Search results for: artificial plasma

Authors: Johan Buermans, Kristel Crombé, Niek Desmet, Laura Dittrich, Andrei Goriaev, Yurii Kovtun, Daniel López-Rodriguez, Sören Möller, Per Petersson, Maja Verstraeten

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The International Thermonuclear Experimental Reactor (ITER) will rely on three sources of external heating to produce and sustain a plasma; Neutral Beam Injection (NBI), Ion Cyclotron Resonance Heating (ICRH), and Electron Cyclotron Resonance Heating (ECRH). ECRH is a way to heat the electrons in a plasma by resonant absorption of electromagnetic waves. The energy of the electrons is transferred indirectly to the ions by collisions. The electron cyclotron heating system can be directed to deposit heat in particular regions in the plasma (https://www.iter.org/mach/Heating). Electron Cyclotron Resonance Heating (ECRH) at the fundamental resonance in X-mode is limited by a low cut-off density. Electromagnetic waves cannot propagate in the region between this cut-off and the Upper Hybrid Resonance (UHR) and cannot reach the Electron Cyclotron Resonance (ECR) position. Higher harmonic heating is hence preferred in heating scenarios nowadays to overcome this problem. Additional power deposition mechanisms can occur above this threshold to increase the plasma density. This includes collisional losses in the evanescent region, resonant power coupling at the UHR, tunneling of the X-wave with resonant coupling at the ECR, and conversion to the Electron Bernstein Wave (EBW) with resonant coupling at the ECR. A more profound knowledge of these deposition mechanisms can help determine the optimal plasma production scenarios. Several ECRH experiments are performed on the TOroidally MAgnetized System (TOMAS) to identify the conditions for Electron Bernstein Wave (EBW) heating. Density and temperature profiles are measured with movable Triple Langmuir Probes in the horizontal and vertical directions. Measurements of the forwarded and reflected power allow evaluation of the coupling efficiency. Optical emission spectroscopy and camera images also contribute to plasma characterization. The influence of the injected power, magnetic field, gas pressure, and wave polarization on the different deposition mechanisms is studied, and the contribution of the Electron Bernstein Wave is evaluated. The TOMATOR 1D hydrogen-helium plasma simulator numerically describes the evolution of current less magnetized Radio Frequency plasmas in a tokamak based on Braginskii’s legal continuity and heat balance equations. This code was initially benchmarked with experimental data from TCV to determine the transport coefficients. The code is used to model the plasma parameters and the power deposition profiles. The modeling is compared with the data from the experiments.

Keywords: electron Bernstein wave, Langmuir probe, plasma characterization, TOMAS

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Authors: Kaoutar Abbahaddou, Mohammed Salah Chiadmi

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The need to find a relevant way to predict the next-day price of a stock index is a real concern for many financial stakeholders and researchers. We have known across years the proliferation of several methods. Nevertheless, among all these methods, the most controversial one is a machine learning algorithm that claims to be reliable, namely neural networks. Thus, the purpose of this article is to study the prediction power of neural networks in the particular case of Islamic finance as it is an under-looked area. In this article, we will first briefly present a review of the literature regarding neural networks and Islamic finance. Next, we present the architecture and principles of artificial neural networks most commonly used in finance. Then, we will show its empirical application on two Islamic stock indexes. The accuracy rate would be used to measure the performance of the algorithm in predicting the right price the next day. As a result, we can conclude that artificial neural networks are a reliable method to predict the next-day price for Islamic indices as it is claimed for conventional ones.

Keywords: Islamic finance, stock price prediction, artificial neural networks, machine learning

Procedia PDF Downloads 193

Authors: Foong Kiew Ooi, Aidi Naim Mohamad Samsani, Chee Keong Chen, Mohamed Saat Ismail

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Introduction: Prolonged exercise in a hot and humid environment can result in glycogen depletion and associated with loss of body fluid. Carbohydrate contained in sports beverages is beneficial for improving sports performance and preventing dehydration. Carbohydrate contained in honey is believed can be served as an alternative form of carbohydrate for enhancing sports performance. Objective: To investigate the effectiveness of honey drink compared to sports drink as a recovery aid for running performance and physiological parameters in the heat. Method: Ten male recreational athletes (age: 22.2 ± 2.0 years, VO2max: 51.5 ± 3.7 ml.kg-1.min-1) participated in this randomized cross-over study. On each trial, participants were required to run for 1 hour in the glycogen depletion phase (Run-1), followed by a rehydration phase for 2 hours and subsequently a 20 minutes time trial performance (Run-2). During Run-1, subjects were required to run on the treadmill in the heat (31°C) with 70% relative humidity at 70 % of their VO2max. During rehydration phase, participants drank either honey drink or sports drink, or plain water with amount equivalent to 150% of body weight loss in dispersed interval (60 %, 50 % and 40 %) at 0 min, 30 min and 60 min respectively. Subsequently, time trial was performed by the participants in 20 minutes and the longest distance covered was recorded. Physiological parameters were analysed using two-way ANOVA with repeated measure and time trial performance was analysed using one-way ANOVA. Results: Result showed that Acacia honey elicited a better time trial performance with significantly longer distance compared to water trial (P<0.05). However, there was no significant difference between Acacia honey and sport drink trials (P > 0.05). Acacia honey and sports drink trials elicited 249 m (8.24 %) and 211 m (6.79 %) longer in distance compared to the water trial respectively. For physiological parameters, plasma glucose, plasma insulin and plasma free fatty acids in Acacia honey and sports drink trials were significantly higher compared to the water trial respectively during rehydration phase and time trial running performance phase. There were no significant differences in body weight changes, oxygen uptake, hematocrit, plasma volume changes and plasma cortisol in all the trials. Conclusion: Acacia honey elicited greatest beneficial effects on sports performance among the drinks, thus it has potential to be used for rehydration in athletes who train and compete in hot environment.

