Institutionalized children represent a risk-factor category from the perspective of social integration. Educational interventions implemented in programs designed for children raised in foster homes verify the effectiveness of complex means of training that could influence their multidimensional development. Among these means, dance has been identified as a way of developing coordination, rhythmicity, motor skills, and spatiotemporal orientation through body movements. Starting from the hypothesis that the systematic participation of institutionalized children in a dance program contributes to the development of their motor skills, an intervention model based on dance content was designed for this study. The purpose of this research is to optimize the motor skills of institutionalized children and to stimulate their bodily-kinesthetic and visual-spatial intelligences. The objectives of the study are to highlight the influence of dance on the development of institutionalized children and to develop the methodological concept regarding the use of dance for institutionalized children at the age of preadolescence. The research was conducted over a nine-month period, with a frequency of two training sessions per week of 60 minutes each, and was based on the consolidation of steps from different dance styles for a group of 29 institutionalized children aged 11-12 years. Testing was carried out using the Optojump device, and the tests applied were aimed at assessing their lower limb power, reaction speed, repetition speed, and spatiotemporal orientation. The motor effects produced indicate positive changes in test values, with all results showing significant differences after nine months of participation in the dance program. The greatest impact is for the displacement point of the March in Place Eyes Closed 30 Seconds test, which reveals an improvement in spatial orientation ability. In conclusion, the participation of institutionalized children in a dance program contributes to the optimization of their motor skills and the stimulation of their bodily-kinesthetic and visual-spatial intelligences, therefore we consider it appropriate to deepen the study of dance as a means of developing multiple intelligences through educational programs implemented in schools.
{"title":"The Contribution of Dance to Optimizing Motor Skills and Improving the Educational Process in Institutionalized Children","authors":"G. Tomescu, Monica Stănescu, K. Aivaz","doi":"10.18662/brain/15.2/580","DOIUrl":"https://doi.org/10.18662/brain/15.2/580","url":null,"abstract":"Institutionalized children represent a risk-factor category from the perspective of social integration. Educational interventions implemented in programs designed for children raised in foster homes verify the effectiveness of complex means of training that could influence their multidimensional development. Among these means, dance has been identified as a way of developing coordination, rhythmicity, motor skills, and spatiotemporal orientation through body movements. Starting from the hypothesis that the systematic participation of institutionalized children in a dance program contributes to the development of their motor skills, an intervention model based on dance content was designed for this study. The purpose of this research is to optimize the motor skills of institutionalized children and to stimulate their bodily-kinesthetic and visual-spatial intelligences. The objectives of the study are to highlight the influence of dance on the development of institutionalized children and to develop the methodological concept regarding the use of dance for institutionalized children at the age of preadolescence. The research was conducted over a nine-month period, with a frequency of two training sessions per week of 60 minutes each, and was based on the consolidation of steps from different dance styles for a group of 29 institutionalized children aged 11-12 years. Testing was carried out using the Optojump device, and the tests applied were aimed at assessing their lower limb power, reaction speed, repetition speed, and spatiotemporal orientation. The motor effects produced indicate positive changes in test values, with all results showing significant differences after nine months of participation in the dance program. The greatest impact is for the displacement point of the March in Place Eyes Closed 30 Seconds test, which reveals an improvement in spatial orientation ability. In conclusion, the participation of institutionalized children in a dance program contributes to the optimization of their motor skills and the stimulation of their bodily-kinesthetic and visual-spatial intelligences, therefore we consider it appropriate to deepen the study of dance as a means of developing multiple intelligences through educational programs implemented in schools.","PeriodicalId":504804,"journal":{"name":"BRAIN. Broad Research in Artificial Intelligence and Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141677419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I. Susnea, Emilia Pecheanu, A. Cocu, Simona Susnea
The paper discusses the prospects and risks associated with the development superintelligent artificial intelligence (AI) and artificial consciousness (AC) ten years after Nick Bostrom explored these ideas in his influential book (Bostrom, 2014). We argue that the debate about the evolution of AI has changed at least in the following aspects: First, the development of superintelligent machines is no longer limited to speculations about a distant future – recent advances in this field already produce immediate and palpable impact across various sectors, including education, business, and technology. Second, we argue that the debate on whether AI systems might one day achieve a form of artificial consciousness (AC) has shifted from a theoretical possibility to a pressing concern. After reviewing some of the most likely prerequisites for the development of potentially dangerous AI systems, we suggest several directions of action to avoid the risk of losing control over superintelligent AI.
