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Journal articles on the topic 'Artificial section'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

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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4

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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Bhasin, Shivam, Siddharth Garg, and Francesco Regazzoni. "Special Section on Attacking and Protecting Artificial Intelligence." CAAI Transactions on Intelligence Technology 6, no. 1 (March 2021): 1–2. http://dx.doi.org/10.1049/cit2.12023.

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Fofi, David. "Special Section on Quality Control by Artificial Vision." Journal of Electronic Imaging 17, no. 3 (July 1, 2008): 031101. http://dx.doi.org/10.1117/1.2959057.

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13

Feinberg, B. "Artificial preterm labor in private practice." Journal of obstetrics and women's diseases 7, no. 1 (September 2, 2020): 67–69. http://dx.doi.org/10.17816/jowd7167-69.

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Unfortunately, The benefits of Lister's antiseptic science, says Fehling, have been taken advantage of by gynecology to a much greater extent than obstetrics. From obstetric operations to caesarean section, Lister's scholarship brought more benefits than forceps and perforations. It would therefore be desirable that in the future, artificial premature birth under the influence of anti- and asepsis would give both the mother and the fetus better results than at the present time, and then only this operative aid in a state will be replaced, as a cesarean section with conditional shown and perforated.

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14

Flintsch, Gerardo W., and John P. Zaniewski. "Expert Project Recommendation Procedure for Arizona Department of Transportation’s Pavement Management System." Transportation Research Record: Journal of the Transportation Research Board 1592, no. 1 (January 1997): 26–34. http://dx.doi.org/10.3141/1592-04.

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The Arizona Department of Transportation (ADOT) uses a network-level pavement management system to determine budget requirements for its annual pavement preservation program. Although this is a valuable tool for preservation programming, it does not assist the engineers with the selection of projects and rehabilitation treatments. The documented research was designed to enhance the capability of ADOT’s pavement management system to include project selection. An automatic project recommendation procedure was developed and implemented in a user-friendly, modular computer program. This automatic system is expected to reduce considerably the effort required to develop the preservation programs. It should improve the consistency of the decision process. The analysis starts with a section delineation procedure that delineates uniform roadway sections. It then computes the remaining service life of each uniform section by using linear performance equations and trigger points defined for each condition indicator. An artificial neural network simulator is used to screen and recommend roadway sections for the preservation program. The trained artificial neural network prepares a list of candidate sections, using the criteria learned from past selections and the current condition of all pavement sections. This preliminary list of candidate sections is further analyzed by a project recommendation procedure. This procedure recommends a preservation treatment, assigns a priority rating to each section in the list, and sorts the projects by priority. Funding is assigned to the highest-priority sections within each roadway group until the budget recommendation provided by the network optimization process is reached.

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Dunn, Bruce L., and Jon T. Lindstrom. "Intersectional Hybridization among Trichostema Species." HortScience 43, no. 2 (April 2008): 310–13. http://dx.doi.org/10.21273/hortsci.43.2.310.

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Controlled reciprocal crosses between Trichostema lanatum Benth. (section Chromocephalum F.H. Lewis) with Trichostema arizonicum A. Gray (section Paniculatum F.H. Lewis) and Trichostema purpusii Brandegee (section Rhodanthum Lewis) were successful in generating the first artificial hybrids in the genus. Crosses where T. lanatum was used as the female were unsuccessful. Leaf and floral morphology among the hybrids was typically intermediate. Female sterility was seen in the T. arizonicum × T. lanatum hybrids, and these hybrids also produced abnormally small, nonviable pollen grains. Propagation procedures are also presented. Although these species may be in different sections, their crossability suggests that they are closely related.

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Chrpa, Lukas, and Mauro Vallati. "Planning with Critical Section Macros: Theory and Practice." Journal of Artificial Intelligence Research 74 (June 9, 2022): 691–732. http://dx.doi.org/10.1613/jair.1.13269.

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Macro-operators (macros) are a well-known technique for enhancing performance of planning engines by providing “short-cuts” in the state space. Existing macro learning systems usually generate macros by considering most frequent action sequences in training plans. Unfortunately, frequent action sequences might not capture meaningful activities as a whole, leading to a limited beneficial impact for the planning process. In this paper, inspired by resource locking in critical sections in parallel computing, we propose a technique that generates macros able to capture whole activities in which limited resources (e.g., a robotic hand, or a truck) are used. Specifically, such a Critical Section macro starts by locking the resource (e.g., grabbing an object), continues by using the resource (e.g., manipulating the object) and finishes by releasing the resource (e.g., dropping the object). Hence, such a macro bridges states in which the resource is locked and cannot be used. We also introduce versions of Critical Section macros dealing with multiple resources and phased locks. Usefulness of macros is evaluated using a range of state-of-the-art planners, and a large number of benchmarks from the deterministic and learning tracks of recent editions of the International Planning Competition.

