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Academic literature on the topic 'Artificial section'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Artificial section"

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Gond, Pankaj Kumar, Aditya Shukla, Satish Sahani, Neha Gond, and Dr Harvendra Kumar. "Association Rule Mining using FP-Growth and An Innovative Artificial Neural Network Techniques." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (May 31, 2022): 3407–12. http://dx.doi.org/10.22214/ijraset.2022.43149.

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Abstract: With the prodigious proliferation of ginormous-scale data depots, a need for incorporating the empirical techniques of Data Mining (DM) with the effectiveness of commensurate systems to intuitively manage cosmic volumes of data has now risen. To quell these obstructions of managing data efficiently, in this document we present a new algorithm based on ANN for DM activities, which overcomes the problems in the current available algorithms of mining apropos of their execution time and interestingness and to prove its efficiency the new algorithm will be compared to a popular mining algorithm: FP Growth. The following sections of the paper are sorted as – section I exhibits the introduction, section II exhibits the previously done related works, section III is exemplifies of the methodologies, section IV exhibits the experimental setup of the analogous work, section V inculcates the experimental result and finally section VI depicts the conclusion of the respective work. Keyword: Data Mining, Association Rule Mining, FP Growth algorithm, Artificial Neural Networks.
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Vinayak, Patil Ashish, and S. R. Suryawanshi. "Behaviour of Frp Strengthening of Hysd-I Section With Artificial Degradation." Journal of Advances and Scholarly Researches in Allied Education 15, no. 2 (April 1, 2018): 427–30. http://dx.doi.org/10.29070/15/56859.

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YANG, H. S. "Special Section on Artificial Reality and Telexistence." IEICE Transactions on Information and Systems E89-D, no. 1 (January 1, 2006): 9–10. http://dx.doi.org/10.1093/ietisy/e89-d.1.9.

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Li, Hairong. "Special Section Introduction: Artificial Intelligence and Advertising." Journal of Advertising 48, no. 4 (August 8, 2019): 333–37. http://dx.doi.org/10.1080/00913367.2019.1654947.

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López, Beatriz, Clare Martin, and Pau Herrero Viñas. "Special section on artificial intelligence for diabetes." Artificial Intelligence in Medicine 85 (April 2018): 26–27. http://dx.doi.org/10.1016/j.artmed.2017.09.008.

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Xie, Heng Xing. "Analysis of Water Environmental Quality Using BP Artificial Neural Network in Weihe River Baoji Segment." Applied Mechanics and Materials 401-403 (September 2013): 2147–50. http://dx.doi.org/10.4028/www.scientific.net/amm.401-403.2147.

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The BP artificial neural network model in type 7-5-5 was constructed with the surface water quality standard (GB3838-2002) and the surface water quality items such as BOD5 (5 day biochemical oxygen demand), COD (chemical oxygen demand), permanganate index, fluoride, NH3-N, TP (total phosphorus) and TN (total nitrogen), and the water environmental quality evaluation was conducted using the trained BP artificial neural network with the water contamination concentration data in 6 sections of Weihe river Baoji segment in year 2009. Results showed that the water quality were GradeIand GradeII in Lin Jia Cun section and Sheng Li Qiao section, and Grade III in the rest section (Wo Long Si Bridge, Guo Zhen Bridge, Cai Jia Po Bridge and Chang Xing Bridge).
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Obeid, H., F. Hillani,, R. Fakih, and K. Mozannar. "Artificial Intelligence: Serving American Security and Chinese Ambitions." Financial Markets, Institutions and Risks 4, no. 3 (2020): 42–52. http://dx.doi.org/10.21272/fmir.4(3).42-52.2020.

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In recent years artificial intelligence has entered a new era, which gives rise to many hopes for powerful states such as the United States and China. In this paper, we analyze the importance and role of artificial intelligence in technological development in each of the two countries on the one hand, and its influence on China-American relations in terms of technological and geopolitical conflict. To get the right results, we rely on a literature review of dozens of articles published on the phenomenon in order to compare the power of artificial intelligence between the United States and China where we found that the US still has technological strength, especially in the field of artificial intelligence, but we can say that a large force is beginning pose a threat for it which is China that has great technological capabilities so, we can say that the United States should work more in this field. Also, we found that artificial intelligence has a primary goal in both countries, it helps China to achieve its ambitions to be the leader of the world, and this intelligence, on the other hand, provides protection and security to the United States. This paper is divided into three sections. The first section focuses on the importance of artificial intelligence in achieving China’s ambitions, the second section explains the role of artificial intelligence in the US protection service, and the third section describes the technological and geopolitical conflict resulting from the competition in artificial intelligence between these two countries. Keywords: Artificial intelligence, United States, China, Conflict, leader.
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Wu, Huiling, Bingzheng Wu, Fangping Lai, Peizhong Liu, Guorong Lyu, Shaozheng He, and Jiangfeng Dai. "Application of Artificial Intelligence in Anatomical Structure Recognition of Standard Section of Fetal Heart." Computational and Mathematical Methods in Medicine 2023 (January 24, 2023): 1–13. http://dx.doi.org/10.1155/2023/5650378.

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Congenital heart defect (CHD) refers to the overall structural abnormality of the heart or large blood vessels in the chest cavity. It is the most common type of fetal congenital defects. Prenatal diagnosis of congenital heart disease can improve the prognosis of the fetus to a certain extent. At present, prenatal diagnosis of CHD mainly uses 2D ultrasound to directly evaluate the development and function of fetal heart and main structures in the second trimester of pregnancy. Artificial recognition of fetal heart 2D ultrasound is a highly complex and tedious task, which requires a long period of prenatal training and practical experience. Compared with manual scanning, computer automatic identification and classification can significantly save time, ensure efficiency, and improve the accuracy of diagnosis. In this paper, an effective artificial intelligence recognition model is established by combining ultrasound images with artificial intelligence technology to assist ultrasound doctors in prenatal ultrasound fetal heart standard section recognition. The method data in this paper were obtained from the Second Affiliated Hospital of Fujian Medical University. The fetal apical four-chamber heart section, three vessel catheter section, three vessel trachea section, right ventricular outflow tract section, and left ventricular outflow tract section were collected at 20-24 weeks of gestation. 2687 image data were used for model establishment, and 673 image data were used for model validation. The experiment shows that the map value of this method in identifying different anatomical structures reaches 94.30%, the average accuracy rate reaches 94.60%, the average recall rate reaches 91.0%, and the average F1 coefficient reaches 93.40%. The experimental results show that this method can effectively identify the anatomical structures of different fetal heart sections and judge the standard sections according to these anatomical structures, which can provide an auxiliary diagnostic basis for ultrasound doctors to scan and lay a solid foundation for the diagnosis of congenital heart disease.
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Dymitruk, Maria. "The Right to a Fair Trial in Automated Civil Proceedings." Masaryk University Journal of Law and Technology 13, no. 1 (June 30, 2019): 27–44. http://dx.doi.org/10.5817/mujlt2019-1-2.

