Search results for: artificial membranes

Authors: Amad Nasseef, Layan Zugail, Joud Musalli, Layan Shaikan

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Technology has become an essential part of our lives. We have also witnessed the significant emergence of artificial intelligence in so many areas. Throughout this research paper, the following will be discussed: an introduction on AI and Socratic application, we also did an overview on the application’s background and other similar applications, as for the methodology, we conducted a survey to collect results on users experience in using the Socratic application. The results of the survey strongly supported the usefulness and interest of users in the Socratic application. Finally, we concluded that Socratic is a meaningful tool for learning purposes due to it being supported by artificial intelligence, which made the application easy to use and familiar to users to deal with through a click of a button.

Keywords: Socratic, artificial intelligence, application, features

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Authors: Kylie Leonard

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Investment in artificial intelligence (AI) can be an attractive opportunity for business leaders as there are many easy-to-see benefits. These benefits include task completion rates, overall cost, and better forecasting. Business leaders are often unaware of the challenges that can accompany AI, such as data center costs, access to data, employee acceptance, and privacy concerns. In addition to the benefits and challenges of AI, it is important to practice AI ethics to ensure the safe creation of AI. AI ethics include aspects of algorithm bias, limits in transparency, and surveillance. To be a good business leader, it is critical to address all the considerations involving the challenges of AI and AI ethics.

Keywords: artificial intelligence, artificial intelligence ethics, business leaders, business concerns

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Authors: Priyanka Bhatnagar, Malkeshkumar Patel, Joondong Kim, Joonpyo Hong

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Artificial skin and sensory memory platforms are produced using a flexible, transparent photovoltaic (TPV) device. The TPV device is composed of a metal oxide heterojunction (nZnO/p-NiO) and transmits visible light (> 50%) while producing substantial electric power (0.5 V and 200 μA cm-2 ). This TPV device is a transparent energy interface that can be used to detect signals and propagate information without an external energy supply. The TPV artificial skin offers a temperature detection range (0 C75 C) that is wider than that of natural skin (5 C48 °C) due to the temperature-sensitive pyrocurrent from the ZnO layer. Moreover, the TPV thermoreceptor offers sensory memory of extreme thermal stimuli. Much like natural skin, artificial skin uses the nociceptor mechanism to protect tissue from harmful damage via signal amplification (hyperalgesia) and early adaption (allodynia). This demonstrates the many features of TPV artificial skin, which can sense and transmit signals and memorize information under self-operation mode. This transparent photovoltaic skin can provide sustainable energy for use in human electronics.

Keywords: transparent, photovoltaics, thermal memory, artificial skin, thermoreceptor

Procedia PDF Downloads 84

Authors: Chukwuma Mgboji

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Since the advent of Artificial Intelligence, robots have become a major stay in developing societies. Robots are deployed in Education, Health, Food and in other spheres of life. Nigeria a country in West Africa has a very low profile in the advancement of Artificial Intelligence especially in the grass roots. The benefits of Artificial intelligence are not fully maximised and harnessed. Advances in artificial intelligence are perceived as impossible or observed as irrelevant. This study seeks to ascertain the needed skills for the development of artificialintelligence amongst secondary schools in Nigeria. The study focused on South East Nigeria with Five states namely Imo, Abia, Ebonyi, Anambra and Enugu. The sample size is 1000 students drawn from Five Government owned Universities offering Computer Science, Computer Education, Electronics Engineering across the Five South East states. Survey method was used to solicit responses from respondents. The findings from the study identified mathematical skills, analytical skills, problem solving skills, computing skills, programming skills, algorithm skills amongst others. The result of this study to the best of the author’s knowledge will be highly beneficial to all stakeholders involved in the advancements and development of artificial intelligence.