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Ikram Badshah, Zakiya Rubab Mohsin, and Jan Alam. "Local Perception about Caesarian Section among Post Caesarian Section Women in Pakistan." sjesr 4, no. 2 (May 25, 2021): 299–308. http://dx.doi.org/10.36902/sjesr-vol4-iss2-2021(299-308).

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Birthing is a critical moment in the life of a mother. The biomedical practice of the Caesarian Section (C-section) does not exist in a vacuum but is under the influence of the sociocultural environment. However, deciding between methods of birth and the perception about the C-section shows a gap and dearth in the present literature. This paper aims at understanding what social and cultural factors construct the perceptions and experiences of the Caesarian Section among post-C-section- women belonging to different socio-economic statuses. Moreover, it explores how these factors influence Pakistani women’s decision-making regarding childbirth methods. The paper uses a qualitative yet multi-sited locale approach, employing semi-structured interviews from 20 post-C-section women mainly from Islamabad and Rawalpindi region; 10 women belong to lower socio-economic status whereas, 10 to the upper one. Different themes from data were identified and obtained for analysis. The perception and experience of the C-section fluctuate with social, economic, and cultural factors. The influence of biomedical and intra-household politics on the decision of C-section is much conspicuous and evident. Affluent families practice C-sections under dominant power dynamics without any reasoning. For those who can afford C-section, is perceived as a luxury and artificial motherhood in the eyes of ‘’the others’’ whereas, normal birthing was true and natural motherhood. The social construction of the C-section suggests that social and cultural forces play a decisive role. C-section is only acceptable if there is an emergency otherwise natural birth is the most suitable method of childbirth. Along with advocating C-sections in critical medical conditions, an awareness campaign against C-sections is also imperative for it has severe consequences.

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Mériaudeau, Fabrice, and Amir Malik Saeed. "Special Section Guest Editorial:Special Section on Quality Control by Artificial Vision: Nonconventional Imaging Systems." Journal of Electronic Imaging 24, no. 6 (December 22, 2015): 061101. http://dx.doi.org/10.1117/1.jei.24.6.061101.

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Smith, David. "News section." AI & Society 4, no. 2 (April 1990): 168–70. http://dx.doi.org/10.1007/bf01889646.

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Ennals, Richard. "New section." AI & Society 6, no. 3 (July 1992): 299–301. http://dx.doi.org/10.1007/bf02472803.

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Vaux, Janet, and Robert Dale. "Review section." AI & Society 1, no. 1 (July 1987): 72–76. http://dx.doi.org/10.1007/bf01905894.

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Smith, David. "News section." AI & Society 4, no. 3 (July 1990): 247–56. http://dx.doi.org/10.1007/bf01889944.

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Werner, Eric. "News section." AI & Society 3, no. 3 (July 1989): 260–67. http://dx.doi.org/10.1007/bf01891437.

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Iliya, Sunday, and Ferrante Neri. "Towards Artificial Speech Therapy: A Neural System for Impaired Speech Segmentation." International Journal of Neural Systems 26, no. 06 (July 19, 2016): 1650023. http://dx.doi.org/10.1142/s0129065716500234.

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This paper presents a neural system-based technique for segmenting short impaired speech utterances into silent, unvoiced, and voiced sections. Moreover, the proposed technique identifies those points of the (voiced) speech where the spectrum becomes steady. The resulting technique thus aims at detecting that limited section of the speech which contains the information about the potential impairment of the speech. This section is of interest to the speech therapist as it corresponds to the possibly incorrect movements of speech organs (lower lip and tongue with respect to the vocal tract). Two segmentation models to detect and identify the various sections of the disordered (impaired) speech signals have been developed and compared. The first makes use of a combination of four artificial neural networks. The second is based on a support vector machine (SVM). The SVM has been trained by means of an ad hoc nested algorithm whose outer layer is a metaheuristic while the inner layer is a convex optimization algorithm. Several metaheuristics have been tested and compared leading to the conclusion that some variants of the compact differential evolution (CDE) algorithm appears to be well-suited to address this problem. Numerical results show that the SVM model with a radial basis function is capable of effective detection of the portion of speech that is of interest to a therapist. The best performance has been achieved when the system is trained by the nested algorithm whose outer layer is hybrid-population-based/CDE. A population-based approach displays the best performance for the isolation of silence/noise sections, and the detection of unvoiced sections. On the other hand, a compact approach appears to be clearly well-suited to detect the beginning of the steady state of the voiced signal. Both the proposed segmentation models display outperformed two modern segmentation techniques based on Gaussian mixture model and deep learning.

