that elevated the serum IL-32 level and autoantibody positivity against several nervous system antigens may be involved in the pathogenesis of schizophrenia.

Keywords: schizophrenia, microglia, autoantibodies, IL-32

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Authors: Jonas Colin

Abstract:

Standing at the vanguard of AI development, Alpha represents an unprecedented synthesis of logical rigor and human abstraction, meticulously crafted to mirror the user's unique persona and personality, a feat previously unattainable in AI development. Alpha, an avant-garde artefact in the realm of artificial intelligence, epitomizes a paradigmatic shift in personalized digital interaction, amalgamating user-specific dialogic patterns with the sophisticated algorithmic prowess of OpenAI's GPT-3.5 to engender a platform for enhanced metacognitive engagement and individualized user experience. Underpinned by a sophisticated algorithmic framework, Alpha integrates vast datasets through a complex interplay of neural network models and symbolic AI, facilitating a dynamic, adaptive learning process. This integration enables the system to construct a detailed user profile, encompassing linguistic preferences, emotional tendencies, and cognitive styles, tailoring interactions to align with individual characteristics and conversational contexts. Furthermore, Alpha incorporates advanced metacognitive elements, enabling real-time reflection and adaptation in communication strategies. This self-reflective capability ensures continuous refinement of its interaction model, positioning Alpha not just as a technological marvel but as a harbinger of a new era in human-computer interaction, where machines engage with us on a deeply personal and cognitive level, transforming our interaction with the digital world.

Keywords: chatbot, GPT 3.5, metacognition, symbiose

Procedia PDF Downloads 43

Authors: Chih-Chieh Yang, Chung-Neng Huang

Abstract:

In power system, how to improve the fault diagnosis technology of transmission line has always been the primary goal of power grid operators. In recent years, due to the rise of green energy, the addition of all kinds of distributed power also has an impact on the stability of the power system. Because the smart meters are with the function of data recording and bidirectional transmission, the adaptive Fuzzy Neural inference system, ANFIS, as well as the artificial intelligence that has the characteristics of learning and estimation in artificial intelligence. For transmission network, in order to avoid misjudgment of the fault type and location due to the input of these unstable power sources, combined with the above advantages of smart meter and ANFIS, a method for identifying fault types and location of faults is proposed in this study. In ANFIS training, the bus voltage and current information collected by smart meters can be trained through the ANFIS tool in MATLAB to generate fault codes to identify different types of faults and the location of faults. In addition, due to the uncertainty of distributed generation, a wind power system is added to the transmission network to verify the diagnosis correctness of the study. Simulation results show that the method proposed in this study can correctly identify the fault type and location of fault with more efficiency, and can deal with the interference caused by the addition of unstable power sources.

Keywords: ANFIS, fault diagnosis, power system, smart meter

Procedia PDF Downloads 122

Authors: Helene Thieblemont, Fariborz Haghighat

Abstract:

Energy storage systems play a crucial role in decreasing building energy consumption during peak periods and expand the use of renewable energies in buildings. To provide a high building thermal performance, the energy storage system has to be properly controlled to insure a good energy performance while maintaining a satisfactory thermal comfort for building’s occupant. In the case of passive discharge storages, defining in advance the required amount of energy is required to avoid overheating in the building. Consequently, anticipatory supervisory control strategies have been developed forecasting future energy demand and production to coordinate systems. Anticipatory supervisory control strategies are based on some predictions, mainly of the weather forecast. However, if the forecasted hourly outdoor temperature may be found online with a high accuracy, solar radiations predictions are most of the time not available online. To estimate them, this paper proposes an advanced approach based on the forecast of weather conditions. Several methods to correlate hourly weather conditions forecast to real hourly solar radiations are compared. Results show that using weather conditions forecast allows estimating with an acceptable accuracy solar radiations of the next day. Moreover, this technique allows obtaining hourly data that may be used for building models. As a result, this solar radiation prediction model may help to implement model-based controller as Model Predictive Control.

