Academic literature on the topic 'Intelligence tests – history'
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Journal articles on the topic "Intelligence tests – history"
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Molinari, Victoria. "Psychoanalyzing intelligence: Béla Székely’s Los Tests." Dynamis 40, no. 2 (December 31, 2020): 375–98. http://dx.doi.org/10.30827/dynamis.v40i2.17971.
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This paper aims to analyze the definition of intelligence that appeared in the book Los Tests (1946) written by BélaSzékely, a Hungarian psychologist who emigrated to Argentina in 1938. Although Székely’s work was mainly related to psychoanalysis and child psychology, the publication of this compilation of psychometric tests became one of his most influential works, in which he based his observations on the ideas of Wilhelm Stern, Sigmund Freud, and Alfred Adler. The methodology used in this article is based on a qualitative and interpretative analysis of bibliographical sources from the perspectives of the critical history of psychology and intellectual history in Argentina in the 1930s and 1940s. In using this approach, I analyze what other specialists thought of intelligence, in contrast to the ideas presented by Székely. The article approaches the issue first by briefly presenting the author in question, and his position within Hungarian and Argentinian intellectual groups. Then, it studies general understandings of ‘intelligence’ and ‘intellectual level’ in Argentina around the time that Székely’s book made its first appearance and, finally, it examines to what extent his viewpoint was different. The articulation between epistemological and historical discussions allows us to reflect not only on the transformations present in scientific constructs such as intelligence but also on the implications they had within the scientific community and on a wider social and political level. If intelligence was considered to be a neutral concept, then a mere compilation of tests would be enough for its dissemination. Székely’s book made an impact because it contributed to the availability of testing technology, the popularization of said technology, and the intelligence concept.
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Suzuki, Tomoko. "Features of japanese intelligence tests history from test developers’ perspective." Proceedings of the Annual Convention of the Japanese Psychological Association 78 (September 10, 2014): 2AM—2–001–2AM—2–001. http://dx.doi.org/10.4992/pacjpa.78.0_2am-2-001.
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Beauvais, Clémentine. "Teacher, Tester, Soldier, Spy: Psychologists Talk about Teachers in the Intelligence-Testing Movement, 1910s-1930s." History of Education Quarterly 57, no. 3 (July 19, 2017): 371–98. http://dx.doi.org/10.1017/heq.2017.16.
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This article focuses on teachers in the discourses of early twentieth-century proponents of intelligence testing in America. Teachers were often a targeted enemy in the academic literature on intelligence testing—their methods belittled, their unreliability emphasized. Yet, in part because teachers were essential for intelligence tests to be given in schools, they were also often talked about in more ambiguous ways. In particular, this paper argues that psychologists’ ways of talking to, at, and about teachers presented a relationship characterized by an originary indebtedness of teachers toward psychology. Intelligence tests, it was implied, were a gift for teachers, and psychologists’ help a favor that teachers should repay by using the tests and showing rigor, obedience, and gratefulness in doing so. Arguably, the debt was framed in such ways as to render impossible its repayment and to make illegible the potential contributions and initiatives of teachers in the intelligence-testing movement.
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Ryue, Sookhee, Haebum Lee, and Woo Taek Jeon. "The Relationship among the Learning Motivation, the Characteristics of Multiple Intelligence and Academic Achievement in Medical School Students." Korean Medical Education Review 15, no. 1 (February 28, 2013): 46–53. http://dx.doi.org/10.17496/kmer.2013.15.1.046.
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The purpose of this study was to analyze the relationship among medical students’ learning motivation, characteristics of multiple intelligence, and academic achievement. The participants were 144 medical students. The data were collected by administering learning motivation tests (self-confidence, self-efficacy, level of task, emotion of learning, learning behavior, failure tolerance, task difficulty, and academic self-efficacy), a multiple intelligence test (linguistic intelligence, logical-mathematical intelligence, musical intelligence, bodily-kinesthetic intelligence, spatial intelligence, interpersonal intelligence, intrapersonal intelligence, and naturalistic intelligence), and two semesters of grades. There is a correlation between multiple intelligences and learning motivation. Among academic self-efficacy of academic motivation, the self-control efficacy (0.28) and behavior (0.18) subscales are significantly positively correlated with academic achievement. However, the emotion subscale (-0.18) was significantly negatively correlated. Learning motivation was correlated with two of the eight multiple intelligence profiles: the intrapersonal intelligence (0.18) and bodily-kinesthetic intelligence (-0.19). The structural equation modeling analysis showed that the behavior and self-control efficacy subscales of intrapersonal intelligence had an impact on academic achievement. An analysis according to the academic achievement group showed significant differences in self-control efficacy and emotion subscales with intrapersonal intelligence. A positive relationship can be observed between learning motivation and some characteristics of multiple intelligence of medical school students. In light of the findings, it is worth examining whether we can control medical students’ learning motivation through educational programs targeting self-control efficacy and intrapersonal intelligence.
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Imanita, Myristica. "Pengaruh Metode Pembelajaran dan Kecerdasan Interpersonal Terhadap Hasil Belajar Sejarah Siswa SMA." Jurnal Pendidikan Sejarah 3, no. 1 (April 29, 2017): 45. http://dx.doi.org/10.21009/jps.031.05.
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This study aimed to determine the effect of learning methods and student’s intrepersonal intelligence on the outcome of history learning on the students. This research is quantitative research using design treatment by level 2x2 The research date was taken from the observation, tests and questionnaires. The results showedthat(1) history learning outcome of students who follow STAD instructional methods higher than students whofollow conventional linstructional methods, (2) there is interaction effect between instructional methods and interpersonal intelligence on history learning outcome of students, (3) history learning outcomesof studentswhofollow STAD instructionalmethodwithhighinterpersonalintelligence, higher thanstudents who followconventional linstructionalmethod, (4)historylearning outcomesof studentswhofollow STAD instuctionalmethodswithlowinterpersonalintelligence, lower thanstudents who followconventional instructional methods
Keywords : History learning outcome, instructional method, interpersonal intelligence
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Conzelmann, Kristin, Susanne Weis, and Heinz-Martin Süß. "New Findings About Social Intelligence." Journal of Individual Differences 34, no. 3 (August 1, 2013): 119–37. http://dx.doi.org/10.1027/1614-0001/a000106.
