Search results for: animal artificial insemination

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 recognising 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, intellectual property, inventorship, patents

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Authors: R. R. Govind

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In the digital age, artificial intelligence (AI) is having a significant impact on the rapid changes that cities are experiencing. This study explores the profound impact of AI on urban morphology, especially with regard to promoting friendly design choices. It addresses a significant research gap by examining the real-world effects of integrating AI into urban design and management. The main objective is to outline a framework for integrating AI to transform urban settings. The study employs an urban design framework to effectively navigate complicated urban environments, emphasize the need for urban management, and provide efficient planning and design strategies. Taking Gangtok's informal settlements as a focal point, the study employs AI methodologies such as machine learning, predictive analytics, and generative AI to tackle issues of 'urban informality'. The insights garnered not only offer valuable perspectives but also unveil AI's transformative potential in addressing contemporary urban challenges.

Keywords: urban design, artificial intelligence, urban challenges, machine learning, urban informality

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Authors: Dona Abdulwassi, Dhaee Dahlawi, Yara Zainy, Leen Joharji

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The relationship between Netflix and artificial intelligence is discussed in this paper. Netflix uses the most effective and efficient approaches to apply artificial intelligence, machine learning, and data science. Netflix employs the personalization tool for their users, recommending or suggesting shows based on what those users have already watched. The researchers conducted an experiment to learn more about how Netflix is used and how AI affects the user experience. The main conclusions of this study are that Netflix has a wide range of AI features, most users are happy with their Netflix subscriptions, and the majority prefer Netflix to alternative apps.

Keywords: easy accessibility, recommends, accuracy, privacy

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Authors: Basma Abdel Mohsen Al-Sheikh

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This study aimed to create textile designs inspired by Najdi Al-Sadu art, with the objective of highlighting Saudi identity and heritage. The research proposed clothing designs for women and children, utilizing textiles inspired by Najdi Al-Sadu art, and incorporated artificial intelligence techniques in the design process. The study employed a descriptive-analytical approach to describe Najdi Al-Sadu, and an experimental method involving the creation of textile designs inspired by Al-Sadu. The study sample consisted of 33 participants, including experts in the fashion and textile industry, fashion designers, lecturers, professors, and postgraduate students from King Abdulaziz University. A questionnaire was used as a tool to gather opinions regarding the proposed designs. The results demonstrated a clear acceptance of the designs inspired by Najdi Al-Sadu and incorporating artificial intelligence, with approval rates ranging from 22% to 81% across different designs. The study concluded that artificial intelligence applications have a significant impact on fashion design, particularly in the integration of Al-Sadu art. The findings also indicated a positive reception of the designs in terms of their aesthetic and functional aspects, although individual preferences led to some variations in opinions. The results highlighted a demand for designs that combine heritage and modern fashion, striking a balance between authenticity and contemporary style. The study recommended that designers continue to explore ways to integrate cultural heritage, such as Al-Sadu art, with contemporary design elements to achieve this balance. Furthermore, it emphasized the importance of enhancing the aesthetic and functional aspects of designs, taking into consideration the preferences of the target market and customer expectations. The effective utilization of artificial intelligence was also emphasized to improve design processes, expand creative possibilities, and foster innovation and authenticity.

Keywords: Najdi Al-Sadu art, artificial intelligence, women's and children's fashion, clothing designs

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Authors: Abdelazziz Aouiche, El Moundher Aouiche, Mouhamed Salah Soudani

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Renewable energy sources now significantly contribute to the replacement of traditional fossil fuel energy sources. One of the most potent types of renewable energy that has developed quickly in recent years is photovoltaic energy. We all know that solar energy, which is sustainable and non-depleting, is the best knowledge form of energy that we have at our disposal. Due to changing weather conditions, the primary drawback of conventional solar PV cells is their inability to track their maximum power point. In this study, we apply artificial neural networks (ANN) to automatically track and measure the maximum power point (MPP) of solar panels. In MATLAB, the complete system is simulated, and the results are adjusted for the external environment. The results are better performance than traditional MPPT methods and the results demonstrate the advantages of using neural networks in solar PV systems.