Keywords: artificial intelligence, secondary school, robotics, skills

Procedia PDF Downloads 115

Authors: Yiqiao Yin

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Many scholars and educators have dedicated their lives in K12 education system and there has been an exploding amount of attention to implement technical foundations for Artificial Intelligence Education for high school and precollege level students. This paper focuses on the development and use of resources to support K-12 education in Artificial Intelligence (AI). The author and his team have more than three years of experience coaching students from pre-college level age from 15 to 18. This paper is a culmination of the experience and proposed online tools, software demos, and structured activities for high school students. The paper also addresses a portfolio of AI concepts as well as the expected learning outcomes. All resources are provided with online videos and Github repositories for immediate use.

Keywords: K12 education, AI4ALL, pre-college education, pre-college AI

Procedia PDF Downloads 104

Authors: Boyu Li

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Mixed matrix membranes (MMMs), as a separation technology, can improve CO₂ recycling efficiency and reduce the environmental impacts associated with huge emissions. Nevertheless, many challenges must be overcome to design excellent selectivity and permeability performance MMMs. Herein, this work demonstrates the design of nano-scale GNPs (Cu-BDC@PEG) with strong compatibility and high free friction volume (FFV) is an effective way to construct non-interfacial voids MMMs with a desirable combination of selectivity and permeability. Notably, the FFV boosted thanks to the chain length and shape of the GNPs. With this, the permeability and selectivity of Cu-BDC@PEG/PVDF MMMs had also been significantly improved. As such, compatible Cu-BDC@PEG proves very efficient for resolving challenges of MMMs with poor compatibility on the basis of the interfacial defect. Poly (Ethylene Glycol) (PEG) with oxygen groups can be finely coordinated with Cu-MOFs to disperse Cu-BDC@PEG homogenously and form hydrogen bonds with matrix to achieve continuous phase. The resultant MMMs exhibited a simultaneous enhancement of gas permeability (853.1 Barrer) and ideal CO₂/N selectivity (41.7), which has surpassed Robenson's upper bound. Moreover, Cu-BDC@PEG/PVDF has a high-temperature resistance and a long time sustainably. This attractive separation performance of Cu-BDC@PEG/PVDF offered an exciting platform for the development of composite membranes for sustainable CO₂ separations.

Keywords: metal organic framework, CO₂ separation, mixed matrix membrane, polymer

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Authors: Artur Matuck, Guilherme F. Nobre

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Machines can be either tool, media, or social agents. Advances in technology have been delivering machines capable of autonomous expression, both through communication and art. This paper deals with models (theoretical approach) and experiments (applied approach) related to artificial agents. On one hand it traces how social sciences' scholars have worked with topics such as text automatization, man-machine writing cooperation, and communication. On the other hand it covers how computer sciences' scholars have built communicative and artistic machines, including the programming of creativity. The aim is to present a brief survey on artificially intelligent communicators and artificially creative writers, and provide the basis to understand the meta-authorship and also to new and further man-machine co-authorship.

Keywords: artificial communication, artificial creativity, artificial writers, meta-authorship, robotic art

Procedia PDF Downloads 265

Authors: Lipeng Zhang, Limei Li, Yanming Pearl Zhang

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This paper takes a philosophical view as axiom, and reveals the relationship between information theory and Natural Intelligence and Artificial Intelligence under real world conditions. This paper also derives the relationship between natural intelligence and nature. According to communication principle of information theory, Natural Intelligence can be divided into real part and virtual part. Based on information theory principle that Information does not increase, the restriction mechanism of Natural Intelligence creativity is conducted. The restriction mechanism of creativity reveals the limit of natural intelligence and artificial intelligence. The paper provides a new angle to observe natural intelligence and artificial intelligence.

Keywords: natural intelligence, artificial intelligence, creativity, information theory, restriction of creativity

Procedia PDF Downloads 344

Authors: Jong-Ho Moon, Dong-Ho Lee, Hyunuk Kim, Young Cheol Park, Jong-Seop Lee, Jae-deok Jeon, Hyung-Keun Lee

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A novel membrane reactor process for DMC synthesis from carbon dioxide has been developing in Korea Institute of Energy Research. The scheme of direct synthesis of DMC from CO₂ and Methanol is 'CO₂ + 2MeOH ↔ DMC + H₂O'. Among them, reactants are CO₂ and MeOH, product is DMC, and byproduct is H₂O (water). According to Le Chatelier’s principle, removing byproduct (water) can shift the reaction equilibrium to the right (DMC production). The main purpose of this process is removing water during the reaction. For efficient in situ water removal (dehydration) and DMC separation, zeolite 4A membranes with very small pore diameter and hydrophilicity were introduced. In this study, pervaporation performances of binary and ternary DMC / methanol / water mixtures were evaluated.