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Challenges associated with the use of artificial intelligence (AI) in law are one of the most hotly debated issues today. This paper draws attention to the question of how to safeguard the right to a fair trial in the light of rapidly changing technologies significantly affecting the judiciary and enabling automation of the civil procedure. The paper does not intend to comprehensively address all aspects related to the right to a fair trial in the context of the automation of civil proceedings but rather seeks to analyse some legal concerns from the perspective of the Article 6 of the European Convention on Human Rights and the case-law of the European Court of Human Rights. Section 1 discusses the issues of using artificial intelligence in the justice and automation of the judicial proceedings. Section 2 is devoted to the judge supporting system based on artificial intelligence and psychological requirements of its practical use. Section 3 presents the right to a fair trial in civil cases established by the Article 6 of the European Convention on Human Rights, while subsequent sections characterize its elements with respect to the possibility to automate civil proceedings: a right to have case heard within a reasonable time in section 4 and a right to a reasoned judgment in section 5.
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O'Leary, Daniel E., and John Kingston. "Artificial intelligence in business II: Development, integration and organizational issues." Knowledge Engineering Review 9, no. 1 (March 1994): 1–19. http://dx.doi.org/10.1017/s026988890000655x.

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AbstractThe purpose of this paper is to review the use of knowledge-based systems and artificial intelligence (AI) in business. Part I of this paper provided a broad survey of the use of AI in business, summarizing the application of AI in a number of business domains. In addition, it also provided a summary of the use of different forms of knowledge representation in business applications. Part I has a large set of references, including a number of survey papers, focusing on AI in business. Part II of this paper consists of more detailed analysis of particular systems or issues affecting AI in business. It examines technical issues which are central to the construction of business AI systems, and it also examines the commercial contribution made by methods for the development of AI systems. In addition, part II looks at integration between AI and more traditional information systems. AI can be used to add value to many existing information systems, such as database management systems. Particular attention is given to the integration of AI with operations research, which is the one of the primary “competitors” of AI, providing an alternative set of support tools for decision making.Business organizations are not concerned only with technology issues; there is also concern about the impact of AI on organizations. Further, the evaluation of AI often is based on an economic view of the world. Part II therefore investigates the organizational impact of AI, and the economics of AI, including issues such as value creation. The format of Part II is as follows: Section 8 analyses techniques for improving the performance of AI systems, thus maximizing economic return. Section 9 looks at different forms of uncertainty and ambiguity which must be dealt with by AI systems. It examines the contributions of fuzzy logic and numerical measures of certainty to handling these problems. Section 10 examines the usefulness of different approaches to knowledge acquisition in business situations, and investigates the benefits of methodological approaches to AI applications. It also looks at more recent AI programming techniques which eliminate the need for knowledge elicitation from an expert: neural networks, case-based reasoning and genetic algorithms are discussed. Sections 11 and 12 examine issues of integrating AI systems. Generally, the use of AI in business settings must ultimately be integrated with the broader base of corporate information systems. Section 11 looks at integration with information systems in general, and section 12 looks particularly at integration with operations research. Sections 13 and 14 review the organizational and economic impact of AI. Finally, section 15 provides a brief summary of part II.
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Dissertations / Theses on the topic "Artificial section"

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Sanchez, Maguiña Mildred Madeleine, and Feliz Pool Rusbel Vidal. "Optimización de las dimensiones de placas mediante el uso de IA para reducir los costos en edificios de 6 pisos en el distrito de Miraflores." Bachelor's thesis, Universidad Peruana de Ciencias Aplicadas (UPC), 2020. http://hdl.handle.net/10757/652826.

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En el presente artículo se investiga la implementación de las Redes Neuronales Artificiales como un tipo de Inteligencia Artificial con la finalidad de reducir los costos de concreto armado. Por esto, se propuso el uso de este tipo de algoritmo con el objetivo de optimizar las secciones de los muros de corte en edificaciones de 6 pisos sin irregularidades. Se configuraron 10 redes neuronales distintas con el fin de elegir la que se adapte mejor a los datos empleados para el entrenamiento. En cada algoritmo se establecieron como variables de entrada el ancho y largo de la edificación; y la distancia entre luz máxima del eje X e Y. Sin embargo, el número de capas ocultas y el de neuronas en cada una de ellas fue distinto. En la etapa de entrenamiento se emplearon 30 casos con dimensiones optimizadas, con esto se obtuvo que la red neuronal predice la longitud total de la placa y su espesor con un error del 10%.
This article investigates the use of Artificial Neural Networks as a type of Artificial Intelligence in order to reduce the costs of reinforced concrete. For this reason, the use of this type of algorithm was proposed with the objective of optimizing the sections of the shear walls in 6-story buildings without irregularities. Ten different neural networks were configured in order to choose the one that best suits the data used for training. In each algorithm, the width and length of the building; and the distance between maximum span of the X and Y axis were established as input variables. However, the number of hidden layers and the number of neurons in each of them was different. In the training stage, 30 cases with optimized dimensions were used, with this it was obtained that the neuronal network predicts the total length of the shear wall and its thickness with an error of 10%.
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Szames, Esteban Alejandro. "Few group cross section modeling by machine learning for nuclear reactor." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASS134.

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Pour estimer la répartition de la puissance au sein d’un réacteur nucléaire, il est nécessaire de coupler des modélisations neutroniques et thermohydrauliques. De telles simulations doivent disposer des valeurs sections efficaces homogénéisées à peu de groupes d’énergies qui décrivent les interactions entre les neutrons et la matière. Cette thèse est consacrée à la modélisation des sections efficaces par des techniques académiques innovantes basées sur l’apprentissage machine. Les premières méthodes utilisent les modèles à noyaux du type RKHS (Reproducing Kernel Hilbert Space) et les secondes par réseaux de neurones. La performance d’un modèle est principalement définie par le nombre de coefficients qui le caractérisent (c’est-à-dire l’espace mémoire nécessaire pour le stocker), la vitesse d’évaluation, la précision, la robustesse au bruit numérique, la complexité, etc. Dans cette thèse, un assemblage standard de combustible UOX REP est analysé avec trois variables d’état : le burnup, la température du combustible et la concentration en bore. La taille de stockage des bibliothèques est optimisée en cherchant à maximiser la vitesse et la précision de l’évaluation, tout en cherchant à réduire l’erreur de reconstruction des sections efficaces microscopiques, macroscopiques et du facteur de multiplication infini. Trois techniques d’approximation sont étudiées. Les méthodes de noyaux, qui utilisent le cadre général d’apprentissage machine, sont capables de proposer, dans un espace vectoriel normalisé, une grande variété de modèles de régression ou de classification. Les méthodes à noyaux peuvent reproduire différents espaces de fonctions en utilisant un support non structuré, qui est optimisé avec des techniques d’apprentissage actif. Les approximations sont trouvées grâce à un processus d’optimisation convexe facilité par "l’astuce du noyau”. Le caractère modulaire intrinsèque de la méthode facilite la séparation des phases de modélisation : sélection de l’espace de fonctions, application de routines numériques, et optimisation du support par apprentissage actif. Les réseaux de neurones sont des méthodes d’approximation universelles capables d’approcher de façon arbitraire des fonctions continues sans formuler de relations explicites entre les variables. Une fois formés avec des paramètres d’apprentissage adéquats, les réseaux à sorties multiples (intrinsèquement parallélisables) réduisent au minimum les besoins de stockage tout en offrant une vitesse d’évaluation élevée. Les stratégies que nous proposons sont comparées entre elles et à l’interpolation multilinéaire sur une grille cartésienne qui est la méthode utilisée usuellement dans l’industrie. L’ensemble des données, des outils, et des scripts développés sont disponibles librement sous licence MIT
Modern nuclear reactors utilize core calculations that implement a thermo-hydraulic feedback requiring accurate homogenized few-group cross sections.They describe the interactions of neutrons with matter, and are endowed with the properties of smoothness and regularity, steaming from their underling physical phenomena. This thesis is devoted to the modeling of these functions by industry state-of-theart and innovative machine learning techniques. Mathematically, the subject can be defined as the analysis of convenient mapping techniques from one multi-dimensional space to another, conceptualize as the aggregated sum of these functions, whose quantity and domain depends on the simulations objectives. Convenient is intended in terms of computational performance, such as the model’s size, evaluation speed, accuracy, robustness to numerical noise, complexity,etc; always with respect to the engineering modeling objectives that specify the multidimensional spaces of interest. In this thesis, a standard UO₂ PWR fuel assembly is analyzed for three state-variables, burnup,fuel temperature, and boron concentration.Library storage requirements are optimized meeting the evaluation speed and accuracy targets in view of microscopic, macroscopic cross sections and the infinite multiplication factor. Three approximation techniques are studied: The state-of-the-art spline interpolation using computationally convenient B-spline basis, that generate high order local approximations. A full grid is used as usually donein the industry. Kernel methods, that are a very general machine learning framework able to pose in a normed vector space, a large variety of regression or classification problems. Kernel functions can reproduce different function spaces using an unstructured support,which is optimized with pool active learning techniques. The approximations are found through a convex optimization process simplified by the kernel trick. The intrinsic modular character of the method facilitates segregating the modeling phases: function space selection, application of numerical routines and support optimization through active learning. Artificial neural networks which are“model free” universal approximators able Artificial neural networks which are“model free” universal approximators able to approach continuous functions to an arbitrary degree without formulating explicit relations among the variables. With adequate training settings, intrinsically parallelizable multi-output networks minimize storage requirements offering the highest evaluation speed. These strategies are compared to each other and to multi-linear interpolation in a Cartesian grid, the industry standard in core calculations. The data set, the developed tools, and scripts are freely available under aMIT license
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Hou, Chuanchuan. "Vibration-based damage identification with enhanced frequency dataset and a cracked beam element model." Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/20434.