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Social intelligence (SI) is an ability construct with a long history in scientific psychology which has yet to be clearly established. SI tests show low convergent validity and can hardly be distinguished from academic intelligence. This may be the result of conceptual ambiguity and a lack of reliable and valid performappance tests that apply nonverbal stimuli. The Magdeburg Test of Social Intelligence (MTSI) is a new multimedia-based performance test battery relying on a potential-based concept of SI. It presently comprises subtests for social understanding, social memory, and social perception, each of which is measured with real auditory, video-based, pictorial, and verbal task material. It applies target scoring to the social understanding tasks. Two studies with 127 and 190 participants, respectively, examined the psychometric properties and construct validity of the MTSI. Discriminant construct validation was conducted with well-established academic intelligence and personality tests. The findings revealed satisfactory psychometric properties for nearly all of the 22 tasks. A general SI and a social perception factor were not substantiated. Social understanding was separate from academic intelligence, whereas social memory and social perception tasks showed systematic correlations with academic intelligence. The SI tasks were not systematically related to personality traits.
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Cicciola, Elisabetta, Renato Foschi, and Giovanni Pietro Lombardo. "Making up intelligence scales: De Sanctis’s and Binet’s tests, 1905 and after." History of Psychology 17, no. 3 (August 2014): 223–36. http://dx.doi.org/10.1037/a0033740.
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Nikolaeva, A. Yu, Yu A. Burdukova, O. S. Alekseeva, I. E. Rzhanova, and V. S. Britova. "Gender Aspect of Fluid Intelligence Diagnostics." Клиническая и специальная психология 9, no. 4 (2020): 99–114. http://dx.doi.org/10.17759/cpse.2020090405.
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The study of fluid intelligence has a long history. The term “fluid intelligence” was proposed by R. Cattell in the 40s of the last century. According Cattell, fluid intelligence, along with crystallized intelligence, were fundamental factors in the structure of intelligence. With the further development of psychological science and the improvement of data analysis methods, other schemes of cognitive abilities were proposed, however, almost all of them included fluid intelligence as one of the main factor. In many studies the connection of fluid intelligence, working memory and the prefrontal cortex was demonstrated, the influence of fluid intelligence on the success of learning was proved. However, the question about gender differences in fluid intelligence is still open. In the presented study, two tests were selected for the diagnosis of fluid intelligence – Wechsler Intelligence Scale for Children – 5th edition – WISC–V and the Kaufman Assessment Battery for Children – 2nd edition KABC–II. Both of these tests contain fluid intelligence scales. In the WISC–V, the Fluid Reasoning Index includes two subtests: Matrix Reasoning, Figure Weights; in the KABC–II, the Gf Scale also consists of two subtests: Story Completion and Pattern Reasoning. The sample include 48 children. The average age was 9,5 years, 52% were boys. All children passed both intelligence tests completely. Comparison of the test results did not reveal gender differences in the fluid intelligence index. However, the correlation structure of the results of both tests was different in the group of boys compared with the group of girls (in the group of boys, significantly more relationships were found out than in the group of girls), which confirms the hypothesis that the structure of fluid intelligence is dependent on gender.
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CHÁÁVEZ-GARCÍÍA, MIROSLAVA. "Intelligence Testing at Whittier School, 1890-1920." Pacific Historical Review 76, no. 2 (May 1, 2007): 193–228. http://dx.doi.org/10.1525/phr.2007.76.2.193.
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This article examines the intersections of youth, race, and science in early twentieth-century California. It explores how scientific researchers, reform school administrators, and social reformers at Whittier State School advocated the use of intelligence tests to determine the causes of delinquency. Through the process of testing, they identified a disproportionate number of delinquent boys of color-Mexicans, Mexican Americans, and African Americans-as mentally deficient or "feebleminded." As the evidence reveals, intelligence, race, heredity, and criminality became inextricably linked as the basis for segregating and removing youth of color from the reformatory. The records indicate that, despite officials' recommendations to send feebleminded boys to state hospitals that routinely sterilized their wards, as allowed by a 1909 state law, they sent the majority of youth to the Preston School of Industry, a reform school for older boys. In this instance, expediency in creating a premier institution at Whittier State School took precedence over larger eugenicists designs.
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Nada, Qotrun, M. Fahri Yasin, and Khairan M. Arief. "THE EFFECT OF GOOGLE CLASSROOM LEARNING MEDIA AND EMOTIONAL INTELLIGENCE ON THE RESULTS OF LEARNING HISTORY INDONESIA GRADE X STUDENTS AT SMK BINA INSAN KAMIL." Akademika 9, no. 02 (November 30, 2020): 17–28. http://dx.doi.org/10.34005/akademika.v9i02.1108.
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This study aims 1) The differences in learning outcomes of Indonesian history between students who get learning using google classroom and those using printed media. 2) The effect of interaction between instructional media and emotional intelligence on learning outcomes of Indonesian history. 3) To find out the difference between students' learning outcomes of Indonesian history using media google classroom and those using printed media for students who have high emotional intelligence. 4) To find out the learning outcomes of Indonesian history using media based on google classroom and those using printed media for students who have low emotional intelligence. This study used an experimental method with a 2x2 factorial group design.The affordable population in this study were students of class X SMK Bina Insan Kamil Bekasi City, the sample was taken using a random sampling technique, so the sample was 64 students, consisting of 32 students for the experimental group and 32 students. for the control group. Retrieval of data using test instruments for learning outcomes and non-tests for emotional intelligence. The data analysis technique used descriptive analysis and infrential analysis. Based on the research results, it can be concluded that:The learning outcomes of Indonesian history students taught using google classroom media are higher than students taught using print media. There is an influence of learning media interaction with emotional intelligence on learning outcomes of Indonesian history.