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Burghardt, Alicia D., and Shirley M. Espert. "Phylogeny of Prosopis (Leguminosae) as shown by morphological and biochemical evidence." Australian Systematic Botany 20, no. 4 (2007): 332. http://dx.doi.org/10.1071/sb06043.

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Prosopis L. is a rather primitive genus within the Leguminosae–Mimosoideae. This genus has been divided into five sections on the basis especially of the vegetative diversification of the spines. Three of the sections, Algarobia, Monilicarpa and Strombocarpa, are distributed in America. In order to elucidate systematic relationships between the American sections of Prosopis, a morphological and biochemical phylogeny were obtained. Twenty-two morphological characters were scored for 27 species of Prosopis and the outgroup taxon following polyacrilamide gel electrophoresis of seed storage proteins. The results obtained clearly prove that the secction Strombocarpa is a natural taxon. The section Algarobia, on the other hand, seems to comprise an artificial grouping of species. Members of the series Denudantes appear isolated from the remaining species, therefore this taxon should be treated as a new section within Prosopis. The section Algarobia should be circumscribed to series Chilenses, Ruscifoliae and Pallidae, which are always united in a monophyletic clade. Finally, no evidence was found to confirm the existence of the section Monilicarpa.

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Chen, Chi-Yuan, Wei Quan, Nan Cheng, Shui Yu, Jong-Hyouk Lee, Gregorio Martinez Perez, Hongke Zhang, and Shiuhpyng Shieh. "IEEE Access Special Section Editorial: Artificial Intelligence in Cybersecurity." IEEE Access 8 (2020): 163329–33. http://dx.doi.org/10.1109/access.2020.3021604.

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Qadir, Junaid, Kok-Lim Alvin Yau, Muhammad Ali Imran, Qiang Ni, and Athanasios V. Vasilakos. "IEEE ACCESS SPECIAL SECTION EDITORIAL: ARTIFICIAL INTELLIGENCE ENABLED NETWORKING." IEEE Access 3 (2015): 3079–82. http://dx.doi.org/10.1109/access.2015.2507798.

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Pinoli, Jean-Charles. "Special Section Guest Editorial: Quality Control by Artificial Vision." Journal of Electronic Imaging 21, no. 2 (June 20, 2012): 021101. http://dx.doi.org/10.1117/1.jei.21.2.021101.

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Gleason, Shaun S. "Special Section Guest Editorial: Quality Control for Artificial Vision." Journal of Electronic Imaging 19, no. 3 (July 1, 2010): 031201. http://dx.doi.org/10.1117/1.3497000.

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Sethi, Ishwar K. "Special section on artificial neural networks for machine vision." Machine Vision and Applications 8, no. 5 (September 1995): 261. http://dx.doi.org/10.1007/bf01211487.

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Krupinski, Elizabeth A., Paul Kinahan, and Patrick La Riviere. "Special Section Guest Editorial: Artificial Intelligence in Medical Imaging." Journal of Medical Imaging 6, no. 01 (December 22, 2018): 1. http://dx.doi.org/10.1117/1.jmi.6.1.011001.

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Pożarycki, Andrzej. "Pavement diagnosis accuracy with controlled application of artificial neural network." Baltic Journal of Road and Bridge Engineering 10, no. 4 (December 15, 2015): 355–64. http://dx.doi.org/10.3846/bjrbe.2015.45.