Keywords: dimehtyl carbonate, methanol, water, zeolite membrane, pervaporation

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Authors: W. H. Zheng, J. Li, F. J. Hong

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Thin liquid film evaporation in ultrathin nanoporous membranes, which reduce the viscous resistance while still maintaining high capillary pressure and efficient liquid delivery, is a promising thermal management approach for high-power electronic devices cooling. Given the challenges and technical limitations of experimental studies for accurate interface temperature sensing, complex manufacturing process, and short duration of membranes, a dimensionless lattice Boltzmann method capable of restoring thermophysical properties of working fluid is particularly derived. The evaporation of R134a to its pure vapour ambient in nanoporous membranes with the pore diameter of 80nm, thickness of 472nm, and three porosities of 0.25, 0.33 and 0.5 are numerically simulated. The numerical results indicate that the highest heat transfer coefficient is about 1740kW/m²·K; the highest heat flux is about 1.49kW/cm² with only about the wall superheat of 8.59K in the case of porosity equals to 0.5. The dissipated heat flux scaled with porosity because of the increasing effective evaporative area. Additionally, the self-regulation of the shape and curvature of the meniscus under different operating conditions is also observed. This work shows a promising approach to forecast the membrane performance for different geometry and working fluids.

Keywords: high heat flux, ultrathin nanoporous membrane, thin film evaporation, lattice Boltzmann method

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Authors: M. N. Abu Seman, L. M. Kei, M. A. Yusoff

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Forward Osmosis (FO) polyamide thin-film composite membranes have been prepared by inter facial polymerization using commercial UF polyethersulfone as membrane support. Different inter facial polymerization times (10s, 30s and 60s) in the organic solution containing trimesoyl chloride (TMC) at constant m-phenylenediamine (MPD) concentration (2% w/v) were studied. The synthesized polyamide membranes then tested for treatment of natural organic matter (NOM) and compared to commercial Cellulose TriAcetate (CTA) membrane. It was found that membrane prepared with higher reaction time (30 s and 60 s) exhibited better membrane performance (flux and humic acid removal) over commercial CTA membrane.

Keywords: cellulose triacetate, forward osmosis, humic acid, polyamide

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Authors: O. P. Oladipo, O. A. Falode

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The determination of Recovery Factor is of great importance to the reservoir engineer since it relates reserves to the initial oil in place. Reserves are the producible portion of reservoirs and give an indication of the profitability of a field Development. The core objective of this project is to develop an artificial neural network model using selected reservoir data to predict Recovery Factors (RF) of hydrocarbon reservoirs and compare the model with a couple of the existing correlations. The type of Artificial Neural Network model developed was the Single Layer Feed Forward Network. MATLAB was used as the network simulator and the network was trained using the supervised learning method, Afterwards, the network was tested with input data never seen by the network. The results of the predicted values of the recovery factors of the Artificial Neural Network Model, API Correlation for water drive reservoirs (Sands and Sandstones) and Guthrie and Greenberger Correlation Equation were obtained and compared. It was noted that the coefficient of correlation of the Artificial Neural Network Model was higher than the coefficient of correlations of the other two correlation equations, thus making it a more accurate prediction tool. The Artificial Neural Network, because of its accurate prediction ability is helpful in the correct prediction of hydrocarbon reservoir factors. Artificial Neural Network could be applied in the prediction of other Petroleum Engineering parameters because it is able to recognise complex patterns of data set and establish a relationship between them.