Keywords: modeling, photovoltaic panel, artificial neural networks, maximum power point tracking

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Authors: W. Walke, J. Przondziono, K. Nowińska

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The study comprises evaluation of suitability of passive layer created on the surface of AISI 316L stainless steel for products that are intended to have contact with blood. For that purpose, prior to and after chemical passivation, samples were subject to 7 day exposure in artificial plasma at the temperature of T=37°C. Next, tests of metallic ions infiltration from the surface to the solution were performed. The tests were performed with application of spectrometer JY 2000, by Yobin – Yvon, employing Inductively Coupled Plasma Atomic Emission Spectrometry (ICP-AES). In order to characterize physical and chemical features of electrochemical processes taking place during exposure of samples to artificial plasma, tests with application of electrochemical impedance spectroscopy were suggested. The tests were performed with application of measuring unit equipped with potentiostat PGSTAT 302n with an attachment for impedance tests FRA2. Measurements were made in the environment simulating human blood at the temperature of T=37°C. Performed tests proved that application of chemical passivation process for AISI 316L stainless steel used for production of goods intended to have contact with blood is well-grounded and useful in order to improve safety of their usage.

Keywords: AISI 316L stainless steel, chemical passivation, artificial plasma, ions infiltration, EIS

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Authors: Maamar Ali Saud Al Tobi, Geraint Bevan, K. P. Ramachandran, Peter Wallace, David Harrison

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Centrifugal pumps are complex machines which can experience different types of fault. Condition monitoring can be used in centrifugal pump fault detection through vibration analysis for mechanical and hydraulic forces. Vibration analysis methods have the potential to be combined with artificial intelligence systems where an automatic diagnostic method can be approached. An automatic fault diagnosis approach could be a good option to minimize human error and to provide a precise machine fault classification. This work aims to introduce an approach to centrifugal pump fault diagnosis based on artificial intelligence and genetic algorithm systems. An overview of the future works, research methodology and proposed experimental setup is presented and discussed. The expected results and outcomes based on the experimental work are illustrated.

Keywords: centrifugal pump setup, vibration analysis, artificial intelligence, genetic algorithm

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Authors: Ann Enright

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More than ever, animal shelters need to identify ways to reduce the number of animals entering shelter facilities and the incidence of euthanasia. Managing animal overpopulation using euthanasia can have detrimental health and emotional consequences for the shelter staff involved. There are also community expectations with moral and financial implications to consider. To achieve the goals of reducing animal intake and the incidence of euthanasia, shelter best practice involves combining programs, procedures and partnerships to increase live release rates (LRR), reduce the incidence of disease, length of stay (LOS) and shelter intake whilst overall remaining financially viable. Analysing daily processes, tracking outcomes and implementing simple strategies enabled shelter staff to more effectively focus their efforts and achieve amazing results. The objective of this retrospective study was to assess the effect of implementing the capacity for care (C4C) management model. Data focusing on the average daily number of animals on site for a two year period (2016 – 2017) was exported from a shelter management system, Customer Logic (CL) Vet to Excel for manipulation and comparison. Following the implementation of C4C practices the average daily number of animals on site was reduced by >50%, (2016 average 103 compared to 2017 average 49), average LOS reduced by 50% from 8 weeks to 4 weeks and incidence of disease reduced from ≥ 70% to less than 2% of the cats on site at the completion of the study. The total number of stray cats entering the shelter due to council contracts reduced by 50% (486 to 248). Improved cat outcomes were attributed to strategies that increased adoptions and reduced euthanasia of poorly socialized cats, including foster programs. To continue to achieve improvements in LRR and LOS, strategies to decrease intake further would be beneficial, for example, targeted sterilisation programs. In conclusion, the study highlighted the benefits of using C4C as a management tool, delivering a significant reduction in animal intake and euthanasia with positive emotional, financial and community outcomes.