{"title":"Superintelligence Revisited in Times of ChatGPT","authors":"I. Susnea, Emilia Pecheanu, A. Cocu, Simona Susnea","doi":"10.18662/brain/15.2/579","DOIUrl":"https://doi.org/10.18662/brain/15.2/579","url":null,"abstract":"The paper discusses the prospects and risks associated with the development superintelligent artificial intelligence (AI) and artificial consciousness (AC) ten years after Nick Bostrom explored these ideas in his influential book (Bostrom, 2014). We argue that the debate about the evolution of AI has changed at least in the following aspects: First, the development of superintelligent machines is no longer limited to speculations about a distant future – recent advances in this field already produce immediate and palpable impact across various sectors, including education, business, and technology. Second, we argue that the debate on whether AI systems might one day achieve a form of artificial consciousness (AC) has shifted from a theoretical possibility to a pressing concern. After reviewing some of the most likely prerequisites for the development of potentially dangerous AI systems, we suggest several directions of action to avoid the risk of losing control over superintelligent AI.","PeriodicalId":504804,"journal":{"name":"BRAIN. Broad Research in Artificial Intelligence and Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141676501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Roman Khavula, Oksana Chuyko, Nataliia Rodina, Inokentii Korniienko, Zhanna Bogdan, A. Kichuk
So far, the focus of safety psychology, coping strategies, and occupational safety has been predominantly on physical factors and self-regulation tools. However, this article outlines the poorly researched neuro-dependent phenomena of Ukrainian organizational culture, where parallel new proactive and old reactive tendencies are observed. The purpose of this article is to identify the main neurodependent destructive tools of deceptive psychological self-protection in the context of contemporary organizational culture. These phenomena proved to be dependent on both general and personal culture, through which the instincts of psychological self-preservation and primitive unconscious defenses such as shame, guilt, excessive responsibility, competition avoidance, mythological attitudes, rituals, etc. are refracted. Methods of sociological survey by means of posing provocative questions with short answer time, intervisional and independent observations of production teams (with the subsequent neurointerpretative analysis) allowed to make a number of important conclusions. The main ones are the objectification and explanation of two intensions of Ukrainian organization culture, the determination of neuro-markers of destructive manifestations of personal deontological culture and the conclusion of a systematizing table of the stages of development of organization culture with procedural-attributive and neurodestructive explication. Also in the conclusions by psychological and pedagogical modeling and expedient selection of tools the authors concluded a set of recommendations for the acquisition of stress resistance in the context of the culture of the organization. The article can become a theoretical basis for the development of effective training programs and non-invasive neuropsychological tools for the correction of neurocultural deviations.
{"title":"Stress Resistance of Personality in the Conditions of Organizational Culture in Ukraine. Specific Dependent Phenomena","authors":"Roman Khavula, Oksana Chuyko, Nataliia Rodina, Inokentii Korniienko, Zhanna Bogdan, A. Kichuk","doi":"10.18662/brain/15.2/571","DOIUrl":"https://doi.org/10.18662/brain/15.2/571","url":null,"abstract":"So far, the focus of safety psychology, coping strategies, and occupational safety has been predominantly on physical factors and self-regulation tools. However, this article outlines the poorly researched neuro-dependent phenomena of Ukrainian organizational culture, where parallel new proactive and old reactive tendencies are observed. The purpose of this article is to identify the main neurodependent destructive tools of deceptive psychological self-protection in the context of contemporary organizational culture. These phenomena proved to be dependent on both general and personal culture, through which the instincts of psychological self-preservation and primitive unconscious defenses such as shame, guilt, excessive responsibility, competition avoidance, mythological attitudes, rituals, etc. are refracted. Methods of sociological survey by means of posing provocative questions with short answer time, intervisional and independent observations of production teams (with the subsequent neurointerpretative analysis) allowed to make a number of important conclusions. The main ones are the objectification and explanation of two intensions of Ukrainian organization culture, the determination of neuro-markers of destructive manifestations of personal deontological culture and the conclusion of a systematizing table of the stages of development of organization culture with procedural-attributive and neurodestructive explication. Also in the conclusions by psychological and pedagogical modeling and expedient selection of tools the authors concluded a set of recommendations for the acquisition of stress resistance in the context of the culture of the organization. The article can become a theoretical basis for the development of effective training programs and non-invasive neuropsychological tools for the correction of neurocultural deviations.","PeriodicalId":504804,"journal":{"name":"BRAIN. Broad Research in Artificial Intelligence and Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141674983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the development of the IoT domain, the volume of data produced by various applications has also increased. Due to multiple reasons, such as sensor failure, communication system failure, and human errors, the data acquired from the sensors have missing values. The presence of missing values in the dataset affects the informational content of the dataset and thus affects the process of extracting knowledge from the data. In this paper, the authors present a comparative analysis of the performances of the methods of filling in the missing values, such as method, Interpolation, Mean, the K-Nearest Neighbors (KNN), and Random Forests (RF), on the data coming from a Predictive Maintenance (PdM) system that can be used at Unmanned Aerial Vehicle (UAV). The data on which the performance of these methods has been studied comes from a PdM system from the UAVs, used to identify the defects of the Brushless DC (BLDC) motors and estimate the Remaining Useful Life (RUL) of Li-ion batteries.