Keywords: honey drink, rehydration, sports performance, plasma glucose, plasma insulin, plasma cortisol

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Authors: Elana Mahboub, Lamar Bakhurji, Hind Alhindi, Sara Alesayi

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Duolingo is a revolutionary language learning platform that offers an interactive and accessible learning experience. Its gamified approach makes language learning engaging and enjoyable, with a diverse range of languages available. The platform's adaptive learning system tailors lessons to individual proficiency levels, ensuring a personalized and efficient learning journey. The incorporation of multimedia elements enhances the learning experience and promotes practical language application. Duolingo's success is attributed to its mobile accessibility, offering basic access to language courses for free, with optional premium features for those seeking additional resources. Research shows positive outcomes for users, and the app's global impact extends beyond individual learning to formal language education initiatives. Duolingo is a transformative force in language education, breaking down barriers and making language learning an attainable goal for millions worldwide.

Keywords: duolingo, artificial intelligence, artificial intelligence in duolingo, benefit of artificial intelligence

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Authors: Sandeep Kumar, Naveen Gupta

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Terahertz (THz) generation has been investigated by beating two cosh-Gaussian laser beams of the same amplitude but different wavenumbers and frequencies through rippled collisionless plasma. The ponderomotive force is operative which is induced due to the intensity gradient of the laser beam over the cross-section area of the wavefront. The electrons evacuate towards a low-intensity regime, which modifies the dielectric function of the medium and results in cross focusing of cosh-Gaussian laser beams. The evolution of spot size of laser beams has been studied by solving nonlinear Schrodinger wave equation (NLSE) with variational technique. The laser beams impart oscillations to electrons which are enhanced with ripple density. The nonlinear oscillatory motion of electrons gives rise to a nonlinear current density driving THz radiation. It has been observed that the periodicity of the ripple density helps to enhance the THz radiation.

Keywords: rippled collisionless plasma, cosh-gaussian laser beam, ponderomotive force, variational technique, nonlinear current density

Procedia PDF Downloads 168

Authors: Masoumeh Asadi Aghbolaghi, Beata Dedicova, Farzad Sharifzadeh, Mansoor Omidi, Ulrika Egertsdotter

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Stipagrostis pennata is one of the valuable fodder plants and is very resistant to drought, due to the low capacity of seed production, the use of asexual reproduction methods, including somatic embryogenesis and artificial seed, can increase its reproduction on a large scale. This study was conducted in order to obtain optimal treatments for the production of artificial seeds of this plant through the somatic embryo encapsulating. Embryonic calluses were encapsulated using sodium alginate and calcium chloride and then sowed in a germination medium. The experiment was conducted as a factorial based on a completely randomized design with three replications. The treatments include three concentrations of sodium alginate (1.5, 2.5, and 3.5 percent), two ion exchange times (20 and 30 minutes,) and two artificial seed germination media (hormone free MS and MS containing zeatin riboside and L-proline). Germination percentage and number of days until the beginning of germination were investigated. The highest percentage of artificial seed germination was obtained when 2.5% sodium alginate was used for 30 minutes (ion exchange time) and the seeds were placed on the germination medium containing zeatin riboside and L-proline.

Keywords: somatic embryogenesis, Stipagrostis pennata, synthetic seed, tissue culture

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Authors: Hossein Barri Ghazani

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Transfusion-related acute lung injury is the main reason of transfusion-related death, and it’s assigned to white blood cell reactive antibodies present in the blood product (anti-HLA class I and class II or anti granulocyte antibodies). TRALI may occur in the COVID-19 patients who are treated by convalescent plasma. The rate of TRALI’s reactions is the same in both males and females and can happen in all age groups. TRALI’s occurrence is higher for people who receive plasma from female donors because the parous female donors have multiple HLA antibodies in their plasma. Patients with chronic liver disease have an augmented risk of transfusion-related acute lung injuries from plasma containing blood products like FFP and PRP. The condition of TRALI suddenly starts with a non‐cardiogenic pulmonary Edema, often accompanied by marked systemic hypovolemic and hypotension. The conditions occur during or within a few hours of transfusion. Chest X-ray shows a nodular penetration or bats’ wing pattern of Edema which can be seen in acute respiratory distress syndrome as well. TRALI can occur with any type of blood products and can occur with as little as one unit. The blood donor center should be informed of the suspected TRALI reactions when the symptoms of TRALI are observed. After a review of the clinical data, the donors must be screened for granulocyte and HLA antibodies. The diagnosis and management of TRALI is not simple and is best done with a professional team and a specialty skilled nurse experienced with the upkeep of these patients.