Keywords: Emotional Intelligence, Indonesian History Study Results
Dissertations / Theses on the topic "Intelligence tests – history"
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Silverberg, Carol. "IQ testing and tracking : the history of scientific racism in the American public schools : 1890-1924 /." abstract and full text PDF (UNR users only), 2008. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3311920.
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Thesis (Ph. D.)--University of Nevada, Reno, 2008."May 2008." Includes bibliographical references (leaves 105-120). Library also has microfilm. Ann Arbor, Mich. : ProQuest Information and Learning Company, [2009]. 1 microfilm reel ; 35 mm. Online version available on the World Wide Web.
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Silva, Carolina da Costa e. "O álbum \"Parques Infantis\" como objeto cultural (São Paulo, 1937)." Universidade de São Paulo, 2008. http://www.teses.usp.br/teses/disponiveis/48/48134/tde-18062008-151701/.
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Esta pesquisa histórica teve como objeto o álbum fotográfico Parques Infantis, produzido em 1937, sob a encomenda do Departamento de Cultura de São Paulo. Percebendo-o como objeto cultural, a pesquisa teve como propósito analisar o álbum a partir de suas condições de emergência e produção, materialidade e circulação. Para tanto, recorreu não apenas ao próprio álbum e suas fotografias como fonte histórica, como também mobilizou fontes escritas (discursos, legislação, artigos de revistas, biografias, entre outras), fontes orais (depoimentos) e fontes iconográficas (revista S. Paulo e outras fotografias) a fim de compor um quadro de entendimento sobre as finalidades e intenções que motivaram sua elaboração. A pesquisa mostra que essa publicação iconográfica impressa conformou parte da estratégia de publicização operada pela inteligência paulista (grupo de Paulo Duarte) sobre o principal projeto desenvolvido pelo Departamento de Cultura: os Parques Infantis. Por meio do impresso, os contratantes procuraram dar a ver o modo como eles delinearam os trabalhos educativos nesses estabelecimentos segundo concepções de educação que se propunham modernas (como a educação higiênica e a cultura física). Os intelectuais contrataram o artista-fotógrafo B. J. Duarte para efetuar os registros e elaborar a paginação do álbum. Para tanto, apropriou-se da estética de representação que estava na ordem da visualidade dos anos 1930, qual seja, a fotografia moderna.This historical research had as an object the photographic album Children Park, produced in 1937, under the orders of the Department of Culture of Sao Paulo. Perceiving it as a cultural object, the research had as purpose was to examine the album from their conditions of emergency and production, materiality and movement. Thus, appealed not only to their own album and its photographs as historical source, but also mobilized written sources (speeches, legislation, articles from journals, biographies among others),oral sources (testimony) and iconographic sources, (magazine S. Paulo and other photographs) in order to compose a framework of understanding about the aims and intentions that motivated their elaboration. The research shows that this printed iconographic publication complied part of the strategy of publicization operated by Paulista intelligence (group of Paulo Duarte) on the main project developed by the Department of Culture, the Children Park. Through print, contractors tried to see how they outlined the educative works in these establishments\' according education conceptions that proposed itself as modern (such as hygiene education and physical culture). The intellectuals hired the photographer-artist, B. J. Duarte to make the records and prepare the layout of the album. To this end, appropriated from the aesthetics of representation that was on the order of visuality of the years 1930, which is the modern photo.
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Chen, Hung-Chen, and 陳虹蓁. "A Study on Investigating the Message History for the Ability of Intelligence Test by Using Eyeball Tracking System." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/20631776326308676557.
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碩士崑山科技大學
數位生活科技研究所
98
The study adopts the eye movements’ recordation system during the whole instantly procedure of vision stimulus ( plane transformation, pattern variation, three-dimensional rotation figure on IQ test) with face LAB4. Eye movements tracking system records the whole test procedure information and analyses the rate of correct answer, the time of answering, the time of gaze, the area of gaze, and the trajectory of eye movements to judge the decision state of subjects with statistical method. The writing test divides the experimental subjects into experimental group (interior-performance) and control group (superior-performance). The results show differences between these two groups. The answering time of control group is shorter than experimental group, so we can discover that the strength of the space with the ability to answer the questions of the time is influential. The area of gazing topic reference diagram in experimental group is higher than control group, knowing the person who has worse space ability need spends more time to remember the questions. The trajectory of eye movements make the analysis, the experimental group search many times for repeatedly, but the control group can memorize characteristic point to seek the answer. This study can know the trend and the intention that subject owns when he is doing an intelligence test of vision stimulus.
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Wessels, Sally. "Factors predicting success in the final qualifying examination for chartered accountants." Diss., 1997. http://hdl.handle.net/10500/18498.
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Anyone desiring to qualify as an accountant or auditor is required to pass an examination as
approved by the Public Accountants' and Auditors' Board to establish whether candidates have
attained the required standard of academic knowledge in terms of the syllabi laid down by the
Board, as well as whether they are able to apply that knowledge in practice (P AAB, 1995).
However each year many students fail this very important examination. The reasons for this are
not clear and the purpose of this research is to determine whether: personality; vocational
interests; intelligence; matriculation Mathematics and home language (English/ Afrikaans) results,
predict success in the QE, by comparing a group of successful and unsuccessful QE candidates.