{"title":"Comparative Performance Analysis of Filling Missing Values Algorithms in PdM Systems of UAV","authors":"D. Andrioaia, V. Gaitan, Bogdan Patrut, I. Furdu","doi":"10.18662/brain/15.2/561","DOIUrl":"https://doi.org/10.18662/brain/15.2/561","url":null,"abstract":"With the development of the IoT domain, the volume of data produced by various applications has also increased. Due to multiple reasons, such as sensor failure, communication system failure, and human errors, the data acquired from the sensors have missing values. The presence of missing values in the dataset affects the informational content of the dataset and thus affects the process of extracting knowledge from the data. In this paper, the authors present a comparative analysis of the performances of the methods of filling in the missing values, such as method, Interpolation, Mean, the K-Nearest Neighbors (KNN), and Random Forests (RF), on the data coming from a Predictive Maintenance (PdM) system that can be used at Unmanned Aerial Vehicle (UAV). The data on which the performance of these methods has been studied comes from a PdM system from the UAVs, used to identify the defects of the Brushless DC (BLDC) motors and estimate the Remaining Useful Life (RUL) of Li-ion batteries.","PeriodicalId":504804,"journal":{"name":"BRAIN. Broad Research in Artificial Intelligence and Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141675942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article reviews the scientific research related to the appropriate use of partial deprivation of natural ethics for drug rehabilitation in a specialized centre. The article’s significance stems from the alarming increase in drug addiction, its widespread availability and the conflicting perspectives within the realms of andragogy, bioethics and neuroethics. The latter specifically pertains to the core of human identity. The article aims to synthesize scientific viewpoints on the problem in question, delineate the neuro- and bioethical realities within individual rehabilitation centres, contrast them with the multi-faceted ethical considerations and evaluate the usefulness of limiting certain natural rights of the client (denying sensory gratification) for therapeutic reasons. The authors of the article experienced limited access to information because of the extended, isolated nature of rehabilitation, in addition to ethical considerations. Therefore, the principal data collection methods included andragogical observations, monitoring of clients’ neurophysiological responses and conditions, examination of diaries maintained by centre staff, interviews with them and occasional questionnaires administered to clients. The analysis involved a neurophysiological interpretation of data without the use of specialized equipment, a summarization of questionnaire findings and an assessment of morally relevant phenomena to gauge their appropriateness and acceptability. The obtained results indicated that ethical considerations regarding interventions in the human body and psyche are indeed pertinent. Nevertheless, these decisions are frequently circumstantial, centring on the central ambition of the article: to alert rehabilitation professionals, medical personnel and legal authorities to the requirement for agreement between the violation of natural human rights and the essential human right to redemption, even in the more severe stages (III-IV) of addiction.