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Damage identification is an important topic in structural assessment and structural health monitoring (SHM). Vibration-based identification techniques use modal data to identify the existence, location and severity of possible damages in structures, often via a numerical model updating procedure. Among other factors influencing the practicality and reliability of a damage identification approach, two are of primary interest to this study. The first one concerns the amount and quality of modal data that can be used as ‘response’ data for the model updating. It is generally recognised that natural frequencies can be measured with relatively high accuracy; however, their number is limited. Mode shapes, on the other hand, are susceptible to larger measurement errors. Seeking additional modal frequency data is therefore of significant value. The second one concerns the errors at the numerical (finite element) model level, particularly in the representation of the effect of damage on the dynamic properties of the structure. An inadequate damage model can lead to inaccurate and even false damage identification. The first part of the thesis is devoted to enhancing the modal dataset by extracting the so called ‘artificial boundary condition’ (ABC) frequencies in a real measurement environment. The ABC frequencies correspond to the natural frequencies of the structure with a perturbed boundary condition, but can be generated without the need of actually altering the physical support condition. A comprehensive experimental study on the extraction of such frequencies has been conducted. The test specimens included steel beams of relatively flexible nature, as well as thick and stiffer beams made from metal material and reinforced concrete, to cover the typical variation of the dynamic characteristics of real-life structures in a laboratory condition. The extracted ABC frequencies are subsequently applied in the damage identification in beams. Results demonstrate that it is possible to extract the first few ABC frequencies from the modal testing in different beam settings for a variety of ABC incorporating one or two virtual pin supports. The inclusion of ABC frequencies enables the identification of structural damages satisfactorily without the necessity to involve the mode shape information. The second part of the thesis is devoted to developing a robust model updating and damage identification approach for beam cracks, with a special focus on thick beams which present a more challenging problem in terms of the effect of a crack than slender beams. The priority task has been to establish a crack model which comprehensively describes the effect of a crack to reduce the modelling errors. A cracked Timoshenko beam element model is introduced for explicit beam crack identification. The cracked beam element model is formulated by incorporating an additional flexibility due to a crack using the fracture mechanics principles. Complex effects in cracked thick beams, including shear deformation and coupling between transverse and longitudinal vibrations, are represented in the model. The accuracy of the cracked beam element model for predicting modal data of cracked thick beams is first verified against numerically simulated examples. The consistency of predictions across different modes is examined in comparison with the conventional stiffness reduction approach. Upon satisfactory verification, a tailored model updating procedure incorporating an adaptive discretisation approach is developed for the implementation of the cracked beam element model for crack identification. The updating procedure is robust in that it has no restriction on the location, severity and number of cracks to be identified. Example updating results demonstrate that satisfactory identification can be achieved for practically any configurations of cracks in a beam. Experimental study with five solid beam specimens is then carried out to further verify the developed cracked beam element model. Both forward verification and crack damage identification with the tested beams show similar level of accuracy to that with the numerically simulated examples. The cracked beam element model can be extended to crack identification of beams with complex cross sections. To do so the additional flexibility matrix for a specific cross-section type needs to be re-formulated. In the present study this is done for box sections. The stress intensity factors (SIF) for a box section as required for the establishment of the additional flexibility matrix are formulated with an empirical approach combining FE simulation, parametric analysis and regression analysis. The extended cracked beam element model is verified against both FE simulated and experimentally measured modal data. The model is subsequently incorporated in the crack identification for box beams. The successful extension of the cracked beam element model to the box beams paves the way for similar extension to the crack identification of other types of sections in real-life engineering applications.
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Fatima, Samar. "Mapping artificial intelligence affordances for the public sector." Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/235926/1/Samar%2BFatime%2BThesis.pdf.

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This thesis explores the affordances of artificial intelligence (AI) for the public sector. The thesis consists of three studies that answer what, why and how questions of AI affordance actualization in public sector using a combination of primary and secondary data sources. In this thesis, the affordance theory lens is used to explore AI affordance perception and actualization for the public sector through three related studies. The perception of AI affordance is investigated in the first two studies. The third study designed and evaluated artefact for public agencies to actualize AI affordance.
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Gomes, Cristina Maria da Silva Ganchinho. "Desafios da adoção de inteligência artificial no sector público." Master's thesis, Instituto Superior de Economia e Gestão, 2020. http://hdl.handle.net/10400.5/21099.