Keywords: TRALI, transfusion-related death, anti-granulocyte antibodies, anti-HLA antibodies, COVID-19

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Authors: J. K. Alhassan, C. S. Actsu

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This study is on the prediction of feature performance of undergraduate students with Artificial Neural Networks (ANN). With the growing decline in the quality academic performance of undergraduate students, it has become essential to predict the students’ feature academic performance early in their courses of first and second years and to take the necessary precautions using such prediction-based information. The feed forward multilayer neural network model was used to train and develop a network and the test carried out with some of the input variables. A result of 80% accuracy was obtained from the test which was carried out, with an average error of 0.009781.

Keywords: academic performance, artificial neural network, prediction, students

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Authors: Yosra Mefteh Rekik, Younes Boujelbene

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We introduce in this paper a new conceptual model representing the stock market dynamics. This model is essentially based on cognitive behavior of the intelligence investors. In order to validate our model, we build an artificial stock market simulation based on agent-oriented methodologies. The proposed simulator is composed of market supervisor agent essentially responsible for executing transactions via an order book and various kinds of investor agents depending to their profile. The purpose of this simulation is to understand the influence of psychological character of an investor and its neighborhood on its decision-making and their impact on the market in terms of price fluctuations. Therefore, the difficulty of the prediction is due to several features: the complexity, the non-linearity and the dynamism of the financial market system, as well as the investor psychology. The Artificial Neural Networks learning mechanism take on the role of traders, who from their futures return expectations and place orders based on their expectations. The results of intensive analysis indicate that the existence of agents having heterogeneous beliefs and preferences has provided a better understanding of price dynamics in the financial market.

Keywords: artificial intelligence methods, artificial stock market, behavioral modeling, multi-agent based simulation

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Authors: Aroob Binhimd, Lyan Sayoti, Rana Almansour

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In recent years, artificial intelligence has grown drastically. This has led to the growth of educational programs to help students in solving educational problems and assist them in understanding certain topics. The purpose of this report is to investigate the Mathway application. Mathway is a mathematics software that teaches students how to solve and handle mathematical issues. The app allows students to insert questions manually on the platform or take a picture of the question, and then they get an answer to this mathematical question. It helps students enhance their performance in mathematics. This app can also be used to verify or check if their answers are correct. The report will include a questionnaire to collect data and analyze the users of this application.

Keywords: artificial intelligence, Mathway, mathematics, mathematical problems

Procedia PDF Downloads 228

Authors: Elena K. Schneider, Johnny X. Huang, Vincenzo Carbone, Mark Baker, Mohammad A. K. Azad, Matthew A. Cooper, Jian Li, Tony Velkov

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Ivacaftor is a novel CF trans-membrane conductance regulator (CFTR) potentiator that improves the pulmonary function for cystic fibrosis patients bearing a G551D CFTR-protein mutation. Because ivacaftor is highly bound (>97%) to plasma proteins, there is the strong possibility that co-administered CF drugs that compete for the same plasma protein binding sites and impact the free drug concentration. This in turn could lead to drastic changes in the in vivo efficacy of ivacaftor and therapeutic outcomes. This study compares the binding affinity of ivacaftor and co-administered CF drugs for human serum albumin (HSA) and α1-acid glycoprotein (AGP) using surface plasmon resonance and fluorimetric binding assays that measure the displacement of site selective probes. Due to their high plasma protein binding affinities, drug-drug interactions between ivacaftor are to be expected with ducosate, montelukast, ibuprofen, dicloxacillin, omeprazole and loratadine. The significance of these drug-drug interactions is interpreted in terms of the pharmacodynamic/pharmacokinetic parameters and molecular docking simulations. The translational outcomes of the data are presented as recommendations for a staggered treatment regimen for future clinical trials which aims to maximize the effective free drug concentration and clinical efficacy of ivacaftor.

Keywords: human α-1-acid glycoprotein, binding affinity, human serum albumin, ivacaftor, cystic fibrosis

Procedia PDF Downloads 279

Authors: Sarun Phibanchon, Yuttakarn Rattanachai

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The quadratic-cubic nonlinear Schrodinger equation can be explained the weakly ion-acoustic waves in magnetized plasma with a slightly non-Maxwellian electron distribution by using the Madelung's fluid picture. However, the soliton solution to the quadratic-cubic nonlinear Schrodinger equation is determined by using the direct integration. By the characteristics of a soliton, the solution can be claimed that it's a soliton by considering its time evolution and their collisions between two solutions. These results are shown by applying the spectral method.

Keywords: soliton, ion-acoustic waves, plasma, spectral method

Procedia PDF Downloads 379

Authors: Abdelmadjid Mammeri, Fatima Zohra Mahi, Luca Varani, H. Marinchoi

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We propose an analytical model for the admittance and the noise calculations of the InGaAs transistor and diode. The development of the small-signal admittance takes into account the longitudinal and transverse electric fields through a pseudo two-dimensional approximation of the Poisson equation. The frequency-dependent of the small-signal admittance response is determined by the total currents and the potentials matrix relation between the gate and the drain terminals. The noise is evaluated by using the real part of the transistor/diode admittance under a small-signal perturbation. The analytical results show that the admittance spectrum exhibits a series of resonant peaks corresponding to the excitation of plasma waves. The appearance of the resonance is discussed and analyzed as functions of the channel length and the temperature. The model can be used, on one hand; to control the appearance of the plasma resonances, and on other hand; can give significant information about the noise frequency dependence in the InGaAs transistor and diode.