The logistic regression, discriminant analysis and t-test statistical procedures, indicated that:
warmth (A), liveliness (F), rule-consciousness (G), social boldness (H), apprehension (0),
self-reliance (Q2), perfectionism (Q3), tension (Q4), computational interest, social services
interest, mechanical interest, Mental Alertness and matriculation home language, are significant
factors to consider when identifying candidates likely to be successful in the QE.Industrial & Organisational Psychology
MCOM (Industrial Psychology)
Books on the topic "Intelligence tests – history"
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Hattie, John. Intelligence and intelligence testing. London: Routledge, 2011.
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P, Flanagan Dawn, Genshaft Judy, and Harrison Patti L, eds. Contemporary intellectual assessment: Theories, tests, and issues. New York: Guilford Press, 1997.
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Intelligence, destiny, and education: The ideological roots of intelligence testing. London: Routledge, 2006.
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Richardson, John T. E. Howard Andrew Knox: Pioneer of intelligence testing at Ellis Island. New York: Columbia University Press, 2011.
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Castles, Elaine E. Inventing intelligence: How Americans came to worship IQ. Santa Barbara, Calif: Praeger, 2012.
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Fancher, Raymond E. The intelligence men, makers of the IQ controversy. New York: Norton, 1985.
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1945-, Sokal Michael M., and American Association for the Advancement of Science. National Meeting, eds. Psychological testing and American society, 1890-1930. New Brunswick: Rutgers University Press, 1987.
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The homes and homeless of post-war Britain. Carnforth: Parthenon Press, 1985.
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F, Lohman David, ed. A century of ability testing. Chicago: Riverside Pub. Co., 1990.
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Jacoby, Russell. The bell curve debate: History, documents, opinions. New York: Times Books, 1995.
Find full textBook chapters on the topic "Intelligence tests – history"
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Mariani, Fabio, Lynn Rother, and Max Koss. "Teaching Provenance to AI." In Edition Museum, 163–72. Bielefeld, Germany: transcript Verlag, 2023. http://dx.doi.org/10.14361/9783839467107-014.
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Our paper addresses how artificial intelligence technologies can transform museum records of provenance into structured and machine-readable data, which is the first critical step in undertaking a large-scale cross-institutional analysis of object history. Drawing on research on natural language processing (NLP), we have identified sentence boundary disambiguation and span categorization as highly effective techniques for extracting and structuring information from provenance texts. Our paper focuses on a provenance-specific annotation scheme that enables us to retain historical nuances when constructing provenance linked open data (PLOD).
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Kawazoe, Ai, Yusuke Miyao, Takuya Matsuzaki, Hikaru Yokono, and Noriko Arai. "World History Ontology for Reasoning Truth/Falsehood of Sentences: Event Classification to Fill in the Gaps Between Knowledge Resources and Natural Language Texts." In New Frontiers in Artificial Intelligence, 42–50. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10061-6_3.
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Poortinga, Ype H., and Eckhard Klieme. "The History and Current Status of Testing Across Cultures and Countries." In The ITC International Handbook of Testing and Assessment, 14–28. Oxford University Press, 2016. http://dx.doi.org/10.1093/med:psych/9780199356942.003.0002.
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Chapter 2 gives a narrative account of the use of tests across countries and cultures over the course of nearly a century. Initially, differences in test score distributions were usually interpreted at face value, independent of the cultural and educational background of test takers. Findings of group differences in the domain of intelligence were seen as a confirmation of widely held beliefs, also among psychologists, about racial differences. Soon implicit assumptions to the effect that tests can be culture-free or culture-fair were challenged. The cross-cultural equivalence of tests became an issue for conceptual and, especially, for psychometric analysis. This line of work has resulted in a large array of methods and statistical procedures for identifying cultural bias in items and tests. The concluding section of the chapter envisages further improvements in the quality of instruments for cross-cultural usage, notably through the use of international teams of authors in test development.
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Geisinger, Kurt F. "The History of Bias Assessment in Educational and Psychological Testing." In Fairness in Educational and Psychological Testing: Examining Theoretical, Research, Practice, and Policy Implications of the 2014 Standards. American Educational Research Association, 2022. http://dx.doi.org/10.3102/9780935302967_1.
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This chapter provides a brief historical overview of how psychometricians, educational researchers, and psychologists have studied the fairness of tests. This history does not really begin until the early 1960s. Early foci included the apparent benefits of testing during the world wars, the use of intelligence testing, and the attempt to build culture-free and culture-fair tests. Shortly after the passage of the Civil Rights Act of 1964, college admissions and employment measures came under scrutiny for fairness by researchers and the courts, often with surprising results. Researchers developed test fairness models and methods for identifying items that behave with systematic differences across demographic groups. An original focus in test fairness was African Americans; subsequently, women, language minorities, immigrants, and those with disabilities were studied. The Standards for Educational and Psychological Testing (American Educational Research Association, American Psychological Association, & National Council on Measurement in Education, 2014) have shed much light on fairness in testing, especially in the most recent tests.
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de Almondes, Katie Moraes, Gilberto Sousa Alves, and Candida Lopes Alves. "Artificial Intelligence in Neuropsychology." In Advances in Neuroscience, Neuropsychiatry, and Neurology, 1–16. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-0851-6.ch001.
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This chapter reflects the challenge of discussing the possibility of a paradigm shift in neuropsychology to cognitive and behavioral science based on technology, especially with the use of artificial intelligence, considering all continents and their sociocultural differences. With this purpose, it presents the history of neuropsychology in the digital universe, the advancement of artificial intelligence/technology in neuropsychological assessment, and the creation of standardized tests through digital means. It discusses psychological intervention and the use of artificial intelligence. Lastly, there are monitoring applications for neurocognitive and technology in rehabilitation.