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Mestrado em Gestão de Sistemas de Informação
A transformação digital provocada pela introdução da Inteligência Artificial nos negócios, trouxe muitas vantagens competitivas às organizações, através da otimização de processos de trabalho, possibilidade de investimentos em novas áreas de Mercado, entre outros. A evolução tecnológica evidencia cada vez mais o papel da IA nesta crescente transformação digital sendo por isso importante compreender o seu efeito nas organizações e nas pessoas. Este estudo pretende identificar quais são os potenciais desafios que o Setor Publico enfrenta na adoção de tecnologias suportadas em IA. Para tal foi realizada uma investigação, de caracter exploratório, com recurso a entrevistas a gestores da área tecnológica de várias organizações do Sector Público. Foram realizadas cinco entrevistas com questões abertas onde se pretendeu responder a questões relacionadas com a decisão de adoção de IA. Os resultados do estudo demonstram que existe motivação para a adoção destas tecnologias, no entanto existem alguns constrangimentos que influenciam a adoção destas tecnologias, destacamos a falta de recursos humanos e a capacitação dos mesmos como sendo um dos maiores dos desafios.
The digital transformation brought by the introduction of Artificial Intelligence in business provided many competitive advantages to organizations, through the optimization of work processes, the possibility of investments in new business areas among others. Technological evolution increasingly highlights the role of AI in this growing digital transformation and therefore it is important to understand its effect on organizations and in people. This study aims to identify which are the potential challenges that the Public Sector faces in the adoption of technologies supported by AI. To achieve this goal, an exploratory investigation was carried out using interviews with managers in the IT area of distinct business areas of the Public Sector. Five interviews were conducted with open questions about the decision to adopt AI in organizations of the Public Sector. The results show that despite the motivation for the adoption of these technologies, there are some important constraints affecting this adoption, namely the lack of human resources and their training as one of the greatest challenges.
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Gustafsson, Victor. "Artificial intelligence effect on jobs in the financial sector." Thesis, Mittuniversitetet, Avdelningen för ekonomivetenskap och juridik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-34247.

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Carbajal, Valverde Giuliana Mayte, and Correa Gianella Alejandra Segura. "Consecuencias positivas y negativas de la inteligencia artificial en el sector hotelero." Bachelor's thesis, Universidad Peruana de Ciencias Aplicadas (UPC), 2021. http://hdl.handle.net/10757/656854.

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La tecnología es un factor esencial pues transforma, influye y brinda grandes beneficios a la humanidad; dentro de ella destaca la inteligencia artificial, la cual en los últimos años ha sido de gran ayuda para diferentes rubros. Uno de ellos es el sector hotelero, el cual ha ido implementando en sus servicios la inteligencia artificial según las exigencias del mercado. La presente investigación se centra en determinar las consecuencias de la inteligencia artificial en el sector hotelero. Se analizará las consecuencias positivas y negativas de dicha tecnología y cómo se está implementando en la industria hotelera actualmente. El presente estudio se sustenta en la revisión de literatura de revistas científicas y tesis de grado. Asimismo, se utiliza el enfoque metodológico integrador, el cual sintetiza y examina la literatura encontrada sobre el tema a investigar para encontrar nuevas definiciones y perspectivas. Se obtuvo como hallazgo que el uso de la inteligencia artificial beneficia al sector hotelero de diferentes maneras, por ejemplo, automatizando servicios, reduciendo los tiempos y costos, entre otros. Asimismo, la mayoría de estudios se concentran en consecuencias positivas. En conclusión, la inteligencia artificial es de beneficio para el sector hotelero, ya que disminuye tiempos, reduce costos, y ayuda a obtener información valiosa para la toma de decisiones.
Technology is an essential factor because it transforms, influences, and provides great benefits to humanity; inside it, artificial intelligence stands out, which has been of great help to different areas in recent years. One of them is the hotel sector, which has been implementing artificial intelligence in its services according to market demands. This research work is focused on determining the consequences of artificial intelligence in the hotel sector. It will analyze this technology’s positive and negative aspects and how it is currently being implemented in the hotel industry. This study is based on the literature review of scientific journals and theses. Furthermore, this research uses the integrative methodological approach, which synthesizes and examines the literature to find new definitions and perspectives. In conclusion, the use of artificial intelligence benefits the hotel sector in different ways, for example, automating services, reducing time and costs, among others. In conclusion, artificial intelligence is beneficial for the hotel sector, since it reduces time, reduces costs, and helps to obtain valuable information for decision-making.
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Amaro, Jorge Filipe Montez Vaz Monteiro. "Modelos de avaliação em massa : redes neuronais artificiais aplicadas ao sector imobiliário residencial em Portugal? : estudo de caso na cidade de Lisboa." Master's thesis, Instituto Superior de Economia e Gestão, 2012. http://hdl.handle.net/10400.5/10737.

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Mestrado em Gestão e Avaliação Imobiliária
As redes neuronais artificiais são uma metodologia alternativa aos modelos tradicionais de previsão. A sua utilização tem-se vindo a massificar, sobretudo nas áreas da medicina, finanças, indústria automóvel e, mais recentemente em modelos de avaliação em massa aplicados ao mercado imobiliário. Este trabalho teve como objectivo fundamental a realização de experiências que utilizassem esta metodologia de previsão não paramétrica (não linear). No estudo de caso apresentado, foram analisadas 2.013 transacções, que ocorreram entre 2007 e 2012, mediadas pela rede de franchisados RE/MAX, relativas ao segmento residencial na cidade de Lisboa. Com esta base de dados, e depois de encontrada a melhor rede neuronal, foi possível obter um erro médio percentual absoluto (MAPE) na ordem dos 19%, em que para cerca de 67% da amostra foi alcançado um erro de estimação abaixo dos 20%. Utilizando esta metodologia, também foi observado que a rede neuronal funciona melhor se eliminados os outliers da amostra, aumentando a sua precisão. Foi ainda experimentada a introdução de variáveis temporais e de localização, tais como o ano de transacção de um determinado imóvel e a sua idade, ou ainda a freguesia onde está inserido, tendo sido obtidos comportamentos positivos no desempenho das redes. Para além da originalidade do tema, é de destacar que foram utilizados para este trabalho, valores reais de transacção relativos ao sector residencial em Portugal, tendo sido verificada uma aproximação do comportamento e da tendência do valor de transacção estimado pela rede, aos verificados pelo mercado.
The artificial neural networks are an alternative approach to traditional forecasting. Its use has been largely used, particularly in the areas of medicine, finance, automotive, and more recently in mass valuation models applied to the real estate market. This work had as main objective conducting experiments that used this methodology to forecast nonparametric (nonlinear). In the case study were analyzed 2013 transactions that occurred between 2007 and 2012, mediated by the network of franchisees RE / MAX, for the residential segment in Lisbon. With this database, and after found the best neural network, it was possible to obtain an mean absolute percent error (MAPE) of around 19%, in which to approximately 67% of the sample was reached estimation error below 20 %. Using this methodology, it was also observed that the neural network works better if the outliers are removed from the sample, increasing its accuracy. It also experienced the introduction of temporal variables and location, such as the year of a particular property transaction and its age, or the parish where it is located, having obtained positive behaviors in network performance. Beyond the originality of the subject, it is worth noting that was used for this work, actual transaction values for the residential sector in Portugal, having been verified an approximation of the behavior and trend of the transaction value estimated by the network, verified by the market.
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Mendieta, Retuerto Carlos Andres. "El uso del Chatbot con respecto a la satisfacción del cliente en empresas del sector financiero en Lima Metropolitana." Bachelor's thesis, Universidad Peruana de Ciencias Aplicadas (UPC), 2020. http://hdl.handle.net/10757/651915.