{"title":"Adult Bioethics and Pedagogy in Rehabilitation Centre Practice: Neuroethical Factors","authors":"L. Tomich, Nina Kravets, Olha Barladyn, Valentyn Grushko, Tetiana Biriukova, Halyna Leshchuk","doi":"10.18662/brain/15.2/581","DOIUrl":"https://doi.org/10.18662/brain/15.2/581","url":null,"abstract":"This article reviews the scientific research related to the appropriate use of partial deprivation of natural ethics for drug rehabilitation in a specialized centre. The article’s significance stems from the alarming increase in drug addiction, its widespread availability and the conflicting perspectives within the realms of andragogy, bioethics and neuroethics. The latter specifically pertains to the core of human identity. The article aims to synthesize scientific viewpoints on the problem in question, delineate the neuro- and bioethical realities within individual rehabilitation centres, contrast them with the multi-faceted ethical considerations and evaluate the usefulness of limiting certain natural rights of the client (denying sensory gratification) for therapeutic reasons. The authors of the article experienced limited access to information because of the extended, isolated nature of rehabilitation, in addition to ethical considerations. Therefore, the principal data collection methods included andragogical observations, monitoring of clients’ neurophysiological responses and conditions, examination of diaries maintained by centre staff, interviews with them and occasional questionnaires administered to clients. The analysis involved a neurophysiological interpretation of data without the use of specialized equipment, a summarization of questionnaire findings and an assessment of morally relevant phenomena to gauge their appropriateness and acceptability. The obtained results indicated that ethical considerations regarding interventions in the human body and psyche are indeed pertinent. Nevertheless, these decisions are frequently circumstantial, centring on the central ambition of the article: to alert rehabilitation professionals, medical personnel and legal authorities to the requirement for agreement between the violation of natural human rights and the essential human right to redemption, even in the more severe stages (III-IV) of addiction.","PeriodicalId":504804,"journal":{"name":"BRAIN. Broad Research in Artificial Intelligence and Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141674249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Corina Simionescu, Daniela Marcu, Marius Silviu Măciucă
Sentiment analysis from students' interactions with learning environments is a topic of interest for researchers in the field of education because it can make important contributions to improving the quality of instructional processes through recommendation systems integrated into learning applications, or by improving the quality of courses, by grouping students according to their common interests and providing feedback on school progress. There are two approaches to sentiment analysis: one lexicon-based and another that uses machine learning. In this study, we present a sentiment analysis from two own data sets that represent students' opinions about school. Our goal is to create a model that helps us to automatically label students' opinions, assigning sentiment scores between 0 and 4 (0 for an extremely negative opinion). To train and evaluate the performance of the model, we used opinions collected from 1443 Romanian high school students. The novelty that we propose is the manual labeling system. Our current research which uses a machine learning approach to classify students' opinions obtains an accuracy of 86.507%.
{"title":"Toward Better Education Quality through Students’ Sentiment Analysis Using AutoML","authors":"Corina Simionescu, Daniela Marcu, Marius Silviu Măciucă","doi":"10.18662/brain/15.2/578","DOIUrl":"https://doi.org/10.18662/brain/15.2/578","url":null,"abstract":"Sentiment analysis from students' interactions with learning environments is a topic of interest for researchers in the field of education because it can make important contributions to improving the quality of instructional processes through recommendation systems integrated into learning applications, or by improving the quality of courses, by grouping students according to their common interests and providing feedback on school progress. There are two approaches to sentiment analysis: one lexicon-based and another that uses machine learning. In this study, we present a sentiment analysis from two own data sets that represent students' opinions about school. Our goal is to create a model that helps us to automatically label students' opinions, assigning sentiment scores between 0 and 4 (0 for an extremely negative opinion). To train and evaluate the performance of the model, we used opinions collected from 1443 Romanian high school students. The novelty that we propose is the manual labeling system. Our current research which uses a machine learning approach to classify students' opinions obtains an accuracy of 86.507%.","PeriodicalId":504804,"journal":{"name":"BRAIN. Broad Research in Artificial Intelligence and Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141675980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this article, we take a view of ignorance in