Keywords: animal welfare, capacity for care, cat, euthanasia, length of stay, managed intake, shelter

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Authors: Abhivardhan, Ritu Agarwal

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The role of entrepreneurial ethics is connected with materializing the core components of human life, and the flexible and gullible attributions dominate the materialization of human lifestyle and outreach in the age of the internet and globalization. One of the key bi-products of the age of information – Artificial Intelligence has become a relevant mechanism to materialize and understand human empathy and originality via various algorithmic policing methodologies with specific intricacies. Since it has a special connection with ethnocentrism – it has the potential to influence the approach of international law and politics owed to the rise of and approach towards perception and communication via populism in progressive and third world countries. The paper argues about the cultural persona of artificial intelligence, and its ontological resemblance in human life is connected with the ethnocentric treatment of cyberspace, with an analysis of the influence of the ethics of entrepreneurship in international politics. The paper further provides an analysis of fake news and misinformation as the sub-strata of communication strategies involving populism determined as a communication strategy and about the legal case of constitutional redemption in recent legislative developments in Europe, the U.S, and Asia with reference to certain important strategies, policy documentation, declarations, and legal instruments. The paper concludes that the capillaries of the anthropomorphic developments of cultural perception via towards artificial intelligence have a hidden and unstable connection with the common approach of entrepreneurial ethics, which influences populism to disrupt the peaceful order of international politics via some minor backlashes in the technological, legal and social realm of human life. Suggestions with the conclusion are hereby provided.

Keywords: ethnocentrism, perception politics, populism, international law, slacktivism, artificial intelligence ethics, enculturation

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Authors: I. A. Farhat

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The dynamic economic dispatch (DED) problem is one of the complex, constrained optimization problems that have nonlinear, con-convex and non-smooth objective functions. The purpose of the DED is to determine the optimal economic operation of the committed units while meeting the load demand. Associated to this constrained problem there exist highly nonlinear and non-convex practical constraints to be satisfied. Therefore, classical and derivative-based methods are likely not to converge to an optimal or near optimal solution to such a dynamic and large-scale problem. In this paper, an Artificial Immune System technique (AIS) is implemented and applied to solve the DED problem considering the transmission power losses and the valve-point effects in addition to the other operational constraints. To demonstrate the effectiveness of the proposed technique, two case studies are considered. The results obtained using the AIS are compared to those obtained by other methods reported in the literature and found better.

Keywords: artificial immune system, dynamic economic dispatch, optimal economic operation, large-scale problem

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Authors: Kevin Yeo, Christine Hall, Babinchak Tim

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BAT® [Botulism Antitoxin Heptavalent (A,B,C,D,E,F,G)-(Equine)] anti-toxin is a mixture of equine immune globulin fragments indicated for the treatment of symptomatic botulism in adult and pediatric patients. The effectiveness of BAT anti-toxin is based on efficacy studies conducted in animal models. A general explanation of the pivotal animal studies, post market surveillance and outcomes of an observational patient registry for patients treated with BAT product distributed in the USA is briefly discussed. Overall it took 20 animal studies for two well-designed and appropriately powered pivotal efficacy studies – one in which the effectiveness of BAT was assessed against all 7 serotypes in the guinea pig, and the other where efficacy is confirmed in the Rhesus macaque using Serotype A. Clinical Experience for BAT to date involves approximately 600 adult and pediatric patients with suspected botulism. In pre-licensure, patient data was recorded under the US CDC expanded access program (259 adult and pediatric patients between 10 days to 88 years of age). In post licensure, greater than 350 patients to date have received BAT and been followed up by enhanced expanded access program. The analysis of the post market surveillance data provided a unique opportunity to demonstrate clinical benefit in the field study required by the animal rule. While the animal rule is applied because human efficacy studies are not ethical or feasible, a post-marketing requirement is to conduct a study to evaluate safety and clinical benefit when circumstances arise and demonstrate the favourable benefit-risk profile that supported licensure.