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La tecnología ha ido evolucionando durante los últimos años. La inteligencia artificial ha conseguido entrar en los mercados de todo el mundo como una nueva tecnología y nueva forma de ver el mundo. Es por ello, quen este estudio se explora las dimensiones del chatbot, que son tres: Calidad de la información, calidad del sistema y calidad del servicio en relación a la satisfacción del cliente en el sistema financiero en Lima Metropolitana. Este estudio está dividido en dos partes: un estudio cualitativo y uno cuantitativo. En la parte cualitativa, en donde se buscó la opinió de tres expertos del tema y, asimismo, se realizaron tres focus group. Con respecto al estudio cuantitativo, se usó una muestra de 250 personas. Los datos analizados sugieren que existe una relación entre las dimensiones del chatbot y la satisfacción del cliente, pero dicha relación es negativa muy baja.
Technology has been evolving in recent years. Artificial intelligence has managed to enter markets around the world as a new technology and a new way of seeing the world. That is why, in this study, the dimensions of the chatbot are explored, which are three: Information quality, system quality and service quality in relation to customer satisfaction in the financial system in Metropolitan Lima. This study is divided into two parts: a qualitative and a quantitative study. In the qualitative part, where the opinion of three experts of the subject was sought and, likewise, three focus groups were carried out. With respect to the quantitative study, a sample of 250 people was used. The data analyzed suggest that there is a relationship between the dimensions of the chatbot and customer satisfaction, but this relationship is very low negative.
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Kloub, Maha, and Annika Gerigoorian. "A Cross-Sectional Technology Acceptance Study of an AI CAD System in a Breast Screening Unit." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-299859.

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In January 2021, one of the first large-scale implementations of an artificial intelligent computer-aided detection system (AI CAD) for detecting breast cancer was implemented at Capio S:t Göran hospital in Stockholm. AI CAD for detecting breast cancer is promising, however, it can only be a successful implementation if it is accepted by the end-users. This study examines and evaluates factors critical to the acceptance of the AI CAD, prior to the radiology professionals using it by applying the third version of the Technology Acceptance Model, that is TAM3. A questionnaire was designed and distributed accordingly to 28 professionals at the hospital’s breast screening unit. The quantitative data collected were further analyzed using the statistical tool SPSS. The empirical findings concluded that the intention to use the AI CAD was influenced directly by the perceived usefulness and indirectly by image, job relevance, and perceived ease of use. In addition, the association between subjective norm and image was shown to be significant. This study further revealed two new associations, contrary to what TAM3 postulates, the first one being between image and behavioral intention and the second one being between job relevance and behavioral intention. Organizational support, system-related activities, and information and communication are interventions suggested based on the findings in this study, in which the breast screening unit at S:t Göran should tap into to enhance the acceptance of the AI CAD system.
I januari 2021, implementerades ett artificiellt intelligent datorstött detektionssystem som ska upptäcka bröstcancer på Capio S:t Görans sjukhus i Stockholm. Användning av AI CAD för att upptäcka bröstcancer är lovande, men det kan endast bli en framgångsrik implementering om det accepteras av de som använder systemet. Denna studie undersöker och utvärderar de initiala faktorer som är avgörande för användaracceptansen av AI CAD hos radiologipersonal genom att utgå från den senaste versionen av teknologiacceptansmodellen – Technology Acceptance Model 3 (TAM3). Ett frågeformulär utformades i enlighet med modellen och distribuerades till 28 yrkesverksamma på S:t Görans mammografiavdelning. Den kvantitativa data som samlades in från enkäten analyserades med hjälp av det statistiska verktyget SPSS. De empiriska resultaten visade att radiologipersonalens avsikt att använda AI CAD påverkades direkt av den upplevda användbarheten av systemet och indirekt av personalens upplevda syn på hur enkelt systemet är att använda, att systemet är relevant för personalens jobb samt att systemet kan höja personalens image. Dessutom bekräftade studien att den subjektiva normen påverkar systemets image. Slutligen upptäcktes två nya associationer, i vilken TAM3 inte antar. Dessa påträffades mellan image och den beteendemässiga intentionen till att använda systemet samt mellan jobbrelevansen och den beteendemässiga intentionen till att använda systemet. Organisationsstöd, systemrelaterade aktiviteter samt information och kommunikation med personal är interventioner som föreslås baserat på resultaten i denna studie som mammografiavdelningen på S:t Görans sjukhus bör utnyttja för att öka acceptansen av AI CAD systemet.
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Books on the topic "Artificial section"

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O'Dell, S. L. Fifth Conference on Artificial Intelligence for Space Applications: Proceedings of a conference sponsored by the University of Alabama in Huntsville, the IEEE Computer Society/Huntsville Chapter, the AIAA Alabama-Mississippi Section, and the National Aeronautics and Space Administration and held in Huntsville, Alabama, May 22-23, 1990. Huntsville, Ala: George C. Marshall Space Flight Center, 1990.

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United States. President (1989-1993 : Bush). Approving exports for the AUSSAT and FREJA projects: Communication from the President of the United States transmitting his justification for waiving legislative prohibitions on approval of United States-origin exports to China for the AUSSAT communication and FREJA scientific satellite projects, pursuant to Public Law 101-246, section 902(b)(2) (104 Stat. 85). Washington: U.S. G.P.O., 1991.

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Ahmed, S. E. (Syed Ejaz), 1957- editor of compilation, ed. Perspectives on big data analysis: Methodologies and applications : International Workshop on Perspectives on High-Dimensional Data Anlaysis II, May 30-June 1, 2012, Centre de Recherches Mathématiques, University de Montréal, Montréal, Québec, Canada. Providence, Rhode Island: American Mathematical Society, 2014.

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Chuvikov, Dmitriy. Models and algorithms for reconstruction and examination of emergency events of road accidents based on logical artificial intelligence. 2nd ed. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1220729.

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The purpose of the monograph is to create a methodology, combined expert and simulation models, as well as algorithms and software-modeling tools for reconstruction and examination of accident events for automating decision-making by an expert center employee. The methodology of combining and algorithms of joint work of an expert system based on logical artificial intelligence (mivar approach) and a simulation system for solving problems of reconstruction and examination of road accidents are developed; model reconstruction and examination of the accident in the formalism of the knowledge base bipartite oriented mivar nets, including analysis formulas braking qualities of the vehicle, determining the speed of a car's performance in terms of specific DTS, the formula for calculating different occasions: - slip car when braking, driving on curved sections of the road, hitting a car on the pedestrian in uniform motion and unlimited visibility; a method of generation of interfaces for designer expert systems based on the concept of mivar approach; special software in the form of expert systems "Analysis of road accident" in order to reduce the complexity of the process of calculating the disputed accidents, errors in the calculation and improve the accuracy and objectivity of the results obtained and the speed and quality of the calculations. It can be useful to specialists of expert institutions, insurance companies, educational institutions in the field of expertise, as well as unmanned vehicles in terms of objective analysis and examination of road accidents.
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Ksenofontov, Boris. Biological wastewater treatment. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1013710.