Keywords: recovery factor, reservoir, reserves, artificial neural network, hydrocarbon, MATLAB, API, Guthrie, Greenberger

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Authors: Reza Dinarvand, Mahdi Sadeghian, Somaye Sadeghian

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Prediction of the ultimate bearing capacity of piles (Qu) is one of the basic issues in geotechnical engineering. So far, several methods have been used to estimate Qu, including the recently developed artificial intelligence methods. In recent years, optimization algorithms have been used to minimize artificial network errors, such as colony algorithms, genetic algorithms, imperialist competitive algorithms, and so on. In the present research, artificial neural networks based on colonial competition algorithm (ANN-ICA) were used, and their results were compared with other methods. The results of laboratory tests of short piles in clayey soils with parameters such as pile diameter, pile buried length, eccentricity of load and undrained shear resistance of soil were used for modeling and evaluation. The results showed that ICA-based artificial neural networks predicted lateral bearing capacity of short piles with a correlation coefficient of 0.9865 for training data and 0.975 for test data. Furthermore, the results of the model indicated the superiority of ICA-based artificial neural networks compared to back-propagation artificial neural networks as well as the Broms and Hansen methods.

Keywords: artificial neural network, clayey soil, imperialist competition algorithm, lateral bearing capacity, short pile

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Authors: Hafiz Arbab Sakandar, Sabahat Yaqub, Ayesha Sameen, Muhammad Imran, Sarfraz Ahmad

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Yoghurt is one of the famous nutritious fermented milk products which have myriad of positive health effects on human beings and curable against different intestinal diseases. This research was conducted to observe effects of different artificial sweeteners on the quality parameters of yoghurt with relation to storage. Some people are allergic to natural sweeteners so artificial sweetener will be helpful for them. Physical-chemical, Microbiology and various sensory evaluation tests were carried out with the interval of 7, 14, 21, and 28 days. It was outcome from this study that addition of artificial sweeteners in yoghurt has shown much harmful effects on the yoghurt microorganisms and other physicochemical parameters from quality point of view. Best results for acceptance were obtained when aspartame was added in yoghurt at level of 0.022 percent. In addition, growth of beneficial microorganisms in yoghurt was also improved as well as other sensory attributes were enhanced by the addition of aspartame.

Keywords: yoghurt, artificial sweetener, storage, quality parameters

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Authors: Khaled M. Alhawiti

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This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: speech recognition, acoustic phonetic, artificial intelligence, hidden markov models (HMM), statistical models of speech recognition, human machine performance

Procedia PDF Downloads 445

Authors: Siti Aslamyah, Yushinta Fujaya, Okto Rimaldi

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One of the problems faced in the crab hatchery operations is the reliance on the use of natural feed. This study aims to analyze the response of larval development and determine the initial stages crab larvae begin to fully able to accept artificial feeding predigest with the help of probiotic Bacillus sp. The experiment was conducted in June 2014 through July 2014 at the location of the scale backyard hatcheries, Bojo village Mallusettasi sub-district, district Barru. This study was conducted in two stages larval rearing. The first stage is designed in a completely randomized design with 5 treatments and each with 3 repetitions, ie, without the use of artificial feeding; predigest feed given from zoea 1 - megalopa; predigest feed given since zoea 2 - megalopa; predigest feed given from zoea 3 - megalopa; and feed predigest given since zoea 4 - megalopa. The second stage of the two treatments, i.e. comparing artificial feeding without and with predigest. The results showed that the artificial feeding predigest able to replace the use of natural feed started zoea 3 generated based on the survival rate. Artificial feeding predigest provide a higher survival rate (16%) compared to artificial diets without predigest only 10.8%. However, feed predigest not give a different effect on the rate of development of stadia. Cell activity in larvae that received artificial feed predigest higher with RNA-DNA ratio of 8.88 compared with no predigest only 5:36. This research is very valuable information for crab hatchery hatchery scale households have limitations in preparing natural food.