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Yarhi-Milo, Keren. "The US Intelligence Community’s Assessments of Soviet Intentions." In Knowing the Adversary. Princeton University Press, 2014. http://dx.doi.org/10.23943/princeton/9780691159157.003.0008.
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This chapter examines the indicators used by U.S. intelligence organizations to assess the intentions of the Soviet Union. Drawing on National Intelligence Estimates (NIEs) produced on the Soviet Union between 1977 and 1980, the chapter considers the degree to which history confirms the predictions of the selective attention thesis's organizational expertise hypothesis. It also tests the capabilities, strategic military doctrine, and behavior theses. After providing a brief overview of the U.S. intelligence community's estimates of Soviet intentions earlier in the 1970s, the chapter discusses the intelligence organizations' views about Soviet intentions during Jimmy Carter's presidency. It shows that an effort to understand the adversary's political intentions did not play a significant role in the U.S. intelligence community's intentions assessments, and particularly in the NIEs' judgments of the threat posed by the USSR. Instead, most of the NIEs were dedicated to estimating current and projected Soviet strategic forces as well as military intentions.
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Yarhi-Milo, Keren. "The US Intelligence Community’s Assessments of Soviet Intentions." In Knowing the Adversary. Princeton University Press, 2014. http://dx.doi.org/10.23943/princeton/9780691159157.003.0011.
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This chapter examines the indicators used by U.S. intelligence organizations to assess the intentions of the Soviet Union. Drawing on National Intelligence Estimates (NIEs) produced on the Soviet Union between 1977 and 1980, the chapter considers the degree to which history confirms the predictions of the selective attention thesis’s organizational expertise hypothesis. It also tests the capabilities, strategic military doctrine, and behavior theses. After providing a brief overview of the U.S. intelligence community’s estimates of Soviet intentions earlier in the 1970s, the chapter discusses the intelligence organizations’ views about Soviet intentions during Jimmy Carter’s presidency. It shows that an effort to understand the adversary’s political intentions did not play a significant role in the U.S. intelligence community’s intentions assessments, and particularly in the NIEs’ judgments of the threat posed by the USSR. Instead, most of the NIEs were dedicated to estimating current and projected Soviet strategic forces as well as military intentions.
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Mazzuca, Daniela, Francesco Zinno, and Agostino Forestiero. "Enhancing Thrombophilia Risk Prediction Through AI-Based Methodologies." In Studies in Health Technology and Informatics. IOS Press, 2024. http://dx.doi.org/10.3233/shti240073.
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Thrombophilia, a predisposition to thrombosis, poses significant diagnostic challenges due to its multi-factorial nature, encompassing genetic and acquired factors. Current diagnostic paradigms, primarily relying on a combination of clinical assessment and targeted laboratory tests, often fail to capture the complex interplay of factors contributing to thrombophilia risk. This paper proposes an innovative artificial intelligence (AI)-based methodology aimed to enhance the prediction of thrombophilia risk. The designed multidimensional risk assessment model integrates and elaborates through AI a comprehensive collection of patient data types, including genetic markers, clinical parameters, patient history, and lifestyle factors, in order to obtain advanced and personalized explainable diagnoses.
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Marschark, Marc, Harry G. Lang, and John A. Albertini. "Cognitive Development and Deaf Children." In Educating Deaf Students. Oxford University Press, 2006. http://dx.doi.org/10.1093/oso/9780195310702.003.0011.
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There is a long history of investigations reporting that deaf children lag behind hearing peers in learning, problem solving, and creativity. In this chapter we describe the kinds of evidence that led to such conclusions and the extent to which they appear to be valid today. Early research concerning cognitive development in deaf children often was aimed at understanding intellectual growth “in the absence of language.” Other investigations involved tasks that required comprehension of English or histories of reading. More recently, we have come to understand that both kinds of evaluation might be biased against deaf children. Still, ways in which deaf children’s atypical histories of language functioning and educational experience might influence their cognitive development are largely unexplored. There have been a variety of studies dealing with deaf children’s cognitive skills, and especially memory, sometimes including consideration of language fluencies and degree of hearing loss. More recently, various tests of cognitive ability have been developed that are nonverbal in nature or can be administered through sign language. The extent to which those tests accurately reflect the thinking skills of deaf children still remains poorly understood, as does the question of whether such tests tap the same skills that they do in hearing children. Further, some people still make the appealing but dubious assumption that cognitive development is essentially the same for deaf and hearing children (see Braden, 2001; Marschark & Lukomski, 2001, for discussion). Studies of intelligence and academic abilities of minority and underprivileged children during the 1960s and 1970s led to a concern about the lack of cultural fairness in testing. It was recognized at the time that the nature of children’s early environments could influence later performance on intelligence measures and academic achievement. This issue was never adequately addressed with regard to deaf children, most of whom clearly have early childhood experiences that could cause differences in test performance. As a result, deaf children were often described as “deficient” or as “concrete, literal thinkers” who were unlikely to be able to grasp the kinds of abstract concepts necessary for academic success.
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Kilani, Amal, Ahmed Ben Hamida, and Habib Hamam. "Artificial Intelligence Review." In Encyclopedia of Information Science and Technology, Fourth Edition, 106–19. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2255-3.ch010.
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In this paper, we present a profound literature review of the Artificial Intelligence (AI). After defining it, we briefly cover its history and enumerate its principal fields of application. We name for example information system, commerce, image processing, human-computer interaction, data compression, robotics, route planning, etc. Moreover, the test that defines an artificially intelligent system, called The Turing test, is also defined and detailed. Afterwards, we describe some AI tools such as Fuzzy logic, genetic algorithms and swarm intelligence. Special attention will be given to neural networks and fuzzy logic. We also present the future research directions and ethics.