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The training manual sets out the theoretical and practical foundations of biological wastewater treatment in both natural and artificial conditions. For in-depth study of the fundamentals of biological wastewater treatment is quite detailed sections on the basics of Microbiology. Much attention is paid to choosing the best technologies of biological wastewater treatment with effective methods of nutrient removal. In the expanded version of the methods of biological purification of wastewater using membrane bioreactors. Are extensively explored domestic and foreign experience of biological treatment of municipal and industrial wastewater. Meets the requirements of Federal state educational standards of higher education of the last generation. Intended for students of bachelor, master, PhD students, teachers and professionals interested in the methods of sewage purification, and it is recommended to study for the enlarged group of specialties and areas 20.00.00 "Technosphere safety and environmental engineering".
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1974-, Zomorodian Afra J., ed. Advances in applied and computational topology: American Mathematical Society Short Course on Computational Topology, January 4-5, 2011, New Orleans, Louisiana. Providence, R.I: American Mathematical Society, 2012.

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Indoor Gardening/Artificial Lighting, Terrariums, Hanging Baskets, and Plant Section (Family Library of Home Improvement). Xs Books, 1985.

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Petrov, R. V. Immunology: Cell Interactions, Myelopeptides Artificial Immunogens (Soviet Medical Reviews Section D, Immunology Reviews, Vol 1). Routledge, 1987.

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[Artificial fruit sections]. Italy: Biella, 1989.

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The World Market for Artificial Monofilament of At Least 67 Decitex with Cross-Section Dimension Not Exceeding 1 mm and Artificial Textile Strip or Straw ... 5 mm Wide: A 2004 Global Trade Perspective. Icon Group International, Inc., 2005.

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Book chapters on the topic "Artificial section"

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Bachmeier, Andreas S. J. L. "Experimental Section." In Metalloenzymes as Inspirational Electrocatalysts for Artificial Photosynthesis, 213–33. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47069-6_8.

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Özcan, Fatma, V. S. Subrahmanian, and Leana Golubchik. "Optimal Agent Section." In KI 2001: Advances in Artificial Intelligence, 2–17. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45422-5_2.

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Sobhy, M. A., A. Y. Abdelaziz, M. Ezzat, W. Elkhattam, Anamika Yadav, and Bhupendra Kumar. "Artificial Bee Colony Optimization Algorithm for Fault Section Estimation." In Advances in Intelligent Systems and Computing, 127–39. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-3174-8_12.

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Chen, Chih-Wei, Nai-Wen Chang, Yung-Chun Chang, and Hong-Jie Dai. "Section Heading Recognition in Electronic Health Records Using Conditional Random Fields." In Technologies and Applications of Artificial Intelligence, 47–55. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13987-6_5.

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Boubakri, Akram, Saber Dakhli, Fethi Choubani, Tan Hoa Vuong, and Jacques David. "Coding metasurface for radar cross section reduction." In Innovative and Intelligent Technology-Based Services for Smart Environments – Smart Sensing and Artificial Intelligence, 110–16. London: CRC Press, 2021. http://dx.doi.org/10.1201/9781003181545-17.

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Stahl, Bernd Carsten, Doris Schroeder, and Rowena Rodrigues. "The Ethics of Artificial Intelligence: An Introduction." In Ethics of Artificial Intelligence, 1–7. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-17040-9_1.

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AbstractThis chapter introduces the themes covered by the book. It provides an overview of the concept of artificial intelligence (AI) and some of the technologies that have contributed to the current high level of visibility of AI. It explains why using case studies is a suitable approach to engage a broader audience with an interest in AI ethics. The chapter provides a brief overview of the structure and logic of the book by indicating the content of the cases covered in each section. It concludes by identifying the concept of ethics used in this book and how it is located in the broader discussion of ethics, human rightsand regulationof AI.
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de Oliveira, Karen Rezende Caino, Rodrigo Hartstein Salim, André Darós Filomena, Mariana Resener, and Arturo Suman Bretas. "Unbalanced Underground Distribution Systems Fault Detection and Section Estimation." In Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence, 1054–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74205-0_109.

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Capali, Veli. "Improve or Approximation of Nuclear Reaction Cross Section Data Using Artificial Neural Network." In Artificial Intelligence and Applied Mathematics in Engineering Problems, 935–39. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-36178-5_82.

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Dollhopf, Sherry, HÉctor Ayala-Del-RÍo, Syed Hashsham, and James Tiedje. "Section 7 update: Multivariate statistical methods and artificial neural networks for analysis of microbial community molecular fingerprints." In Molecular Microbial Ecology Manual, 3349–87. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-2177-0_706.

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Teixeira, Roselito A., Antônio P. Braga, Rodney R. Saldanha, Ricardo H. C. Takahashi, and Talles H. Medeiros. "The Usage of Golden Section in Calculating the Efficient Solution in Artificial Neural Networks Training by Multi-objective Optimization." In Lecture Notes in Computer Science, 289–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74690-4_30.

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Conference papers on the topic "Artificial section"

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"Section 9: Artificial Intelligence Systems." In 2022 International Conference on Quality Management, Transport and Information Security, Information Technologies (IT&QM&IS). IEEE, 2022. http://dx.doi.org/10.1109/itqmis56172.2022.9976877.

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"Section 9. Artificial Intelligence Systems." In 2021 International Conference on Quality Management, Transport and Information Security, Information Technologies (IT&QM&IS). IEEE, 2021. http://dx.doi.org/10.1109/itqmis53292.2021.9642888.

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"SECTION 3: Artificial Intelligence and Machine Learning." In 2020 10th International Conference on Advanced Computer Information Technologies (ACIT). IEEE, 2020. http://dx.doi.org/10.1109/acit49673.2020.9208952.

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K, Kalaivani, Yaswin Vikhaash R R, Mani Bharathi P A A, Kuttambakam Bhavana C H, and Mahalaxmi R. "An Artificial Eye for Blind People." In 2022 IEEE Delhi Section Conference (DELCON). IEEE, 2022. http://dx.doi.org/10.1109/delcon54057.2022.9752999.

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"SECTION 5: Artificial Intelligence and Cognitive Systems 2022." In 2022 12th International Conference on Advanced Computer Information Technologies (ACIT). IEEE, 2022. http://dx.doi.org/10.1109/acit54803.2022.9913077.

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Malhotra, Neil, Ram Suri, Puru Verma, and Rajesh Kumar. "Smart Artificial Intelligence Based Online Proctoring System." In 2022 IEEE Delhi Section Conference (DELCON). IEEE, 2022. http://dx.doi.org/10.1109/delcon54057.2022.9753313.

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Soni, Kanishka, and Yasha Hasija. "Artificial Intelligence Assisted Drug Research and Development." In 2022 IEEE Delhi Section Conference (DELCON). IEEE, 2022. http://dx.doi.org/10.1109/delcon54057.2022.9753179.

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Taheri, Amir, and Ali Hooshmandkoochi. "Optimum Selection of Artificial Lift System for Iranian Heavy Oil Fields." In SPE Western Regional/AAPG Pacific Section/GSA Cordilleran Section Joint Meeting. Society of Petroleum Engineers, 2006. http://dx.doi.org/10.2118/99912-ms.

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Bhartiya, Namrata, Namrata Jangid, Sheetal Jannu, Purvika Shukla, and Radhika Chapaneri. "Artificial Neural Network Based University Chatbot System." In 2019 IEEE Bombay Section Signature Conference (IBSSC). IEEE, 2019. http://dx.doi.org/10.1109/ibssc47189.2019.8973095.