Keywords: artificial feeding, development of stadia, larvae Portunus pelagicus, predigest

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Authors: Asmaa Selim, Peter Mizsey

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Bio-ethanol is considered of higher potential as a green renewable energy source owing to its environmental benefits and its high efficiency. In the present study, silver nanoparticles were in-situ generated in a poly (vinyl alcohol) in order to improve its potentials for pervaporation of ethanol-water mixture using solution-casting. Effect of silver content on the pervaporation separation index and the enrichment factor of the membrane at 15 percentage mass water at 40ᵒC was reported. Pervaporation data for nanocomposite membranes showed around 100% increase in the water permeance values while the intrinsic selectivity decreased. The water permeances of origin crosslinked PVA membrane, and the 2.5% silver loaded PVA membrane are 26.65 and 70.45 (g/m².kPa.h) respectively. The values of total flux and water flux are closed to each other, indicating that membranes could be effectively used to break the azeotropic point of ethanol-water. Effect of temperature on the pervaporation performance, permeation parameter and diffusion coefficient of both water and ethanol was discussed. The negative heat of sorption ∆Hs values calculated on the basis of the estimated Arrhenius activation energy values indicating that the sorption process was controlled by Langmuir’s mode. The overall results showed that the membrane containing 0.5 mass percentage of Ag salt exhibited excellent PV performance.

Keywords: bio-ethanol, diffusion coefficient, nanocomposite, pervaporation, poly (vinyl alcohol), silver nanoparticles

Procedia PDF Downloads 138

Authors: Nouf Nasser, Nada Alotaibi, Jazzal Kandiel

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This research study is about the use of artificial intelligence in PhotoRoom. When an individual selects a photo, PhotoRoom automagically removes or separates the background from other parts of the photo through the use of artificial intelligence. This will allow an individual to select their desired background and edit it as they wish. The methodology used was an observation, where various reviews and parts of the app were observed. The review section's findings showed that many people actually like the app, and some even rated it five stars. The conclusion was that PhotoRoom is one of the best photo editing apps due to its speed and accuracy in removing backgrounds.

Keywords: removing background, app, artificial intelligence, machine learning

Procedia PDF Downloads 169

Authors: Rachid El Aidani, Phuong Nguyen-Tri, Toan Vu-Khanh

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This study intends to show the influence of the hydrolytic degradation on the properties of the e-PTFE/NOMEX® membranes used in fire-protective clothing. The modification of water vapour permeability, morphology and chemical structure was examined by MOCON Permatran, electron microscopy scanning (SEM), and ATR-FTIR, respectively. A decrease in permeability to water vapour of the aged samples was observed following closure of transpiration pores. Analysis of fiber morphology indicates the appearance of defects at the fibers surface with the presence of micro cavities as well as the of fibrils. ATR-FTIR analysis reveals the presence of a new absorption band attributed to carboxylic acid terminal groups generated during the amide bond hydrolysis.

Keywords: hydrolytic ageing, moisture membrane, water vapor permeability, morphology

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Authors: Chinedu Peter, Dashrath Singh

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Membrane computing is a computability model which abstracts its structures and functions from the biological cell. The main ingredient of membrane computing is the notion of a membrane structure, which consists of several cell-like membranes recurrently placed inside a unique skin membrane. The emergence of several variants of membrane computing gives rise to the notion of a P system. The paper presents a variant of P systems for arithmetic operations on non-negative integers based on the weak priorities for rule application. Consequently, we obtain deterministic P systems. Two membranes suffice. There are at most four objects for multiplication and five objects for division throughout the computation processes. The model is simple and has a potential for possible extension to non-negative integers and real numbers in general.

Keywords: P system, binary operation, determinism, weak rule priority

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Authors: Abhishek Soti, Aditya Sharma, Akhilendra Bhushan Gupta