Keywords: InGaAs transistors, InGaAs diode, admittance, resonant peaks, plasma waves, analytical model

Procedia PDF Downloads 281

Authors: Dong Nyoung Heo, Il Keun Kwon

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Three-dimensional (3D) technology is a promising method for bone tissue engineering. In order to enhance bone tissue regeneration, it is important to have ideal 3D constructs with biomimetic mechanical strength, structure interconnectivity, roughened surface, and the presence of chemical functionality. In this respect, a 3D printing system combined with cold atmospheric plasma (CAP) was developed to fabricate a 3D construct that has a rough surface with polar functional chemical groups. The CAP-etching process leads to oxidation of chemical groups existing on the polycaprolactone (PCL) surface without conformational change. The surface morphology, chemical composition, mean roughness of the CAP-treated PCL surfaces were evaluated. 3D printed constructs composed of CAP-treated PCL showed an effective increment in the hydrophilicity and roughness of the PCL surface. Also, an in vitro study revealed that CAP-treated 3D PCL constructs had higher cellular behaviors such as cell adhesion, cell proliferation, and osteogenic differentiation. Therefore, a 3D printing system with CAP can be a highly useful fabrication method for bone tissue regeneration.

Keywords: bone tissue engineering, cold atmospheric plasma, PCL, 3D printing

Procedia PDF Downloads 84

Authors: Nisha Prakash, Kritika Anand, Arun Barvat, Prabir Pal, Sonachand Adhikari, Suraj P. Khanna

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Group-III nitride semiconductors (GaN, AlN, InN and their ternary and quaternary compounds) have attracted a great deal of attention for the development of high-performance Ultraviolet (UV) photodetectors. Any midgap defect states in the epitaxial grown film have a direct influence on the photodetectors responsivity. The proportion of the midgap defect states can be controlled by the growth parameters. To study this we have grown high quality epitaxial GaN films on MOCVD- grown GaN template using plasma-assisted molecular beam epitaxy (PAMBE) with different growth parameters. Optical and electrical properties of the films were characterized by room temperature photoluminescence and photoconductivity measurements, respectively. The observed persistent photoconductivity behaviour is proportional to the yellow luminescence (YL) and the absolute responsivity has been found to decrease with decreasing YL. The results will be discussed in more detail later.

Keywords: gallium nitride, plasma-assisted molecular beam epitaxy, photoluminescence, photoconductivity, persistent photoconductivity, yellow luminescence

Procedia PDF Downloads 287

Authors: Abisha Isaac Mohanlal

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Amidst all suspicions and cynicism raised by the legal fraternity, Artificial Intelligence has found its way into the legal system and has revolutionized the conventional forms of legal services delivery. Be it legal argumentation and research or resolution of complex legal disputes; artificial intelligence has crept into all legs of modern day legal services. Its impact has been largely felt by way of big data, legal expert systems, prediction tools, e-lawyering, automated mediation, etc., and lawyers around the world are forced to upgrade themselves and their firms to stay in line with the growth of technology in law. Researchers predict that the future of legal services would belong to artificial intelligence and that the age of human lawyers will soon rust. But as far as the Judiciary is concerned, even in the developed countries, the system has not fully drifted away from the orthodoxy of preferring Natural Intelligence over Artificial Intelligence. Since Judicial decision-making involves a lot of unstructured and rather unprecedented situations which have no single correct answer, and looming questions of legal interpretation arise in most of the cases, discretion and Emotional Intelligence play an unavoidable role. Added to that, there are several ethical, moral and policy issues to be confronted before permitting the intrusion of Artificial Intelligence into the judicial system. As of today, the human judge is the unrivalled master of most of the judicial systems around the globe. Yet, scientists of Artificial Intelligence claim that robot judges can replace human judges irrespective of how daunting the complexity of issues is and how sophisticated the cognitive competence required is. They go on to contend that even if the system is too rigid to allow robot judges to substitute human judges in the recent future, Artificial Intelligence may still aid in other judicial tasks such as drafting judicial documents, intelligent document assembly, case retrieval, etc., and also promote overall flexibility, efficiency, and accuracy in the disposal of cases. By deconstructing the major challenges that Artificial Intelligence has to overcome in order to successfully invade the human- dominated judicial sphere, and critically evaluating the potential differences it would make in the system of justice delivery, the author tries to argue that penetration of Artificial Intelligence into the Judiciary could surely be enhancive and reparative, if not fully transformative.

Keywords: artificial intelligence, judicial decision making, judicial systems, legal services delivery

Procedia PDF Downloads 197

Authors: R. Boudjelthia

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The aim of this study is to determine the influence of mix composition of concrete as the content of water and cement, water–binder ratio, and the replacement of fly ash on the durability of self compacting concrete (SCC) by using artificial neural networks (ANNs). To achieve this, an ANNs model is developed to predict the durability of self compacting concrete which is expressed in terms of chloride ions permeability in accordance with ASTM C1202-97 or AASHTO T277. Database gathered from the literature for the training and testing the model. A sensitivity analysis was also conducted using the trained and tested ANN model to investigate the effect of fly ash on the durability of SCC. The results indicate that the developed model is reliable and accurate. the durability of SCC expressed in terms of total charge passed over a 6-h period can be significantly improved by using at least 25% fly ash as replacement of cement. This study show that artificial neural network have strong potentialas a feasible tool for predicting accurately the durability of SCC containing fly ash.