Keywords: botulism, threat, clinical benefit, observational patient registry

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Authors: M. Naidoo

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AI in healthcare can have a massive positive effect in low-resource states like South Africa, where patients outnumber personnel greatly. However, the complexity and ‘black box’ aspects of these technologies pose challenges for the liability regimes of states. This is currently being discussed at the international level. This research finds that within the South African medical negligence context, the current common law fault-based inquiry proves to be wholly inadequate for patient redress. As a solution to this, this research paper culminates in legal reform recommendations designed to solve these issues.

Keywords: artificial intelligence, law, liability, policy

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Authors: Keunho Park, Sunghwan Jeong

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The 4th Industrial Revolution, the next-generation industrial revolution, which is made up of convergence of information and communication technology (ICT), is no exception to the livestock industry, and various studies are being conducted to apply the livestock smart farm. In order to monitor livestock using sensors, it is necessary to drill holes in the organs such as the nose, ears, and even the stomach of the livestock to wear or insert the sensor into the livestock. This increases the stress of livestock, which in turn lowers the quality of livestock products or raises the issue of animal ethics, which has become a major issue in recent years. In this paper, we conducted a study to monitor livestock activity based on vision technology, effectively monitoring livestock activity without increasing animal stress and violating animal ethics. The movement rate was calculated based on the difference images between the frames, and the livestock activity was evaluated. As a result, the average F1-score was 96.67.

Keywords: barn monitoring, livestock, machine vision, smart farm

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Authors: Amira Bousselmi

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This article presents a PIFA antenna designed for geolocation applications (GNSS) operating on 1.278 GHz, 2.8 GHz, 5.7 GHz and 10 GHz. To improve the performance of the antenna, an artificial magnetic conductor structure (AMC) was used. Adding the antenna with AMC resulted in a measured gain of 4.78 dBi. The results of simulations and measurements are presented. CST Microwave Studio is used to design and compare antenna performance. An antenna design methodology, design and characterization of the AMC surface are described as well as the simulated and measured performances of the AMC antenna are then discussed. Finally, in Section V, there is a conclusion.

Keywords: antenna multiband, global navigation system, AMC, Galeleo

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Authors: Safayat Ali Shaikh

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Software has been developed for optimal cropping pattern in an irrigation project considering land constraint, water availability constraint and pick up flow constraint using modified Simplex Algorithm. Artificial Neural Network Models (ANN) have been developed to predict rainfall. AR (1) model used to generate 1000 years rainfall data to train the ANN. Simulation has been done with expected rainfall data. Eight number crops and three types of soil class have been considered for optimization model. Area under each crop and each soil class have been quantified using Modified Simplex Algorithm to get optimum net return. Efficacy of the software has been tested using data of large irrigation project in India.

Keywords: artificial neural network, large irrigation project, modified simplex algorithm, optimal cropping pattern

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Authors: R. Kanthavel, R. Yogesh Kumar, T. Narendrakumar, B. Santhosh, S. Surya Prakash

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This paper primarily focuses on developing an affordable personal assistant and the implementation of it in the field of Artificial Intelligence (AI) to create a virtual assistant/friend. The problem in existing home automation techniques is that it requires the usage of exact command words present in the database to execute the corresponding task. Our proposed work is ATOM a.k.a ‘Artificial intelligence Talking Omnipresent Machine’. Our inspiration came from an unlikely source- the movie ‘Iron Man’ in which a character called J.A.R.V.I.S has omnipresence, and device controlling capability. This device can control household devices in real time and send the live information to the user. This device does not require the user to utter the exact commands specified in the database as it can capture the keywords from the uttered commands, correlates the obtained keywords and perform the specified task. This ability to compare and correlate the keywords gives the user the liberty to give commands which are not necessarily the exact words provided in the database. The proposed work has a higher flexibility (due to its keyword extracting ability from the user input) comparing to the existing work Intelligent Home automation System (IHAS), is more accurate, and is much more affordable as it makes use of WI-FI module and raspberry pi 2 instead of ZigBee and a computer respectively.