relation to the new meaning of rationality, including the specific perspectives of limited rationality. We begin by suggesting that the problem of ignorance is far from the implied clarity of everyday expression, and there is a risk of inappropriate use of the concept. We show that not understanding what ignorance is, is part of ignorance, trying to avoid the situation of ignorance over ignorance. We propose a definition of ignorance by reference to the possible accessible and useful knowledge at a given time, suggesting that the understanding of ignorance is dependent on three variables: time, knowledge accessible at each moment of the present and utility. We analyze some asymmetries, including the one caused by the fact that we are often rigorous (but, nevertheless, interested) judges of others ignorance and very biased (that is, somewhat ignorant) about ourselves. We assess responsibility for our own ignorance by suggesting some limitations to the forms of ignorance for which we are responsible. We suggest that some variants of the unknown meet the definition of ignorance, and if we consider that most human decisions are made in conditions of information poverty, we can find that ignorance is frequently part of our cognitive strategies. Ignorance can be intentionally included in some of our cognitive strategies, one of which is provided by the principle of cognitive economics. The article can be one of the starting points for a set of recommendations on what can be ignored, what should and should not be ignored, when we are ignorant with no considerable effect and where/when we should not be
{"title":"A Reassessment of Ignorance from the Perspective of the New Meanings of Rationality","authors":"Viorel Rotilă","doi":"10.18662/brain/15.2/575","DOIUrl":"https://doi.org/10.18662/brain/15.2/575","url":null,"abstract":"In this article, we take a view of ignorance in relation to the new meaning of rationality, including the specific perspectives of limited rationality. We begin by suggesting that the problem of ignorance is far from the implied clarity of everyday expression, and there is a risk of inappropriate use of the concept. We show that not understanding what ignorance is, is part of ignorance, trying to avoid the situation of ignorance over ignorance. We propose a definition of ignorance by reference to the possible accessible and useful knowledge at a given time, suggesting that the understanding of ignorance is dependent on three variables: time, knowledge accessible at each moment of the present and utility. We analyze some asymmetries, including the one caused by the fact that we are often rigorous (but, nevertheless, interested) judges of others ignorance and very biased (that is, somewhat ignorant) about ourselves. We assess responsibility for our own ignorance by suggesting some limitations to the forms of ignorance for which we are responsible. We suggest that some variants of the unknown meet the definition of ignorance, and if we consider that most human decisions are made in conditions of information poverty, we can find that ignorance is frequently part of our cognitive strategies. Ignorance can be intentionally included in some of our cognitive strategies, one of which is provided by the principle of cognitive economics. The article can be one of the starting points for a set of recommendations on what can be ignored, what should and should not be ignored, when we are ignorant with no considerable effect and where/when we should not be","PeriodicalId":504804,"journal":{"name":"BRAIN. Broad Research in Artificial Intelligence and Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141675834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
From four-function calculators to calculators (or computers) with Computer Algebra System (CAS) software, Mathematics computing technology has advanced. With just a few button pushes, CASs can solve a wide range of mathematical problems, which is a true quantum leap in technology. The implications of having software in the classroom that can, for example, expand and factorize algebraic expressions, solve equations, differentiate functions, and find anti-derivatives are causing the mathematical community to engage in a heated debate about whether this is one of the most exciting or frightening developments in the history of education. It was only a matter of time before Artificial Intelligence entered the field of Science. This is now also the case with Mathematics, one of the dominant, perhaps the most basic, but also the most "difficult" of the sciences. The human mind, for better or for worse, has its limits. As we see in every manifestation of our lives, in this case, technology is being enlisted to help humanity take the next step, whether it has to do with automation and practical matters, or with knowledge and exploration. Creating a model that is understandable to humans is the primary objective of Artificial Intelligence. Additionally, concepts and methods from numerous mathematical fields can be used to prepare these models. In this paper, we will examine the use of AI in CASs and explore some ways to optimize them. The documentation sheets are the data source that we used to examine their characteristics. The research results reveal that there are many tips that we can follow to accelerate performance.