Keywords: artificial neural networks, durability, chloride ions permeability, self compacting concrete

Procedia PDF Downloads 343

Authors: P. Akbartehrani, M. Khaledi Pour, M. Amini, M. Khani, M. Mohajeri Tehrani, E. Ghasemi, P. Charipoor, B. Shokri

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A common problem between diabetic patients is foot ulcers which are chronic and require specialized treatment. Previous studies illustrate that Cold atmospheric plasma (CAP) has beneficial effects on wound healing and infection. Nevertheless, the comparison of different cap exposure protocols in diabetic ulcer wound healing remained to be studied. This study aims to determine the effect of two different exposure protocols on wound healing in diabetic ulcers. A prospective, randomized clinical trial was conducted at two clinics. Diabetic patients with G1 and G2 wanger classification diabetic foot ulcers were divided into two groups of study. One group was treated by the first protocol, which was treating wounds by argon-generated cold atmospheric plasma jet once a week for five weeks in a row. The other group was treated by the second protocol, which was treating wounds every three days for five weeks in a row. The wounds were treated for 40 seconds/cubic centimeter, while the nozzle tip was moved nonlocalized 1 cm above the wounds. A patient with one or more wounds could participate in different groups as wounds were separately randomized, which allow a participant to be treated several times during the study. The study's significant findings were two different reductions rate in wound size, microbial load, and two different healing speeds. This study concludes that CAP therapy by the second protocol yields more effective healing speeds, reduction in wound sizes, and microbial loads of foot ulcers in diabetic patients.

Keywords: wound healing, diabetic ulcers, cold atmospheric plasma, cold argon jet

Procedia PDF Downloads 192

Authors: Victor S. Klimin, Alexey A. Rezvan, Maxim S. Solodovnik, Oleg A. Ageev

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In this paper, the problems of existing methods of profiling and surface modification of nanoscale arsenide-gallium structures are analyzed. The use of a combination of methods of local anodic oxidation and plasma chemical etching to solve this problem is considered. The main features that make this technology one of the promising areas of modification and profiling of near-surface layers of solids are demonstrated. In this paper, we studied the effect of formation stress and etching time on the geometrical parameters of the etched layer and the roughness of the etched surface. Experimental dependences of the thickness of the etched layer on the time and stress of formation were obtained. The surface analysis was carried out using atomic force microscopy methods, the corresponding profilograms were constructed from the obtained images, and the roughness of the etched surface was studied accordingly. It was shown that at high formation voltage, the depth of the etched surface increased, this is due to an increase in the number of active particles (oxygen ions and hydroxyl groups) formed as a result of the decomposition of water molecules in an electric field, during the formation of oxide nanostructures on the surface of gallium arsenide. Oxide layers were used as negative masks for subsequent plasma chemical etching by the STE ICPe68 unit. BCl₃ was chosen as the chlorine-containing gas, which differs from analogs in some parameters for the effect of etching of nanostructures based on gallium arsenide in the low-temperature plasma. The gas mixture of reaction chamber consisted of a buffer gas NAr = 100 cm³/min and a chlorine-containing gas NBCl₃ = 15 cm³/min at a pressure P = 2 Pa. The influence of these methods modes, which are formation voltage and etching time, on the roughness and geometric parameters, and corresponding dependences are demonstrated. Probe nanotechnology was used for surface analysis.

Keywords: nanostructures, GaAs, plasma chemical etching, modification structures

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Authors: Mehrnoosh Abouzari, Shahrokh Shahraei

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With the development of artificial intelligence in the present age, intelligent machines and systems have proven their actual and potential capabilities and are mindful of increasing their presence in various fields of human life in the fields of industry, financial transactions, marketing, manufacturing, service affairs, politics, economics and various branches of the humanities .Therefore, despite the conservatism and prudence of law enforcement, the traces of artificial intelligence can be seen in various areas of law. Including judicial robotics capability estimation, intelligent judicial decision making system, intelligent defender and attorney strategy adjustment, dissemination and regulation of different and scattered laws in each case to achieve judicial coherence and reduce opinion, reduce prolonged hearing and discontent compared to the current legal system with designing rule-based systems, case-based, knowledge-based systems, etc. are efforts to apply AI in law. In this article, we will identify the ways in which AI is applied in its laws and regulations, identify the dominant concerns in this area and outline the relationship between these two areas in order to answer the question of how artificial intelligence can be used in different areas of law and what the implications of this application will be. The authors believe that the use of artificial intelligence in the three areas of legislative, judiciary and executive power can be very effective in governments' decisions and smart governance, and helping to reach smart communities across human and geographical boundaries that humanity's long-held dream of achieving is a global village free of violence and personalization and human error. Therefore, in this article, we are going to analyze the dimensions of how to use artificial intelligence in the three legislative, judicial and executive branches of government in order to realize its application.