Keywords: home automation, speech recognition, voice control, personal assistant, artificial intelligence

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Authors: Ukpaka Paschal

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Margret Boden argues that a creative product is one that is new, surprising, and valuable as a result of the combination, exploration, or transformation involved in producing it. Boden uses examples of artificial intelligence systems that fit all of these criteria and argues that real creativity involves autonomy, intentionality, valuation, emotion, and consciousness. This paper provides an analysis of all these elements in order to try to understand whether they are sufficient to account for creativity, especially human creativity. This paper focuses on Generative Adversarial Networks (GANs), which is a class of artificial intelligence algorithms that are said to have disproved the common perception that creativity is something that only humans possess. This paper will then argue that Boden’s listed properties of creativity, which capture the creativity exhibited by GANs, are not sufficient to account for human creativity, and this paper will further identify “first-person phenomenological experience” as an essential property of human creativity. The rationale behind the proposed essential property is that if creativity involves comprehending our experience of the world around us into a form of self-expression, then our experience of the world really matters with regard to creativity.

Keywords: artificial intelligence, creativity, GANs, first-person experience

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Authors: Belkacem Laimouche

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With the field of artificial intelligence (AI) experiencing exponential growth, fueled by technological advancements that pave the way for increasingly innovative and promising applications, there is an escalating need to develop rigorous methods for assessing their performance in pursuit of transparency and equity. This article proposes a metrology-inspired statistical framework for evaluating bias and explainability in AI systems. Drawing from the principles of metrology, we propose a pioneering approach, using a concrete example, to evaluate the accuracy and precision of AI models, as well as to quantify the sources of measurement uncertainty that can lead to bias in their predictions. Furthermore, we explore a statistical approach for evaluating the explainability of AI systems based on their ability to provide interpretable and transparent explanations of their predictions.

Keywords: artificial intelligence, metrology, measurement uncertainty, prediction error, bias, machine learning algorithms, probabilistic models, interlaboratory comparison, data analysis, data reliability, measurement of bias impact on predictions, improvement of model accuracy and reliability

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Authors: Nihal Murali, Kunal Gupta, Surekha Bhanot

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Training of artificial neural networks (ANNs) using reinforcement learning (RL) techniques is being widely discussed in the robot learning literature. The high model complexity of ANNs along with the model-free nature of RL algorithms provides a desirable combination for many robotics applications. There is a huge need for algorithms that generalize using raw sensory inputs, such as vision, without any hand-engineered features or domain heuristics. In this paper, the standard control problem of line following robot was used as a test-bed, and an ANN controller for the robot was trained on images from a live video feed using Q-learning. A virtual agent was first trained in simulation environment and then deployed onto a robot’s hardware. The robot successfully learns to traverse a wide range of curves and displays excellent generalization ability. Qualitative analysis of the evolution of policies, performance and weights of the network provide insights into the nature and convergence of the learning algorithm.

Keywords: artificial neural networks, q-learning, reinforcement learning, robot learning

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Authors: Marisa Almeida AraúJo

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Artificial intelligence (AI) tools are being used (including in the criminal justice system) and becomingincreasingly popular. The many questions that these (future) super-beings pose the neuralgic center is rooted in the (old) problematic between rationality and morality. For instance, if we follow a Kantian perspective in which morality derives from AI, rationality will also surpass man in ethical and moral standards, questioning the nature of mind, the conscience of self and others, and moral. The recognition of superior intelligence in a non-human being puts us in the contingency of having to recognize a pair in a form of new coexistence and social relationship. Just think of the humanoid robot Sophia, capable of reasoning and conversation (and who has been recognized for Saudi citizenship; a fact that symbolically demonstrates our empathy with the being). Machines having a more intelligent mind, and even, eventually, with higher ethical standards to which, in the alluded categorical imperative, we would have to subject ourselves under penalty of contradiction with the universal Kantian law. Recognizing the complex ethical and legal issues and the significant impact on human rights and democratic functioning itself is the goal of our work.