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Results of research studies, the amount of input data available in pavement management system databases, and artificial intelligence methods serve as versatile tools, well-suited for the analysis conducted as a part of pavement management system. The key source of new and to be employed knowledge is provided. In terms of e.g. assessing thickness of bituminous pavement layers, the default solution is pavement drilling, but for the purposes of pavement management it is prohibitively expensive. This paper attempts to test the original concept of employing an empirical relationship in an algorithm verifying results produced by the artificial neural network method. The assumed multistage asphalt pavement layer thickness identification control process boils down to evaluating test results of the road section built using both, reinforced and non-reinforced pavement structure. By default, the artificial neural network training set has not included the reinforced pavement sections. Hence, it has been possible to identify “perturbations” in assumptions underlying the training set. Pavement test section points’ results are indicated in the automated manner, which, in line with implemented methods, is not generated by perturbations caused by divergence between actual pavement structure and assumptions taken for purposes of building pavement management system database, and the artificial neural network learning dataset is based on.

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Manoonpong, Poramate, Luca Patanè, Xiaofeng Xiong, Ilya Brodoline, Julien Dupeyroux, Stéphane Viollet, Paolo Arena, and Julien R. Serres. "Insect-Inspired Robots: Bridging Biological and Artificial Systems." Sensors 21, no. 22 (November 16, 2021): 7609. http://dx.doi.org/10.3390/s21227609.

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This review article aims to address common research questions in hexapod robotics. How can we build intelligent autonomous hexapod robots that can exploit their biomechanics, morphology, and computational systems, to achieve autonomy, adaptability, and energy efficiency comparable to small living creatures, such as insects? Are insects good models for building such intelligent hexapod robots because they are the only animals with six legs? This review article is divided into three main sections to address these questions, as well as to assist roboticists in identifying relevant and future directions in the field of hexapod robotics over the next decade. After an introduction in section (1), the sections will respectively cover the following three key areas: (2) biomechanics focused on the design of smart legs; (3) locomotion control; and (4) high-level cognition control. These interconnected and interdependent areas are all crucial to improving the level of performance of hexapod robotics in terms of energy efficiency, terrain adaptability, autonomy, and operational range. We will also discuss how the next generation of bioroboticists will be able to transfer knowledge from biology to robotics and vice versa.

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Mudita and Deepali Gupta. "The Aspects of Artificial Intelligence in Software Engineering." Journal of Computational and Theoretical Nanoscience 17, no. 9 (July 1, 2020): 4635–42. http://dx.doi.org/10.1166/jctn.2020.9291.

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Software Engineering is the fundamental methodology used in the process of developing the software. Software Development Life Cycle (SDLC) is the backbone of software engineering. SDLC is emerging in several forms to support software development at different phases. SDLC plays as a role of guide for engineers that are involved from traditional desktop application development to much trending development. The new emerging technologies accelerate the process of software engineering, resulting in saving time and resources and enhance the quality of software systems. This paper focuses on technologies used to accelerate the process of software engineering in solving problems associated with its phases. The first section of this paper contains an introduction to Software Engineering (SE) and Artificial Intelligence (AI). The next section describes the aspects of emerging technologies in software engineering. After this, the role of AI in SE is discussed followed by a conclusion in the last section.

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Nerella, Santhi Sree, Sudheer V. V. S. Nakka, and Bhramara Panitapu. "Mathematical Modeling of Closed Loop Pulsating Heat Pipe by Using Artificial Neural Networks." International Journal of Heat and Technology 39, no. 3 (June 30, 2021): 955–62. http://dx.doi.org/10.18280/ijht.390332.

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Pulsating heat pipe is one of the prominent technology for thermal management of electronic devices. It consists of three sections namely evaporator, adiabatic and condenser section. PHP is a two phase passive device having efficient and quick ability of transferring heat from evaporator section to condenser section. At first an 8 turn pulsating heat pipe of closed loop ends (CLPHP) with copper tube capillary dimensions is investigated experimentally for different fill ratios and for different inclinations by varying range of heat inputs. Different working fluids viz Water, Acetone, Ethanol and Methanol are considered for the experimentation. One of the recent analytical technology for modelling of CLPHPs is Artificial Neural Network (ANN) approach. The analytical models are having limited scope of applicability and they are simple in nature. The present paper describes Validation of experimental data by training prediction model ANN with available data. Three input nodes such as input heat, fill ratio and angle of inclination and one output node corresponding to PHP that is thermal resistance are considered. The feed forward neural network (FFNN) architecture is adopted for predictions. By using the physical phenomena of the system modelling are clearly known for obtaining feasible results which is main function of ANN. The predicted data validates experimental data in a satisfactory range and the results are found to be in good agreement with in the range of ± 10 percent.