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Fouled reverse osmosis membranes are primarily characterized by Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectrometer (EDS) for a detailed investigation of foulants; however, this has severe limitations on several accounts. Apart from inaccuracy in spectral properties and inevitable interferences and interactions between sample and instrument, misidentification of elements due to overlapping peaks is a significant drawback of EDS. This paper discusses this limitation by analyzing fouled polyamide RO membranes derived from community RO plants of Rajasthan treating brackish water via a combination of results obtained from EDS and Raman spectroscopy and cross corroborating with ICP-MS analysis of water samples prepared by dissolving the deposited salts. The anomalous behavior of different morphic forms of CaCO₃ in aqueous suspensions tends to introduce false reporting of the presence of certain heavy metals and rare earth metals in the scales of the fouled RO membranes used for treating brackish groundwater when analyzed using the commonly adopted techniques like SEM-EDS or Raman spectrometry. Peaks of CaCO₃ reflected in EDS spectra of the membrane were found to be misinterpreted as Scandium due to the automatic assignment of elements by the software. Similarly, the morphic forms merged with the dominant peak of CaCO₃ might be reflected as a single peak of Molybdenum in the Raman spectrum. A subsequent ICP-MS analysis of the deposited salts showed that both Sc and Mo were below detectable levels. It is always essential to cross-confirm the results through a destructive analysis method to avoid such interferences. It is further recommended to study different morphic forms of CaCO₃ scales, as they exhibit anomalous properties like reverse solubility with temperature and hence altered precipitation tendencies, for an accurate description of the composition of scales, which is vital for the smooth functioning of RO systems.

Keywords: reverse osmosis, foulant analysis, groundwater, EDS, artifacts

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Authors: K. A. Laptinskiy, S. A. Burikov, A. M. Vervald, S. A. Dolenko, T. A. Dolenko

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The article presents the results of the application of artificial neural networks to separate the fluorescent contribution of nanodiamonds used as biomarkers, adsorbents and carriers of drugs in biomedicine, from a fluorescent background of own biological fluorophores. The principal possibility of solving this problem is shown. Use of neural network architecture let to detect fluorescence of nanodiamonds against the background autofluorescence of egg white with high accuracy - better than 3 ug/ml.

Keywords: artificial neural networks, fluorescence, data aggregation, biomarkers

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Authors: Albatool Al Abdulwahid, Bayan Shakally, Mariam Mohamed, Wed Almokri

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Artificial intelligence has infiltrated every part of our life and every field we can think of. With technical developments, artificial intelligence applications are becoming more prevalent. We chose ELSA speak because it is a magnificent example of Artificial intelligent applications, ELSA speak is a smartphone application that is free to download on both IOS and Android smartphones. ELSA speak utilizes artificial intelligence to help non-native English speakers pronounce words and phrases similar to a native speaker, as well as enhance their English skills. It employs speech-recognition technology that aids the application to excel the pronunciation of its users. This remarkable feature distinguishes ELSA from other voice recognition algorithms and increase the efficiency of the application. This study focused on evaluating ELSA speak application, by testing the degree of effectiveness based on survey questions. The results of the questionnaire were variable. The generality of the participants strongly agreed that ELSA has helped them enhance their pronunciation skills. However, a few participants were unconfident about the application’s ability to assist them in their learning journey.

Keywords: ELSA speak application, artificial intelligence, speech-recognition technology, language learning, english pronunciation

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Authors: Meshandren Naidoo

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An artificial intelligence (AI) system named DABUS 2021 made headlines when it became the very first AI system to be listed in a patent which was then granted by the South African patent office. This grant raised much criticism. The question that this research intends to answer is (1) whether, in South African patent law, an AI can be an inventor. This research finds that despite South African law not recognizing an AI as a legal person and despite the legislation not explicitly allowing AI to be inventors, a legal interpretative exercise would allow AI inventorship.

Keywords: artificial intelligence, creativity, innovation, law

Procedia PDF Downloads 102

Authors: Oluwatosin Olofintoye, Josiah Adeyemo, Gbemileke Shomade

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The relationship between rainfall and runoff is an important issue in surface water hydrology therefore the understanding and development of accurate rainfall-runoff models and their applications in water resources planning, management and operation are of paramount importance in hydrological studies. This paper reviews some of the previous works on the rainfall-runoff process modeling. The hydrologic applications of conceptual models and artificial neural networks (ANNs) for the precipitation-runoff process modeling were studied. Gradient training methods such as error back-propagation (BP) and evolutionary algorithms (EAs) are discussed in relation to the training of artificial neural networks and it is shown that application of EAs to artificial neural networks training could be an alternative to other training methods. Therefore, further research interest to exploit the abundant expert knowledge in the area of artificial intelligence for the solution of hydrologic and water resources planning and management problems is needed.