Keywords: artificial intelligence, law, intelligent system, judge

Procedia PDF Downloads 88

Authors: Amel Boulemtafes-Boukadoum, Ahmed Benzaoui

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Solar air heaters (SAH) are widely used in heating and drying applications using solar energy. Their efficiency needs to be improved to be competitive towards solar water heater. In this work, our goal is to study heat transfer enhancement in SAHs by the use of artificial roughness on the absorber. For this purpose, computational fluid dynamics (CFD) simulations were carried out to analyze the flow and heat transfer in the air duct of a solar air heater provided with transverse ribs. The air flows in forced convection and the absorber is heated with uniform flux. The effect of major parameters (Reynolds number, solar radiation, air inlet temperature, geometry of roughness) is examined and discussed. To highlight the effect of artificial roughness, we plotted the distribution of the important parameters: Nusselt number, friction factor, global thermohydraulic performance parameter etc. The results obtained are concordant to those found in the literature and shows clearly the heat transfer enhancement due to artifical roughness.

Keywords: solar air heater, artificial roughness, heat transfer enhancement, CFD

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Authors: M. Heydari Vini

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There is a complicated relation between effective input parameters of cold rolling and output rolling force and exit thickness of strips.in many mathematical models, the effect of some rolling parameters have been ignored and the outputs have not a desirable accuracy. In the other hand, there is a special relation among input thickness of strips,the width of the strips,rolling speeds,mandrill tensions and the required exit thickness of strips with rolling force and the real exit thickness of the rolled strip. First of all, in this paper the effective parameters of cold rolling process modeled using an artificial neural network according to the optimum network achieved by using a written program in MATLAB,it has been shown that the prediction of rolling stand parameters with different properties and new dimensions attained from prior rolled strips by an artificial neural network is applicable.

Keywords: cold rolling, artificial neural networks, rolling force, real rolled thickness of strips

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Authors: Tala Toonsi, Marah Alagha, Lina Alnowaiser, Hala Rajab

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This report is about the Photomath app, which is an AI application that uses image recognition technology, specifically optical character recognition (OCR) algorithms. The (OCR) algorithm translates the images into a mathematical equation, and the app automatically provides a step-by-step solution. The application supports decimals, basic arithmetic, fractions, linear equations, and multiple functions such as logarithms. Testing was conducted to examine the usage of this app, and results were collected by surveying ten participants. Later, the results were analyzed. This paper seeks to answer the question: To what level the artificial intelligence features are accurate and the speed of process in this app. It is hoped this study will inform about the efficiency of AI in Photomath to the users.

Keywords: photomath, image recognition, app, OCR, artificial intelligence, mathematical equations.

Procedia PDF Downloads 138

Authors: Miesam Golzadeh Gangraj, Younes Parvasi, Mohammad Ghasemi, Ahmad Abdi, Saeid Fazelifar

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The purpose of the study was to determine the effect of glucose feeding on energy and hormonal indexes in plasma and lymphocyte immediately after wrestling – base techniques circuit exercise (WBTCE) in young male freestyle wrestlers. Sixteen wrestlers (weight = 75/45 ± 12/92 kg, age = 22/29 ± 0/90 years, BMI = 26/23 ± 2/64 kg/m²) were randomly divided into two groups: control (water), glucose (2 gr per kg body weight). Blood samples were obtained before, immediately, and 90 minutes of the post-exercise recovery period. Glucose (2 g/kg of body weight, 1W/5V) and water (equal volumes) solutions were given immediately after the second blood sampling. Data were analyzed by using an ANOVA (a repeated measure) and a suitable post hoc test (LSD). A significant decrease was observed in lymphocytes glycogen immediately after exercise (P < 0.001). In the experimental group, increase Lymphocyte glycogen concentration (P < 0.028) than in the control group in 90 min post-exercise. Plasma glucose concentrations increased in all groups immediately after exercise (P < 0.05). Plasma insulin concentrations in both groups decreased immediately after exercise, but at 90 min after exercise, its level was significantly increased only in glucose group (P < 0.001). Our results suggested that WBTCE protocol could be affected cellular energy sources and hormonal response. Furthermore, Glucose consumption can increase the lymphocyte glycogen and better energy within the cell.

Keywords: glucose feeding, lymphocyte, Wrestling – base techniques circuit , exercise

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Authors: An-Jui. Li, Kelvin Lim, Chien-Kuo Chiu, Benson Hsiung

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This paper details the utilization of artificial intelligence (AI) in the field of slope stability whereby quick and convenient solutions can be obtained using the developed tool. The AI tool used in this study is the artificial neural network (ANN), while the slope stability analysis methods are the finite element limit analysis methods. The developed tool allows for the prompt prediction of the safety factors of fill slopes and their corresponding probability of failure (depending on the degree of variation of the soil parameters), which can give the practicing engineer a reasonable basis in their decision making. In fact, the successful use of the Extreme Learning Machine (ELM) algorithm shows that slope stability analysis is no longer confined to the conventional methods of modeling, which at times may be tedious and repetitive during the preliminary design stage where the focus is more on cost saving options rather than detailed design. Therefore, similar ANN-based tools can be further developed to assist engineers in this aspect.