Keywords: ethics, artificial intelligence, legal rules, principles, philosophy

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Authors: Hsu-Yung Cheng, Kuo-Chang Hsu, Chi-Chang Chan, Mei-Hui Tseng, Chih-Chang Yu, Ya-Sheng Liu

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Photovoltaics modules are usually not installed horizontally to avoid water or dust accumulation. However, the measured irradiance data on tilted surfaces are rarely available since installing pyranometers with various tilt angles induces high costs. Therefore, estimating solar irradiance on tilted surfaces is an important research topic. In this work, artificial neural networks (ANN) are utilized to construct the transfer model to estimate solar irradiance on tilted surfaces. Instead of predicting tilted irradiance directly, the proposed method estimates the differences between the horizontal irradiance and the irradiance on a tilted surface. The outputs of the ANNs in the proposed design are differential values. The experimental results have shown that the proposed ANNs with differential outputs can substantially improve the estimation accuracy compared to ANNs that estimate the titled irradiance directly.

Keywords: photovoltaics, artificial neural networks, tilted irradiance, solar energy

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Authors: S. Adjiri-Bailiche, S. M. Boudia, H. Daaou, S. Hadouche, A. Benzaoui

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In this work the study of changes in the wind speed depending on the altitude is calculated and described by the model of the neural networks, the use of measured data, the speed and direction of wind, temperature and the humidity at 10 m are used as input data and as data targets at 50m above sea level. Comparing predict wind speeds and extrapolated at 50 m above sea level is performed. The results show that the prediction by the method of artificial neural networks is very accurate.

Keywords: MATLAB, neural network, power low, vertical extrapolation, wind energy, wind speed

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Authors: Gaurav Sancheti

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This study presents an impacting approach of Artificial Neural Networks (ANNs) in determining the quantity of High Tensile Steel (HTS) strands required in post-tensioned (PT) slabs. Various PT slab configurations were generated by varying the span and depth of the slab. For each of these slab configurations, quantity of required HTS strands were recorded. ANNs with backpropagation algorithm and varying architectures were developed and their performance was evaluated in terms of Mean Square Error (MSE). The recorded data for the quantity of HTS strands was used as a feeder database for training the developed ANNs. The networks were validated using various validation techniques. The results show that the proposed ANNs have a great potential with good prediction and generalization capability.

Keywords: artificial neural networks, back propagation, conceptual design, high tensile steel strands, post tensioned slabs, validation techniques

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Authors: Igor A. Bessmertny, Bidru C. Enkomaryam

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Active involving patients and communities in health decisions can improve both people’s health and the healthcare system. Adopting artificial intelligence can lead to more accurate and complete patient record management. This review aims to identify the current state of researches conducted using artificial intelligence techniques to improve patient engagement and wellbeing, medical domains used in patient engagement context, and lastly, to assess opportunities and challenges for patient engagement in the wellness process. A search of peer-reviewed publications, reviews, conceptual analyses, white papers, author’s manuscripts and theses was undertaken. English language literature published in 2013– 2022 period and publications, report and guidelines of World Health Organization (WHO) were also assessed. About 281 papers were retrieved. Duplicate papers in the databases were removed. After application of the inclusion and exclusion criteria, 41 papers were included to the analysis. Patient counseling in preventing adverse drug events, in doctor-patient risk communication, surgical, drug development, mental healthcare, hypertension & diabetes, metabolic syndrome and non-communicable chronic diseases are implementation areas in healthcare where patient engagement can be implemented using artificial intelligence, particularly machine learning and deep learning techniques and tools. The five groups of factors that potentially affecting patient engagement in safety are related to: patient, health conditions, health care professionals, tasks and health care setting. Active involvement of patients and families can help accelerate the implementation of healthcare safety initiatives. In sub-Saharan Africa, using digital technologies like artificial intelligence in patient engagement context is low due to poor level of technological development and deployment. The opportunities and challenges available to implement patient engagement strategies vary greatly from country to country and from region to region. Thus, further investigation will be focused on methods and tools using the potential of artificial intelligence to support more simplified care that might be improve communication with patients and train health care professionals.