Keywords: anticipatory control, model predictive control, solar radiation forecast, thermal storage

Procedia PDF Downloads 253

Authors: Moaine Jebara, Lionel Boillereaux, Sofiane Belhabib, Michel Havet, Alain Sarda, Pierre Mousseau, Rémi Deterre

Abstract:

Energy consumption efficiency is a major concern for the material processing industry such as thermoforming process and molding. Indeed, these systems should deliver the right amount of energy at the right time to the processed material. Recent technical development, as well as the particularities of the heating system dynamics, made the Model Predictive Control (MPC) one of the best candidates for thermal control of several production processes like molding and composite thermoforming to name a few. The main principle of this technique is to use a dynamic model of the process inside the controller in real time in order to anticipate the future behavior of the process which allows the current timeslot to be optimized while taking future timeslots into account. This study presents a procedure based on a predictive control that brings balance between optimality, simplicity, and flexibility of its implementation. The development of this approach is progressive starting from the case of a single zone before its extension to the multizone and/or multisource case, taking thus into account the thermal couplings between the adjacent zones. After a quadratic formulation of the MPC criterion to ensure the thermal control, the linear expression is retained in order to reduce calculation time thanks to the use of the ARMAX linear decomposition methods. The effectiveness of this approach is illustrated by experiment and simulation.

Keywords: energy efficiency, linear decomposition methods, model predictive control, mold heating systems

Procedia PDF Downloads 248

Authors: Simon Keller, Rainer Mueller

Abstract:

Continuous range queries are a common means to handle mobile clients in high-density areas. Most existing approaches focus on settings in which the range queries for location-based services are more or less static, whereas the mobile clients in the ranges move. We focus on a category called dynamic real-time range queries (DRRQ), assuming that both, clients requested by the query and the inquirers, are mobile. In consequence, the query parameters and the query results continuously change. This leads to two requirements: the ability to deal with an arbitrarily high number of mobile nodes (scalability) and the real-time delivery of range query results. In this paper, we present the highly decentralized solution adaptive quad streaming (AQS) for the requirements of DRRQs. AQS approximates the query results in favor of a controlled real-time delivery and guaranteed scalability. While prior works commonly optimize data structures on the involved servers, we use AQS to focus on a highly distributed cell structure without data structures automatically adapting to changing client distributions. Instead of the commonly used request-response approach, we apply a lightweight streaming method in which no bidirectional communication and no storage or maintenance of queries are required at all.

Keywords: approximation of client distributions, continuous spatial range queries, mobile objects, streaming-based decentralization in spatial mobile environments

Procedia PDF Downloads 120

Authors: Nadine Sammy, Mark Wilson, Samuel Vine

Abstract:

The Theory of Challenge and Threat States in Athletes (TCTSA) states that self-efficacy is an antecedent of challenge and threat. These states result from conscious and unconscious evaluations of situational demands and personal resources and are represented by both cognitive and physiological markers. Challenge is considered a more adaptive stress response as it is associated with a more efficient cardiovascular profile, as well as better performance and attention effects compared with threat. Self-efficacy is proposed to influence challenge/threat because an individual’s belief that they have the skills necessary to execute the courses of action required to succeed contributes to a perception that they can cope with the demands of the situation. This study experimentally examined the effects of self-efficacy on cardiovascular responses (challenge and threat), demand and resource evaluations, performance and attention under pressurised conditions. Forty-five university students were randomly assigned to either a control (n=15), low self-efficacy (n=15) or high self-efficacy (n=15) group and completed baseline and pressurised golf putting tasks. Self-efficacy was manipulated using false feedback adapted from previous studies. Measures of self-efficacy, cardiovascular reactivity, demand and resource evaluations, task performance and attention were recorded. The high self-efficacy group displayed more favourable cardiovascular reactivity, indicative of a challenge state, compared with the low self-efficacy group. The former group also reported high resource evaluations, but no task performance or attention effects were detected. These findings demonstrate that levels of self-efficacy influence cardiovascular reactivity and perceptions of resources under pressurised conditions.

Keywords: cardiovascular, challenge, performance, threat

Procedia PDF Downloads 212