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Alarfaj, Malik K., Abdulazeez Abdulraheem, and Yasser R. Busaleh. "Estimating Dewpoint Pressure Using Artificial Intelligence." In SPE Saudi Arabia section Young Professionals Technical Symposium. Society of Petroleum Engineers, 2012. http://dx.doi.org/10.2118/160919-ms.

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Reports on the topic "Artificial section"

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Rinta-Kahila, Tapani, Ida Someh, Marta Indulska, and I. Ryan. Building Artificial Intelligence capability in the public sector. Brisbane, Australia; Canberra, Australia: The University of Queensland; SAP Institute for Digital Government, January 2021. http://dx.doi.org/10.14264/91738b9.

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Agarwal, Smisha, Madhu Jalan, Holly C. Wilcox, Ritu Sharma, Rachel Hill, Emily Pantalone, Johannes Thrul, Jacob C. Rainey, and Karen A. Robinson. Evaluation of Mental Health Mobile Applications. Agency for Healthcare Research and Quality (AHRQ), May 2022. http://dx.doi.org/10.23970/ahrqepctb41.

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Background. Mental health mobile applications (apps) have the potential to expand the provision of mental health and wellness services to traditionally underserved populations. There is a lack of guidance on how to choose wisely from the thousands of mental health apps without clear evidence of safety, efficacy, and consumer protections. Purpose. This Technical Brief proposes a framework to assess mental health mobile applications with the aim to facilitate selection of apps. The results of applying the framework will yield summary statements on the strengths and limitations of the apps and are intended for use by providers and patients/caregivers. Methods. We reviewed systematic reviews of mental health apps and reviewed published and gray literature on mental health app frameworks, and we conducted four Key Informant group discussions to identify gaps in existing mental health frameworks and key framework criteria. These reviews and discussions informed the development of a draft framework to assess mental health apps. Iterative testing and refinement of the framework was done in seven successive rounds through double application of the framework to a total of 45 apps. Items in the framework with an interrater reliability under 90 percent were discussed among the evaluation team for revisions of the framework or guidance. Findings. Our review of the existing frameworks identified gaps in the assessment of risks that users may face from apps, such as privacy and security disclosures and regulatory safeguards to protect the users. Key Informant discussions identified priority criteria to include in the framework, including safety and efficacy of mental health apps. We developed the Framework to Assist Stakeholders in Technology Evaluation for Recovery (FASTER) to Mental Health and Wellness and it comprises three sections: Section 1. Risks and Mitigation Strategies, assesses the integrity and risk profile of the app; Section 2. Function, focuses on descriptive aspects related to accessibility, costs, organizational credibility, evidence and clinical foundation, privacy/security, usability, functions for remote monitoring of the user, access to crisis services, and artificial intelligence (AI); and Section 3. Mental Health App Features, focuses on specific mental health app features, such as journaling and mood tracking. Conclusion. FASTER may be used to help appraise and select mental health mobile apps. Future application, testing, and refinements may be required to determine the framework’s suitability and reliability across multiple mental health conditions, as well as to account for the rapidly expanding applications of AI, gamification, and other new technology approaches.
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Arnold, Zachary, Roxanne Heston, Remco Zwetsloot, and Tina Huang. Immigration Policy and the U.S. AI Sector. Center for Security and Emerging Technology, September 2019. http://dx.doi.org/10.51593/20190009.

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As the artificial intelligence field becomes more developed globally, the United States will continue to rely on foreign AI talent to stay ahead of the curve. Here are our preliminary recommendations to maintain current U.S. leadership, bolster the domestic AI workforce and improve the outlook for the future.
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Mehmood, Hamid, Surya Karthik Mukkavilli, Ingmar Weber, Atsushi Koshio, Chinaporn Meechaiya, Thanapon Piman, Kenneth Mubea, Cecilia Tortajada, Kimberly Mahadeo, and Danielle Liao. Strategic Foresight to Applications of Artificial Intelligence to Achieve Water-related Sustainable Development Goals. United Nations University Institute for Water, Environment and Health, April 2020. http://dx.doi.org/10.53328/lotc2968.

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The report recommends that: 1) Policymakers should conduct holistic assessments of social, economic, and cultural factors before AI adoption in the water sector, as prospective applications of AI are case- specific. It is also important to conduct baseline studies to measure the implementation capacity, return on investment, and impact of intervention. 2) To ensure positive development outcomes, policies regarding the use of AI for water-related challenges should be coupled with capacity and infrastructure development policies. Capacity development policies need to address the AI and Information and Communications Technology (ICT) needs for the AI-related skill development of all water-related stakeholders. Infrastructure development policies should address the underlying requirements of computation, energy, data generation, and storage. The sequencing of these policies is critical. 3) To mitigate the predicted job displacement that will accompany AI-led innovation in the water sector, policies should direct investments towards enabling a skilled workforce by developing water sector-related education at all levels. This skilled workforce should be strategically placed to offset dependency on the private sector. 4) Water-related challenges are cross-cutting running from grassroots to the global level and require an understanding of the water ecosystem. It is important for countries connected by major rivers and watersheds to collaborate in developing policies that advance the use of AI to address common water-related challenges. 5) A council or agency with representation from all stakeholders should be constituted at the national level, to allow for the successful adoption of AI by water agencies. This council or agency should be tasked with the development of policies, guidelines, and codes of conduct for the adoption of AI in the water-sector. These key policy recommendations can be used as primary guidelines for the development of strategies and plans to use AI to help achieve water-related SDGs.
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Rudd, Ian. Leveraging Artificial Intelligence and Robotics to Improve Mental Health. Intellectual Archive, July 2022. http://dx.doi.org/10.32370/iaj.2710.

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Artificial Intelligence (AI) is one of the oldest fields of computer science used in building structures that look like human beings in terms of thinking, learning, solving problems, and decision making (Jovanovic et al., 2021). AI technologies and techniques have been in application in various aspects to aid in solving problems and performing tasks more reliably, efficiently, and effectively than what would happen without their use. These technologies have also been reshaping the health sector's field, particularly digital tools and medical robotics (Dantas & Nogaroli, 2021). The new reality has been feasible since there has been exponential growth in the patient health data collected globally. The different technological approaches are revolutionizing medical sciences into dataintensive sciences (Dantas & Nogaroli, 2021). Notably, with digitizing medical records supported the increasing cloud storage, the health sector created a vast and potentially immeasurable volume of biomedical data necessary for implementing robotics and AI. Despite the notable use of AI in healthcare sectors such as dermatology and radiology, its use in psychological healthcare has neem models. Considering the increased mortality and morbidity levels among patients with psychiatric illnesses and the debilitating shortage of psychological healthcare workers, there is a vital requirement for AI and robotics to help in identifying high-risk persons and providing measures that avert and treat mental disorders (Lee et al., 2021). This discussion is focused on understanding how AI and robotics could be employed in improving mental health in the human community. The continued success of this technology in other healthcare fields demonstrates that it could also be used in redefining mental sicknesses objectively, identifying them at a prodromal phase, personalizing the treatments, and empowering patients in their care programs.
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Arnold, Zachary, Rebecca Gelles, and Ilya Rahkovsky. Identifying AI-Related Companies: A Conceptual Outline and Proof of Concept. Center for Security and Emerging Technology, July 2020. http://dx.doi.org/10.51593/20200018.