Keywords: artificial intelligence, patient engagement, machine learning, patient involvement

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Authors: Sonia Anand Knowlton

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There are some cases where we as a society feel deeply uncomfortable with the use of Artificial Intelligence (AI) tools in the judicial decision-making process, and justifiably so. A perfect example is COMPAS, an algorithmic model that predicts recidivism rates of offenders to assist in the determination of their bail conditions. COMPAS turned out to be extremely racist: it massively overpredicted recidivism rates of Black offenders and underpredicted recidivism rates of white offenders. At the same time, there are certain uses of AI in the judicial decision-making process that many would feel more comfortable with and even support. Take, for example, a “super-breathalyzer,” an (albeit imaginary) tool that uses AI to deliver highly detailed information about the subject of the breathalyzer test to the legal decision-makers analyzing their drunk-driving case. This article evaluates the point at which a judge’s use of AI tools begins to undermine the public’s trust in the administration of justice. It argues that the answer to this question depends on whether the AI tool is in a role in which it must perform a moral evaluation of a human being.

Keywords: artificial intelligence, judicial reasoning, morality, technology, algorithm

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Authors: Natalia Uribe Corrales, Carolina Cano Arroyave, Santiago Henao Villegas

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Introduction: Stunning is an important stage in the meat industry due to the repercussions on the characteristics of the carcass. It has been demonstrated that inadequate stun can lead to hematomas, fractures and promote the appearance of pale, soft and exudative meat due to the stress caused in animals. In Colombia, gas narcosis and electrical stunning are the two authorized methods in pigs. Objective: To describe the practices of stunning in the Valle de Aburrá and its relation with animal welfare. Methods: A descriptive cross - sectional study was carried out in Valle de Aburrá slaughterhouses, which were authorized by National Institute for Food and Medicine Surveillance (INVIMA). Variables such as stunning method, presence of vocalization, falls, slips, rhythmic breathing, corneal reflex and attempts to incorporate after stunning, stun time and time between stun and bleeding were analyzed. Results: 225 pigs were analyzed, finding that 50.2% had electrical stun, whose amperage and voltage were 1.23 (A) and 120 (V) respectively; 49.8% of the animals were stunned with CO2 chamber whose concentration was always above 95%, the mean desensitization time was 16.8 seconds (d.e.5.37); the mean time of stunning - bleeding was 47.9 seconds (d.e.13.9); similarly, it was found that 27.1% had vocalizations after stunning; 12% had falls; 10.7% showed rhythmic breathing; 33.3% exhibited corneal reflex; and 10.7% had reincorporation attempts. Conclusions: The methods of stunning used in the Valle de Aburrá, although performed with those permitted by law, are shortcomings in relation to the amperage and voltage used for each type of pig, as well, it is found that welfare animal is being violated to find signology of an inadequate desensitization. It is necessary to promote compliance with the principles of stunning according to Animal Welfare, and keep in mind that in electrical desensitization, the calibration of the equipment must be guaranteed (pressure according to the type of animal or current applied and the position where the electrodes are) and in the narcosis the equipment should be calibrated to ensure proper gas concentration and exposure time.

Keywords: animal welfare, pigs, quality of meat, stun methods

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Authors: H. Kiani, S. Moradi, B. Soltani Soulgani, S. Mousavian

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Desalting/dehydration plants (DDP) are often installed in crude oil production units in order to remove water-soluble salts from an oil stream. In order to optimize this process, desalting unit should be modeled. In this research, artificial neural network is used to model efficiency of desalting unit as a function of input parameter. The result of this research shows that the mentioned model has good agreement with experimental data.