Keywords: artificial intelligence, artificial neural networks, evolutionary algorithms, gradient training method, rainfall-runoff model

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Authors: Vishnu Pratap Singh Kirar

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The main aim of the communication system is to achieve maximum performance. In cognitive radio, any user or transceiver have the ability to sense best suitable channel, while the channel is not in use. It means an unlicensed user can share the spectrum of licensed user without any interference. Though the spectrum sensing consumes a large amount of energy and it can reduce by applying various artificial intelligent methods for determining proper spectrum holes. It also increases the efficiency of Cognitive Radio Network (CRN). In this survey paper, we discuss the use of different learning models and implementation of Artificial Neural Network (ANN) to increase the learning and decision-making capacity of CRN without affecting bandwidth, cost and signal rate.

Keywords: artificial neural network, cognitive radio, cognitive radio networks, back propagation, spectrum sensing

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Authors: M. Naidoo

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Artificial intelligence often requires large amounts of good quality data. Within important fields, such as healthcare, the training of AI systems predominately relies on health and personal data; however, the usage of this data is complicated by various layers of law and ethics that seek to protect individuals’ privacy rights. This research seeks to establish the challenges AI and data sciences pose to (i) informational rights, (ii) privacy rights, and (iii) data protection. To solve some of the issues presented, various methods are suggested, such as embedding values in technological development, proper balancing of rights and interests, and others.

Keywords: artificial intelligence, data science, law, policy

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Authors: Tarek Aboueldahab, Amin Mohamed Nassar

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Wind energy is a fluctuating energy source unlike conventional power plants, thus, it is necessary to accurately predict short term wind speed to integrate wind energy in the electricity supply structure. To do so, we present a hybrid artificial intelligence model of short term wind speed prediction based on passive aggregation of the particle swarm optimization and neural networks. As a result, improvement of the prediction accuracy is obviously obtained compared to the standard artificial intelligence method.

Keywords: artificial intelligence, neural networks, particle swarm optimization, passive aggregation, wind speed prediction

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Authors: Diego De Almeida Pereira, Diana Borchenko

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Artificial neural networks are used for many applications as they are able to learn complex nonlinear relationships between input and output data. As the number of neurons and layers in a neural network increases, it is possible to represent more complex behaviors. The present study proposes that artificial neural networks are a valuable tool for architecture and engineering professionals concerned with understanding how buildings influence human and social well-being based on theories of environmental psychology.

Keywords: environmental psychology, architecture, neural networks, human and social well-being

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Authors: Nety Trisnawaty, Mirna Febriani

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The use of stainless steel wires in the field of dentistry is widely used, especially for orthodontic and prosthodontic treatment using stainless steel wire. The oral cavity is the ideal environment for corrosion, which can be caused by saliva. Prevention of corrosion on stainless steel wires can be done by using an organic or non-organic corrosion inhibitor. One of the organic inhibitors that can be used to prevent corrosion is black tea leaves extracts. To explain the comparison of chromium ions release for stainlees steel between artificial saliva and black tea leaves extracts. In this research we used artificial saliva, black tea leaves extracts, stainless steel wire and using Atomic Absorption Spectrophometric testing machine. The samples were soaked for 1, 3, 7 and 14 days in the artificial saliva and black tea leaves extracts. The results showed the difference of chromium ion release soaked in artificial saliva and black tea leaves extracts on days 1, 3, 7 and 14. Statistically, calculation with independent T-test with p < 0,05 showed a significant difference. The longer the duration of days, the more ion chromium were released. The conclusion of this study shows that black tea leaves extracts can inhibit the corrosion rate of stainless steel wires.

Keywords: chromium ion, stainless steel, artificial saliva, black tea leaves extracts

Procedia PDF Downloads 245