Conference papers on the topic "Intelligence tests – history"
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Al Sawafi, Ali, Alireza Kazemi, Tarek Ganat, Faisal Al Saadi, and Adnan Al Ghadani. "Developing an ESP Lifespan Predictive Model Using Artificial Intelligence: A Case Study On an Omani Oilfield." In SPE Conference at Oman Petroleum & Energy Show. SPE, 2024. http://dx.doi.org/10.2118/218601-ms.
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Abstract The Electrical Submersible Pump (ESP) is the most effective and consistent artificial lift method for medium to high production rates. Although the capital cost of ESP is high, it pales in comparison to the production losses resulting from its failure. Recently, Machine Learning (ML) has gained significant attention in the oil and gas industry due to its predictive power. This paper aims to develop a ML model to predict ESP lifespan and identify the key features that influence its longevity. The study reviewed the failure history of more than 100 wells from an Omani oilfield, with 132 ESP failures attributed to sand and scale accumulation. The dataset includes 36 static features related to ESP design, installation, commissioning, failure, pull-out, and teardown. Three algorithms, namely Support Vector Regressor (SVR), Random Forest Regressor (RFR), and Extreme Gradient Boosting Regressor (XGBR), were selected. Hundreds of tests were performed on each algorithm to optimize the parameters and hyperparameters, based on mean absolute error, average residual, and determination coefficient. The study developed a model with two levels to predict the lifespan of ESP before installation and after the last valid well test. The model had a mean absolute error of 25 days and 8 days for the first and second levels, respectively, with a determination coefficient of 60% and 73%. The model showed that certain factors related to pump and motor design have the most significant impact on the longevity of the ESP before installation. Pump discharge pressure and flow rates of oil and water are crucial to monitor and control during its operational lifespan. The findings emphasize the importance of careful selection and design of ESP components to ensure a long-lasting lifespan. By scheduling ESP maintenance before failure, these findings can help mitigate capital costs, while preparing the necessary hoist, rig, and materials for ESP replacement can avoid deferred operational costs.
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Mao, Qian, Zihan Li, Chengxi Huang, and Hailiang Wang. "An exploratory user study on the design of smart walking aids for community-dwelling older adults." In 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1003662.
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Population aging has increasingly become an issue of concern globally. Aging inevitably reduces older adults’ physical capacity (e.g., mobility) and further affects their ability to live independently or perform daily activities. Walking aids (e.g., canes) are generally used as assistive devices to provide physical support and reduce fall risk in daily activities. Given the rapid development of artificial intelligence algorithms and hardware computing capability, smart walking aids with functions like fall alert, health monitoring, and positioning have become promising in elderly care. However, it remains unclear whether community-dwelling older adults are ready for smart walking aids. The present study aims to explore community-dwelling older adults’ attitudes and perceptions of smart walking aids, especially on the functions of fall alert, health monitoring, pill reminder, positioning, and topography detection. The results are expected to guide future designs of smart walking aids to increase users’ well-being in daily life. A convenience sampling method was applied to collect data via an online questionnaire for demographic information, attitudes, and design expectations toward smart walking aids. Chi-square tests and binary logistic regression models were used to analyze the associations among demographics, attitudes, and design expectations. The data were collected from 264 valid respondents (148 males and 116 females; 60.5±7.4 years). The results showed safety assurance, sturdy products, and additional intelligent functions were the most expected design elements in smart walking aids. Community-dwelling older adults preferred three intelligent functions: fall alert, health monitoring, and positioning. However, complex operations would resist users from adopting smart walking aids, showing the importance of usability in future designs. No significant group differences were found in purchase preference and attitudes toward smart walking aids among gender (p > 0.06), education (p > 0.35), and living arrangement (p > 0.06). The results of binary logistic regressions showed that individuals with a user history of smart walking aids are about ten times more likely to buy smart walking aids than those with no user history (p = 0.025, OR = 10.376). Older adults aged 71-80 preferred smart walking aids over other age groups (p = 0.048). Individuals aged 61-70 years are more interested in the intelligent functions of fall alert (p = 0.002) and health monitoring (p = 0.021). Community-dwelling older adults showed positive attitudes to smart walking aids with functions such as fall alerts, health monitoring, and positioning to support their independence in their daily lives. User-centered designs are crucially needed to speed up the successful implementation of smart walking aids in the community.
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Rubio, Erismar, and Nagaraju Reddicharla. "Enhanced Back Allocation Process Assisted by Real Time AI-Based Virtual Metering. Field Case Study in a Giant Field Project." In ADIPEC. SPE, 2023. http://dx.doi.org/10.2118/216936-ms.
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Abstract Artificial Intelligence (AI) is relatively new neurocomputational science employed in oil industry to solve wide spectrum of non-linear problems with high parallelism, fault and noise tolerance. AI seems very attractive for its remarkable capabilities of processing-correlating data and learning attributes. This paper briefs a successful implementation of an ecosystem between AI and physics-based models in a smart field, that support accurate well allocation process during the project start-up when testing facilities were not available. This case study is presented in a smart field during the commissioning of a new phase-project incorporating 45 new strings at a time. Reconciliation between wells and fiscal meters vanished after incorporating the newly commissioned wells with no flow-tests. An innovative AI-model was developed to estimate well rates from real-time surface parameters (pressure, temperature, choke &gas lift rate) to assist the allocation process for those strings, utilizing extensive well test history and subsurface data from pre-existing nearby wells. Data mining and physics-based models were integrated to develop an ecosystem that can virtually measure daily oil, water and gas rates with reasonable accuracy enhancing well back-allocation process. Initial newly-strings models were built using only one commissioning test, consisting of diverting wells to a portable separator for few hours. This practice usually overestimates the productivity index since rates are captured in transient mode. Later, when wells are flowing for longer and cleaned up, production rates decrease after stabilization. Fortunately, these changes of performance over time are well-captured by the real time parameters. Therefore, this paper proposal can be extended to other digital fields to track the well performance and minimize the error in back allocated rates as it was observed in this field application, demonstrating how reconciliation factor was continuously enhanced day after day, once AI-virtual rate prediction was introduced. AI-model prediction was later verified against actual flow tests via portable separators with an average error below 20%. Virtual rates were predicted using machine learning (ML) techniques multilinear regression, Artificial Neural-Network (ANN) and Self-Organizing Maps (SOM). The results were used to update models for better well performance prediction. The performance of these ML techniques were improved with intelligent inputs and proper segregated and intuitive training to machine. As a practical application, an ecosystem was developed combining AI and physics to predict well-performance of newly-drill wells under gas lift and natural flow, using real-time measurement and the digital framework, to provides reasonably accurate in simulating both training and test time-dependent well performance inferred from pressure, temperature, gas-lift rate and choke. The novelty of this paper consists in the developed data cleansing and association technics that enable the implementation of successful AI-models in wells with no flow test data for training, levering Real-Time data usage.