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"Posters/Section 5 - Artificial Heart and Artificial Valves." International Journal of Artificial Organs 21, no. 10 (October 1998): 644–48. http://dx.doi.org/10.1177/039139889802101024.

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Thomsen, Henrik S. "New section editor for Artificial Intelligence (AI)." Acta Radiologica, October 11, 2022, 028418512211293. http://dx.doi.org/10.1177/02841851221129378.

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عرفان الخطيب, محمد. "Artificial Intelligence: Towards a Legal DefinitionAn in-depth study of the philosophical framework of artificial intelligence from a comparative legal perspective." BAU Journal - Journal of Legal Studies - مجلة الدراسات القانونية 2021, no. 1 (July 30, 2022). http://dx.doi.org/10.54729/erkf2181.

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To this date, the term artificial intelligence does not have a definite and universally accepted legal definition, which creates sterile doctrinal debates and significant confusion in the legal field. To tackle this issue, this paper aims to provide a definition of the term artificial intelligence that covers all the legal and technical aspects of this concept. This research is based on an analytical approach and is divided into two sections. In the first section, the author provides a thorough overview of the concept of artificial intelligence, both from a technical and legal point of view. In the second section, the author discusses some of the main challenges posed by artificial intelligence in the legal field. The paper concludes with key recommendations including the necessity of adopting a normative definition of the concept of artificial intelligence as opposed to a descriptive one. Similarly, the paper stresses the importance of promoting an ethical stance and a proactive as opposed to a reactive approach when it comes to dealing with legal issues involving artificial intelligence. Normativity, ethics, and governance are the key words that must be focused on to better address the ever-evolving issues of artificial intelligence in the legal field.

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"Technological Developments Section." Fuzzy Sets and Systems 79, no. 2 (April 1996): 271–76. http://dx.doi.org/10.1016/s0165-0114(96)90097-4.

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"Posters/Section 8 - Biomaterials, Biocompatibility and Artificial Cells." International Journal of Artificial Organs 21, no. 10 (October 1998): 658–62. http://dx.doi.org/10.1177/039139889802101027.

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Üncü, Yiğit Ali, Taner Danışman, and Hasan Özdoğan. "Calculations of GDR parameters for deformed nuclei using LogitBoost classifier and artificial neural network." Modern Physics Letters A, May 25, 2022. http://dx.doi.org/10.1142/s0217732322500791.

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Photo-nuclear interactions are important for investigating fundamental nuclear physics phenomena. The photo-absorption cross-section energy curve displays a wide resonance called giant dipole resonance (GDR) until 30 MeV. First, spherical and deformed nuclei have been determined by using LogitBoost classifier, and then GDR parameters for deformed nuclei have been estimated by using an artificial neural network (ANN) via Levenberg–Marquardt algorithm which has been selected for the training section. In the last step, [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] reaction cross-sections have been computed by using GDR parameters obtained ANN estimations. The mean square error, root mean square error, and [Formula: see text] are evaluated as the best performance of ANN estimates. Photo-neutron cross-section results have been compared with experimental data from the literature. Consequently, it has been found that ANN algorithms can be used to determine the GDR parameters for deformed nuclei in the lack of experimental data of photo-absorption reaction.

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"News section." AI & Society 7, no. 3 (September 1993): 272–74. http://dx.doi.org/10.1007/bf01901824.

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"News section." AI & Society 5, no. 4 (October 1991): 360–61. http://dx.doi.org/10.1007/bf02077441.

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"News section." AI & Society 6, no. 1 (January 1992): 98–99. http://dx.doi.org/10.1007/bf02472774.

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"News section." AI & Society 6, no. 2 (April 1992): 192–94. http://dx.doi.org/10.1007/bf02472782.

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"News section." AI & Society 6, no. 4 (October 1992): 398. http://dx.doi.org/10.1007/bf02472792.

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"News section." AI & Society 2, no. 3 (July 1988): 275–76. http://dx.doi.org/10.1007/bf01908555.

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"News section." AI & Society 7, no. 2 (June 1993): 180–82. http://dx.doi.org/10.1007/bf01908617.

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"News section." AI & Society 3, no. 4 (October 1989): 370. http://dx.doi.org/10.1007/bf01908628.

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"News section." AI & Society 1, no. 1 (July 1987): 77–80. http://dx.doi.org/10.1007/bf01905895.

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