Keywords: landslide, limit analysis, artificial neural network, soil properties

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Authors: Vivek Saxena, Shreshtha Saxena

Abstract:

Background: Gestational diabetes mellitus (GDM) is defined as impaired glucose tolerance first recognized during pregnancy. Uncontrolled or untreated GDM is associated with various adverse outcomes to the maternal and fetal health. Overt diabetes mellitus may also develop in such patients. It is universally accepted fact that first and foremost management to treat GDM is dietary control and lifestyle modification even before starting any oral hypoglycemic agent (OHA) or insulin. So, proper dietary management and little changes in the patient’s lifestyle are very effective for reducing her plasma glucose level. Objectives: Proper counselling of the patients and flexibility in their lifestyle and diet can effectively control the plasma glucose level in GDM patients. Methods: Total 60 GDM patients of age > 18 years were taken. We had three counselling sessions with the patient and other members of the family like husband, parents, and in-laws at different intervals, discussed their lifestyle and diet pattern, helped them to eliminate the factors those had an adverse effect on plasma glucose level and promoted them to acquire a healthy lifestyle. We have counselled the patient and her family member separately and then together also. They have explained how increased plasma glucose level can be effectively controlled with the little modification in their diet and routine activities. They were also taught to remain stress-free during their rest of antenatal period. We have excluded the patients from our study who were diabetic before pregnancy and patients with other comorbid illnesses like hypothyroidism and valvular heart disease. Results and conclusions: Results were very rewarding as patients could acquire a lifestyle of their choice. They were happy because extra pill burden was not there. All the 60 patients were normoglycemic in remaining antenatal period, 48 patients were delivered normally and 12 patients underwent cesarean section due to various reasons.Regular counselling of the patients regarding their disease and little alterations in diet and lifestyle controlled the plasma glucose level much effectively. The things were more easier and effective when we included other family members during our counselling session because they play a major role in patient’s day to day activity and influence her life.

Keywords: dietary management, gestational diabetes mellitus, impaired glucose tolerance, oral hypoglycemic agent, pregnancy

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Authors: Neha Singh, Shristi Singh

Abstract:

Accidents involving motor vehicles are more likely to cause serious injuries and fatalities. It also has a host of other perpetual issues, such as the regular loss of life and goods in accidents. To solve these issues, appropriate measures must be implemented, such as establishing an autonomous incident detection system that makes use of machine learning and artificial intelligence. In order to reduce traffic accidents, this article examines the overview of artificial intelligence and machine learning in autonomous event detection systems. The paper explores the major issues, prospective solutions, and use of artificial intelligence and machine learning in road transportation systems for minimising traffic accidents. There is a lot of discussion on additional, fresh, and developing approaches that less frequent accidents in the transportation industry. The study structured the following subtopics specifically: traffic management using machine learning and artificial intelligence and an incident detector with these two technologies. The internet of vehicles and vehicle ad hoc networks, as well as the use of wireless communication technologies like 5G wireless networks and the use of machine learning and artificial intelligence for the planning of road transportation systems, are elaborated. In addition, safety is the primary concern of road transportation. Route optimization, cargo volume forecasting, predictive fleet maintenance, real-time vehicle tracking, and traffic management, according to the review's key conclusions, are essential for ensuring the safety of road transportation networks. In addition to highlighting research trends, unanswered problems, and key research conclusions, the study also discusses the difficulties in applying artificial intelligence to road transport systems. Planning and managing the road transportation system might use the work as a resource.

Keywords: artificial intelligence, machine learning, incident detector, road transport systems, traffic management, automatic incident detection, deep learning

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Authors: S. Zhuiykov, M. Karbalaei Akbari

Abstract:

Ultra-low-level incorporation of trace impurities and dopants into two-dimensional (2D) semiconductors is a challenging step towards the development of functional electronic instruments based on 2D materials. Herein, the incorporation of sulphur atoms into 2D Ga2O3 surface oxide film of eutectic gallium-indium alloy (EGaIn) is achieved through plasma-enhanced metal-catalyst dissociation of H2S gas on EGaIn substrate. This process led to the growth of GaS crystalline nanodomains inside amorphous 2D Ga2O3 sublayer films. Consequently, 2D lateral heterophase was developed between the amorphous Ga2O3 and crystalline GaS nanodomains. The materials characterization revealed the alteration of photoluminescence (PL) characteristics and change of valence band maximum (VBM) of functionalized 2D films. The comprehensive studies by conductive atomic force microscopy (c-AFM) showed considerable enhancement of conductivity of 2D Ga2O3/GaS materials (300 times improvement) compared with that of 2D Ga2O3 film. This technique has a great potential for the fabrication of 2D metal oxide devices with tuneable electronic characteristics similar to nano junction memristors and transistors.