Keywords: desalting unit, crude oil, neural networks, simulation, recovery, separation

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Authors: Gurmail Singh

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Effective supply chain is the main priority of every organization which is the outcome of strategic corporate investments with deliberate management action. Value-driven supply chain is defined through development, procurement and by configuring the appropriate resources, metrics and processes. However, responsiveness of the supply chain can be improved by proper coordination. So the Bullwhip effect (BWE) and Net stock amplification (NSAmp) values were anticipated and used for the control of inventory in organizations by both discrete wavelet transform-Artificial neural network (DWT-ANN) and Adaptive Network-based fuzzy inference system (ANFIS). This work presents a comparative methodology of forecasting for the customers demand which is non linear in nature for a multilevel supply chain structure using hybrid techniques such as Artificial intelligence techniques including Artificial neural networks (ANN) and Adaptive Network-based fuzzy inference system (ANFIS) and Discrete wavelet theory (DWT). The productiveness of these forecasting models are shown by computing the data from real world problems for Bullwhip effect and Net stock amplification. The results showed that these parameters were comparatively less in case of discrete wavelet transform-Artificial neural network (DWT-ANN) model and using Adaptive network-based fuzzy inference system (ANFIS).

Keywords: bullwhip effect, hybrid techniques, net stock amplification, supply chain flexibility

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Authors: Natalia Uribe Corrales, Santiago Henao Villegas

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Introduction: The management of pigs in the holding pens at the slaughterhouses is a key point to minimize levels of stress and fear, improve efficiency, maintain a good quality of meat and avoid economic losses. Holding pens should guarantee drinking water continuously, a minimum space of 1.2 m2/ animal; As well as an adequate management in the conduction of the animals towards stun. Objective: To characterize the management practices in holding pens in slaughterhouses in the Valle de Aburrá. Methods: A descriptive cross - sectional study was carried out in Valle de Aburrá benefit plants, which were authorized by National Institute for Food and Medicine Surveillance (INVIMA). Variables such as management mechanisms to the pens, time of housing, water supply, load density, vocalization, slips and falls of the animals in the pens and mechanism of conduction towards desensitization were analyzed. Results: 225 pigs were analyzed, finding that 35.6% were lowered with slaps from the trucks to the waiting pens; The lairage time was greater than 10 hours in 16% of the animals; 12.9% of pigs had no water permanently; 40.9% was subjected to a high load density, while 19.6% had a low load density. Regarding aspects of animal welfare, 37.3% presented high vocalizations; 29.3% and 14.2% presented slips or falls respectively. Regarding the mechanism of conduction towards desensitization, slapping was used in 56% and electrical prod in 4%. Conclusions: It is necessary to continue promoting the learning of the densities of load, since both high and low densities generate inconveniences in animal welfare, favoring the appearance of lesions and stress in the animals. Also, to promote the rule of permanent water in the pens and a time of housing less than 10 hours. In relation to the driving mechanisms, it is necessary to continue animal husbandry campaigns, encouraging the use of other alternatives such as boards or panels to assist the movement of pigs.

Keywords: animal welfare, quality of meat, swine, waiting pens

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Authors: Rania Jradi, Christophe Marvillet, Mohamed Razak Jeday

Abstract:

One of the most frequently encountered problems in industrial heat exchangers is fouling, which degrades the thermal and hydraulic performances of these types of equipment, leading thus to failure if undetected. And it occurs due to the accumulation of undesired material on the heat transfer surface. So, it is necessary to know about the heat exchanger fouling dynamics to plan mitigation strategies, ensuring a sustainable and safe operation. This paper proposes an Artificial Neural Network (ANN) approach to estimate the fouling resistance in a cross-flow heat exchanger by the collection of the operating data of the phosphoric acid concentration loop. The operating data of 361 was used to validate the proposed model. The ANN attains AARD= 0.048%, MSE= 1.811x10⁻¹¹, RMSE= 4.256x 10⁻⁶ and r²=99.5 % of accuracy which confirms that it is a credible and valuable approach for industrialists and technologists who are faced with the drawbacks of fouling in heat exchangers.

Keywords: cross-flow heat exchanger, fouling, estimation, phosphoric acid concentration loop, artificial neural network approach

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