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Tanim, Tanvir R., Mayank Garg, and Christopher D. Rahn. "An Intelligent Nail Design for Lithium Ion Battery Penetration Test." In ASME 2016 10th International Conference on Energy Sustainability collocated with the ASME 2016 Power Conference and the ASME 2016 14th International Conference on Fuel Cell Science, Engineering and Technology. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/es2016-59073.
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Internal short-circuiting is the most dangerous abuse scenario for lithium ion batteries. A nail penetration test simulates the internal short circuit process by penetrating a test cell/pack with an electrically conductive nail. Pass or failure of the cell and/or chemistry is determined by the presence of smoke or flame following penetration. To understand and eliminate the safety concerns arising from the internal shorts, it is important to fully understand the cell/pack dynamics during the shorting process. Gathering useful data at the point of penetration during nail penetration tests is very challenging due to the inherent destructive nature of the test. This paper presents an intelligent nail (iNail) design consisting of four parts where multiple sensors (thermo-couples, strain gauges, etc.) can be conveniently placed for reliable and efficient data collection. The time history of temperature distributions through the cell/pack thickness can be recorded with the iNail without position control of the nail penetration tester, greatly simplifying the test. A prototype stainless steel iNail is manufactured with three embedded thermocouples. Nail penetration tests are conducted on fully charged 4 Ah gr/NCM pouch cells. The iNail successfully recorded the temperature time history at the penetration point during the tests. Pack level nail penetration tests (three pouch cells in parallel) were also performed with iNail temperature measurements.
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Suthar, Sailesh, and Lay Lay Goh. "AI Application in Yield and Failure Analysis to Reduce Overall Time-to-Defect and Failure Root-Cause Isolation." In ISTFA 2022. ASM International, 2022. http://dx.doi.org/10.31399/asm.cp.istfa2022p0402.
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Abstract This paper presents conceptual application of AI in Failure Analysis to connect to various databases in semiconductor manufacturing and generating interactive data visualization to isolate root cause of failure faster vs traditional methods. Generally available low-cost software application like Microsoft Power BI (Business Intelligence) is utilized to visualize big data to isolate failure modes at wafer, die, and package level. This historic data visualization knowledge is further used by failure analyst to process failure mode isolation much faster based on failed package unit history. Semiconductor manufacturing companies have various big data such as wafer fab processing, die level test, or wafer sort and packaged die testing including customer return. MS Power BI application has ability to connect to these separate big databases and create unified data visualization to isolate failure modes through faster inter-connectivity and "connecting the dots" to provide bigger picture or drill down to finer unit level detail. This level of visualization utilizes already available info/data to help reduce overall time-to-defect. With this failure background, engineers can plan fault isolation and analysis and reduce overall time to find root-cause of failure.
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Song, Hao, and Yan Zhang. "Numerical simulation and impact test of hand-held vacuum cleaner dust collector." In Intelligent Human Systems Integration (IHSI 2022) Integrating People and Intelligent Systems. AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1001076.
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In order to analyze the dynamic response of the dust collector in the process of falling, numerical simulation and drop impact experiment were used to conduct research. The joint simulation of HYPERMESH and LS-DYNA was used to simulate the drop process; a drop test platform was built with a high-speed camera to record the collision process and sensors were used to obtain the drop impact force and acceleration time history curves. The numerical simulation vividly shows the collision process of the dust collector, which is consistent with the phenomenon of part disengagement and structural deformation that occurred in the experiment. The impact force and acceleration peak values obtained by simulation and experiment in different drop postures are relatively close, which also verifies the reliability of the simulation. The impact resistance of the dust collector is evaluated in this study, which helps reduce product development costs and subsequent structural improvements.
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Bestman, Somiari, Rasheed Mahdi Almahdi, Assem Ahmed Alyomny, and Awoye Lawson-Jack. "Can Artificial Intelligence Enhance Gas Well Deliverability Testing? Exploring the Application of Machine Learning in Backpressure Testing." In SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition. SPE, 2023. http://dx.doi.org/10.2118/215326-ms.
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Abstract A deliverability test is a flow test performed to generate data utilized in the characterization of the short and long-term production performance of a well for various conditions of reservoir and bottomhole pressure. The generated data includes bottomhole pressure and temperature, flowing wellhead pressure and temperature measurements as well as the associated flow rates. An analysis of the acquired data ultimately yields a well model capable of predicting a tested well's productivity under stipulated conditions. This paper presents a methodology by which the data output from a flow-after-flow test may be generated without ever performing the actual test. A machine learning (ML) model developed and trained on historic production data is used to simulate a producing wells performance at several rates as is typical for an actual flow-after-flow test. The methodology utilizes a ML model trained on recent historical production data comprising of flow rates, flowing pressures and flowing temperatures, measured at surface and/or downhole. The ML model is then used to predict the flowing pressures and temperatures for a user specified flow rate. In its current form, the model is designed to utilize a continuous data stream that may be from a real time or archived source. The model may also be adapted to utilize data with a batch type configuration. By minimizing the need for actual deliverability tests, or altogether eliminating the need for testing, operators stand to benefit immensely. The benefits include minimization or reduction of costs associated with testing requirements, curtailed production, as well as the minimization of emissions.