Keywords: 2D semiconductors, Ga₂O₃, GaS, plasma-induced functionalization

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Authors: Haolun Sun, Ping Wang, Mei Wu, Meng Zhang, Bin Hou, Ling Yang, Xiaohua Ma, Yue Hao

Abstract:

Gallium nitride (GaN) is an attractive material for next-generation power devices. It is noted that the performance of GaN-based high electron mobility transistors (HEMTs) is always limited by the self-heating effect. In response to the problem, integrating devices with polycrystalline diamond (PCD) has been demonstrated to be an efficient way to alleviate the self-heating issue of the GaN-based HEMTs. Among all the heat-spreading schemes, using PCD to cap the epitaxial layer before the HEMTs process is one of the most effective schemes. Now, the mainstream method of fabricating the PCD-capped HEMTs is to deposit the diamond heat-spreading layer on the AlGaN surface, which is covered by a thin nucleation dielectric/passivation layer. To achieve the pattern etching of the diamond heat spreader and device preparation, we selected SiN as the hard mask for diamond etching, which was deposited by plasma-enhanced chemical vapor deposition (PECVD). The conventional diamond etching method first uses F-based etching to remove the SiN from the special window region, followed by using O₂/Ar plasma to etch the diamond. However, the results of the scanning electron microscope (SEM) and focused ion beam microscopy (FIB) show that there are lots of diamond pillars on the etched diamond surface. Through our study, we found that it was caused by the high roughness of the diamond surface and the existence of the overlap between the diamond grains, which makes the etching of the SiN hard mask insufficient and leaves micro-masks on the diamond surface. Thus, a cyclic etching method was proposed to solve the problem of the residual SiN, which was left in the F-based etching. We used F-based etching during the first step to remove the SiN hard mask in the specific region; then, the O₂/Ar plasma was introduced to etch the diamond in the corresponding region. These two etching steps were set as one cycle. After the first cycle, we further used cyclic etching to clear the pillars, in which the F-based etching was used to remove the residual SiN, and then the O₂/Ar plasma was used to etch the diamond. Whether to take the next cyclic etching depends on whether there are still SiN micro-masks left. By using this method, we eventually achieved the self-terminated etching of the diamond and the smooth surface after the etching. These results demonstrate that the cyclic etching method can be successfully applied to the integrated preparation of polycrystalline diamond thin films and GaN HEMTs.

Keywords: AlGaN/GaN heterojunction, O₂/Ar plasma, cyclic etching, polycrystalline diamond

Procedia PDF Downloads 82

Authors: Sh. Sousani, Z. Shadrokh, M. Hofbauerová, J. Kollár, M. Jergel, P. Nádaždy, M. Omastová, E. Majková

Abstract:

Perovskite quantum dots (PQDs) have the potential to increase the performance of the perovskite solar cell (PSCs). The integration of PQDs into PSCs can extend the absorption range and enhance photon harvesting and device efficiency. In addition, PQDs can stabilize the device structure by passivating surface defects and traps in the perovskite layer and enhance its stability. The integration of PQDs into PSCs is strongly affected by the type of ligands on the surface of PQDs. The ligands affect the charge transport properties of PQDs, as well as the formation of well-defined interfaces and stability of PSCs. In this work, the CsPbBr₃ QDs were synthesized by the conventional hot-injection method using cesium oleate, PbBr₂ and two different ligands, namely oleic acid (OA) oleylamine (OAm) and didodecyldimethylammonium bromide (DDAB). The STEM confirmed regular shape and relatively monodisperse cubic structure with an average size of about 10-14 nm of the prepared CsPbBr₃ QDs. Further, the photoluminescent (PL) properties of the PQDs/perovskite bilayer with the ligand OA, OAm and DDAB were studied. For this purpose, ITO/PQDs as well as ITO/PQDs/MAPI perovskite structures were prepared by spin coating and the effect of the ligand and oxygen plasma treatment was analyzed. The plasma treatment of the PQDs layer could be beneficial for the deposition of the MAPI perovskite layer and the formation of a well-defined PQDs/MAPI interface. The absorption edge in UV-Vis absorption spectra for OA, OAm CsPbBr₃ QDs is placed around 513 nm (the band gap 2.38 eV); for DDAB CsPbBr₃ QDs, it is located at 490 nm (the band gap 2.33 eV). The photoluminescence (PL) spectra of CsPbBr₃ QDs show two peaks located around 514 nm (503 nm) and 718 nm (708 nm) for OA, OAm (DDAB). The peak around 500 nm corresponds to the PL of PQDs, and the peak close to 710 nm belongs to the surface states of PQDs for both types of ligands. These surface states are strongly affected by the O₃ plasma treatment. For PQDs with DDAB ligand, the O₃ exposure (5, 10, 15 s) results in the blue shift of the PQDs peak and a non-monotonous change of the amplitude of the surface states' peak. For OA, OAm ligand, the O₃ exposition did not cause any shift of the PQDs peak, and the intensity of the PL peak related to the surface states is lower by one order of magnitude in comparison with DDAB, being affected by O₃ plasma treatment. The PL results indicate the possibility of tuning the position of the PL maximum by the ligand of the PQDs. Similar behavior of the PQDs layer was observed for the ITO/QDs/MAPI samples, where an additional strong PL peak at 770 nm coming from the perovskite layer was observed; for the sample with PQDs with DDAB ligands, a small blue shift of the perovskite PL maximum was observed independently of the plasma treatment. These results suggest the possibility of affecting the PL maximum position and the surface states of the PQDs by the combination of a suitable ligand and the O₃ plasma treatment.

Keywords: perovskite quantum dots, photoluminescence, O₃ plasma., Perovskite Solar Cells

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