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Artificial intelligence is of increasing interest to the private sector, but what exactly constitutes an “AI company?” This data brief offers a flexible, data-driven framework for identifying the companies most relevant in this field at the moment, providing policymakers and researchers with a tool for mapping technology transfer risks and gauging the overall health of America’s AI sector.
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Sprague, Joshua, David Kushner, James Grunden, Jamie McClain, Benjamin Grime, and Cullen Molitor. Channel Islands National Park Kelp Forest Monitoring Program: Annual report 2014. National Park Service, August 2022. http://dx.doi.org/10.36967/2293855.

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Channel Islands National Park (CHIS) has conducted long-term ecological monitoring of the kelp forests around San Miguel, Santa Rosa, Santa Cruz, Anacapa and Santa Barbara Islands since 1982. The original permanent transects were established at 16 sites between 1981 and 1986 with the first sampling beginning in 1982, this being the 33rd year of monitoring. An additional site, Miracle Mile, was established at San Miguel Island in 2001 by a commercial fisherman with assistance from the park. Miracle Mile was partially monitored from 2002 to 2004, and then fully monitored (using all KFM protocols) since 2005. In 2005, 16 additional permanent sites were established to collect baseline data from inside and adjacent to four marine reserves that were established in 2003. Sampling results from all 33 sites mentioned above are included in this report. Funding for the Kelp Forest Monitoring Program (KFM) in 2014 was provided by the National Park Service (NPS). The 2014 monitoring efforts utilized 49 days of vessel time to conduct 1,040 dives for a total of 1,059 hours of bottom time. Population dynamics of a select list of 71 “indicator species” (consisting of taxa or categories of algae, fish, and invertebrates) were measured at the 33 permanent sites. In addition, population dynamics were measured for all additional species of fish observed at the sites during the roving diver fish count. Survey techniques follow the CHIS Kelp Forest Monitoring Protocol Handbook (Davis et al. 1997) and an update to the sampling protocol handbook currently being developed (Kushner and Sprague, in progress). The techniques utilize SCUBA and surface-supplied-air to conduct the following monitoring protocols: 1 m2 quadrats, 5 m2 quadrats, band transects, random point contacts, fish transects, roving diver fish counts, video transects, size frequency measurements, and artificial recruitment modules. Hourly temperature data were collected using remote temperature loggers at 32 sites, the exception being Miracle Mile where there is no temperature logger installed. This annual report contains a brief description of each site including any notable observations or anomalies, a summary of methods used, and monitoring results for 2014. All the data collected during 2014 can be found in the appendices and in an Excel workbook on the NPS Integrated Resource Management Applications (IRMA) portal. In the 2013 annual report (Sprague et al. 2020) several changes were made to the appendices. Previously, annual report density and percent cover data tables only included the current year’s data. Now, density and percent cover data are presented in graphical format and include all years of available monitoring data. Roving diver fish count (RDFC), fish size frequency, natural habitat size frequency, and Artificial Recruitment Module (ARM) size frequency data are now stored on IRMA at https://irma.nps.gov/DataStore/Reference/Profile/2259651. The temperature data graphs in Appendix L include the same graphs that were used in past reports, but include additional violin plot sections that compare monthly means from the current year to past years. In addition to the changes listed above, the layout of the discussion section was reordered by species instead of by site. The status of kelp forests differed among the five park islands. This is a result of a combination of factors including but not limited to, oceanography, biogeography and associated differences in species abundance and composition, as well as sport and commercial fishing pressure. All 33 permanent sites were established in areas that had or were historically known to have had kelp forests in the past. In 2014, 15 of the 33 sites monitored were characterized as developing kelp forest, kelp forest or mature kelp forest. In addition, three sites were in a state of transition. Two sites were part kelp forest and part dominated by Strongylocentrotus purpuratus...
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8

Stankovic, Mirjana, and Nikola Neftenov. Cross Pollination and Digitalization of Public Sector Data: Opportunities and Challenges. Inter-American Development Bank, August 2022. http://dx.doi.org/10.18235/0004355.

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This report aims to aid governments in Latin America and the Caribbean in embracing the opportunities public sector data utilization and artificial intelligence (AI) deployment can provide in achieving a circular economy model and the UNs Sustainable Development Goals (SDGs). For such purpose, the report provides a novel concept of sharing data between key players that we have named data cross-pollination. Drawing on this concept, it considers four SDGs, i.e., energy, sustainable food systems, reducing pollution, and smart cities. Building on case studies and initiatives, the report highlights the main challenges and opportunities of utilizing data to achieve a circular economy model and sustainable development. It also looks into the potential of AI to enrich such data cross-pollination and focuses on potential applications of AI in circular innovation that can be transposed in the public sector.
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9

Solovyanenko, Nina I. Legal features of innovative (digital) entrepreneurship in the agricultural and food sector. DOI CODE, 2021. http://dx.doi.org/10.18411/0131-5226-2021-70008.

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Modern agricultural production and food trade are involved in the process of digital transformation, which is a cardinal factor of sustainable development and is carried out on the basis of IT platforms, the Internet of Things, cloud computing, big data, artificial intelligence, blockchain technologies. The COVID-19 pandemic has increased the dependence of these sectors of the economy on information and communication technology infrastructure and services. At the same time, the slow updating of legislation, which lags behind the constantly improving digital technologies, not only hinders their implementation, but also is a source of a number of social and legal problems. A modern regulatory framework based on digital strategies should strengthen "smart agriculture". In Russia, the legal mechanism of digital transformation and development of the national platform "Digital Agriculture" should be supported by updated basic legislation.
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10

Abuhamad, Grace, Cory Salveson, Lilia Stubrin, and Carlos Braga. Abierta configuration options Inteligencia artificial en el sector de maquinaria agrícola de Argentina: diagnóstico de madurez y recomendaciones de política para acelerar la adopción. Inter-American Development Bank, February 2022. http://dx.doi.org/10.18235/0004000.

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Durante la última década, el ritmo de mejora de la inteligencia artificial (IA) sorprendió incluso a los más expertos, creando nuevos mercados y oportunidades de progreso en numerosas áreas. En el 2020, el BID decidió explorar opciones de política pública para promover la adopción de la IA y para ello, seleccionó el sector de la maquinaria agrícola de Argentina. Con cerca de 1,200 empresas, se trata de una industria intensiva en ciencia, tecnología e innovación, susceptible de introducir mejoras en autonomía y automatización en las máquinas existentes, desarrollar nuevos dispositivos y servicios, y optimizar procesos de negocio. Para el desarrollo de este proyecto, el BID contrató a Element AI, una de las compañías líderes en el desarrollo de IA a nivel mundial, para (1) evaluar la madurez del sector en la adopción de IA, a partir de un modelo de madurez que distingue cinco dimensiones (estrategia, datos, tecnología, recursos humanos y gobernanza), a lo largo de cinco etapas de madurez a través de las que evolucionan las empresas (exploración, experimentación, formalización, optimización y transformación), y (2) proponer recomendaciones para la acción, según tres perfiles de beneficiarios: firma, clúster y sector público. Este informe presenta los resultados de la evaluación de la madurez y una serie de conclusiones y propuestas, que pueden ser útiles para las futuras políticas públicas que estimulen el desarrollo y la adopción de aplicaciones de IA en el sector de la maquinaria agrícola argentina, y también en otros sectores industriales de la región.
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