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Zhu, Yada, Jianbo Li, Jingrui He, Brian L. Quanz, and Ajay A. Deshpande. "A Local Algorithm for Product Return Prediction in E-Commerce." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/517.
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With the rapid growth of e-tail, the cost to handle returned online orders also increases significantly and has become a major challenge in the e-commerce industry. Accurate prediction of product returns allows e-tailers to prevent problematic transactions in advance. However, the limited existing work for modeling customer online shopping behaviors and predicting their return actions fail to integrate the rich information in the product purchase and return history (e.g., return history, purchase-no-return behavior, and customer/product similarity). Furthermore, the large-scale data sets involved in this problem, typically consisting of millions of customers and tens of thousands of products, also render existing methods inefficient and ineffective at predicting the product returns. To address these problems, in this paper, we propose to use a weighted hybrid graph to represent the rich information in the product purchase and return history, in order to predict product returns. The proposed graph consists of both customer nodes and product nodes, undirected edges reflecting customer return history and customer/product similarity based on their attributes, as well as directed edges discriminating purchase-no-return and no-purchase actions. Based on this representation, we study a random-walk-based local algorithm for predicting product return propensity for each customer, whose computational complexity depends only on the size of the output cluster rather than the entire graph. Such a property makes the proposed local algorithm particularly suitable for processing the large-scale data sets to predict product returns. To test the performance of the proposed techniques, we evaluate the graph model and algorithm on multiple e-commerce data sets, showing improved performance over state-of-the-art methods.
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Hoang, Son K., Tung V. Tran, Tan N. Nguyen, Tu A. Truong, Duy H. Pham, Trung N. Tran, Vinh X. Trinh, and Anh T. Ngo. "Successful Application of Machine Learning to Improve Dynamic Modeling and History Matching for Complex Gas-Condensate Reservoirs in Hai Thach Field, Nam Con Son Basin, Offshore Vietnam." In SPE Symposium: Artificial Intelligence - Towards a Resilient and Efficient Energy Industry. SPE, 2021. http://dx.doi.org/10.2118/208657-ms.
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Abstract This study aims to apply machine learning (ML) to make history matching (HM) process easier, faster, more accurate, and more reliable by determining whether Local Grid Refinement (LGR) with transmissibility multiplier is needed to history match gas-condensate wells producing from geologically complex reservoirs and determining how LGR should be set up to successfully history match those production wells. The main challenges for HM gas-condensate production from Hai Thach wells are large effect of condensate banking (condensate blockage), flow baffles by the sub-seismic fault network, complex reservoir distribution and connectivity, highly uncertain HIIP, and lack of PVT information for most reservoirs. In this study, ML was applied to analyze production data using synthetic samples generated by a very large number of compositional sector models so that the need for LGR could be identified before the HM process and the required LGR setup could also be determined. The proposed method helped provide better models in a much shorter time, and improved the efficiency and reliability of the dynamic modeling process. 500+ synthetic samples were generated using compositional sector models and divided into training and test sets. Supervised classification algorithms including logistic regression, Gaussian, Bernoulli, and multinomial Naïve Bayes, linear discriminant analysis, support vector machine, K-nearest neighbors, and Decision Tree as well as ANN were applied to the data sets to determine the need for using LGR in HM. The best algorithm was found to be the Decision Tree classifier, with 100% and 99% accuracy on the training and the test sets, respectively. The size of the LGR area could also be determined reasonably well at 89% and 87% accuracy on the training and the test sets, respectively. The range of the transmissibility multiplier could also be determined reasonably well at 97% and 91% accuracy on the training and the test sets, respectively. Moreover, the ML model was validated using actual production and HM data. A new method of applying ML in dynamic modeling and HM of challenging gas-condensate wells in geologically complex reservoirs has been successfully applied to the high-pressure high-temperature Hai Thach field offshore Vietnam. The proposed method helped reduce many trial and error simulation runs and provide better and more reliable dynamic models.
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Thwapiah, Ghalib Y., and L. Flavio Campanile. "Nonlinear Aeroelastic Study of Bending Divergence." In ASME 2010 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. ASMEDC, 2010. http://dx.doi.org/10.1115/smasis2010-3678.
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In the beginning of the history of aviation, aeroelastic static instabilities were a problem in operating monoplane aircraft. After being discovered, they have been systematically avoided by design, since they would have led to large deformations and structural failure. A new research trend (active aeroelasticity) reverts this approach and utilizes — instead of avoiding — static instabilities to realize wing morphing. Another modern research trend are compliant systems (i.e. structures designed to achieve large deformations within its elastic range). Joining those two trends lead to a novel class of airfoil structures (compliant, active aeroelastic wings) enables operating at and beyond aeroelastic instabilities. Such structures need a new modeling approach, which includes nonlinearities of structural and aerodynamic kind. In this paper, a non linear analysis of aeroelastic bending divergence (a phenomenon which concerns forward-swept wings) is presented, initially based on so-called low-fidelity models. Such models are to some extent inaccurate, but allow a good insight into the physical behavior of the phenomenon. Experimental tests of a compliant airfoil will then be presented, performed to investigate the trans-critical and post-critical response of the airfoil model and to validate the low fidelity models. At the end, high-fidelity modeling is approached, which makes use of computational numerical simulations methods (FEM, CFD, FSI). Selected results will be presented, which allow to predict the system response more accurately and to reproduce the wind tunnel test results more closely.