从四功能计算器到装有计算机代数系统（CAS）软件的计算器（或计算机），数学计算技术不断进步。只需按下几个按钮，CAS 就能解决各种数学问题，这是技术上真正的飞跃。例如，在课堂上使用可以展开和因式分解代数表达式、解方程、微分函数和求反衍数的软件所产生的影响，正引起数学界的激烈争论，讨论这究竟是教育史上最令人兴奋还是最令人恐惧的发展之一。人工智能进入科学领域只是时间问题。数学现在也是如此，它是最主要的科学之一，也许是最基础的科学，但也是最 "困难 "的科学。人类的思维，无论好坏，都有其局限性。正如我们在生活中的每一种表现形式中看到的那样，在这种情况下，技术正在被用来帮助人类迈出下一步，无论是在自动化和实际事务方面，还是在知识和探索方面。创建人类可以理解的模型是人工智能的首要目标。此外，众多数学领域的概念和方法也可用于制作这些模型。本文将研究人工智能在 CAS 中的应用，并探讨优化 CAS 的一些方法。文件表是我们用来研究其特征的数据源。研究结果表明，我们可以遵循许多技巧来加快性能。
{"title":"Computer Algebra Systems & Artificial Intelligence","authors":"K. Zotos","doi":"10.18662/brain/15.2/584","DOIUrl":"https://doi.org/10.18662/brain/15.2/584","url":null,"abstract":"From four-function calculators to calculators (or computers) with Computer Algebra System (CAS) software, Mathematics computing technology has advanced. With just a few button pushes, CASs can solve a wide range of mathematical problems, which is a true quantum leap in technology. The implications of having software in the classroom that can, for example, expand and factorize algebraic expressions, solve equations, differentiate functions, and find anti-derivatives are causing the mathematical community to engage in a heated debate about whether this is one of the most exciting or frightening developments in the history of education. It was only a matter of time before Artificial Intelligence entered the field of Science. This is now also the case with Mathematics, one of the dominant, perhaps the most basic, but also the most \"difficult\" of the sciences. The human mind, for better or for worse, has its limits. As we see in every manifestation of our lives, in this case, technology is being enlisted to help humanity take the next step, whether it has to do with automation and practical matters, or with knowledge and exploration. Creating a model that is understandable to humans is the primary objective of Artificial Intelligence. Additionally, concepts and methods from numerous mathematical fields can be used to prepare these models. In this paper, we will examine the use of AI in CASs and explore some ways to optimize them. The documentation sheets are the data source that we used to examine their characteristics. The research results reveal that there are many tips that we can follow to accelerate performance.","PeriodicalId":504804,"journal":{"name":"BRAIN. Broad Research in Artificial Intelligence and Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141673377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The purpose of this study was to determine the level of mental imagery ability and attentional style in senior mini-football players and to identify mental behavioral patterns. The study included a number of 38 senior mini-football players, with an average age of 27.36 years, with a playing experience in the super league of 9.38 years. In the study, two standardized questionnaires were applied, one aimed at identifying the level of mental imagery called the Questionnaire for the Assessment of Mental Imaginative Abilities in Athletes (QMIA) with 16 items and one for identifying the attentional style with the aim of determining internal or external dimensions, called the Questionnaire for Assessment of the Attentional Style in Athletes (QASA) with 6 items, structured in two subscales A and B. The calculated reliability of the questionnaire: QMIA had the Cronbach's α value of 0.811 and QASA registered a good reliability evidenced by Cronbach's α of 0.765 for the entire questionnaire; the internal attentional subscale of 0.728, and for the external attentional subscale of 0.726. After analyzing the results, a good level of mental imagery was found that can be perfected, identifying four behavioral patterns. The attentional style highlighted an internal dimension, which highlighted 3 behavioral patterns. At the level of senior mini-football players, in addition to physical, technical and tactical training, psychological training plays an essential role. Cognitive abilities regarding mental imagery and attention are psychological foundations whose development contributes to obtaining significant sports performances in the mini-football game.
{"title":"Mental Imagery and Attentional Style in Senior Mini-Football Players","authors":"Adela Badau","doi":"10.18662/brain/15.2/563","DOIUrl":"https://doi.org/10.18662/brain/15.2/563","url":null,"abstract":"The purpose of this study was to determine the level of mental imagery ability and attentional style in senior mini-football players and to identify mental behavioral patterns. The study included a number of 38 senior mini-football players, with an average age of 27.36 years, with a playing experience in the super league of 9.38 years. In the study, two standardized questionnaires were applied, one aimed at identifying the level of mental imagery called the Questionnaire for the Assessment of Mental Imaginative Abilities in Athletes (QMIA) with 16 items and one for identifying the attentional style with the aim of determining internal or external dimensions, called the Questionnaire for Assessment of the Attentional Style in Athletes (QASA) with 6 items, structured in two subscales A and B. The calculated reliability of the questionnaire: QMIA had the Cronbach's α value of 0.811 and QASA registered a good reliability evidenced by Cronbach's α of 0.765 for the entire questionnaire; the internal attentional subscale of 0.728, and for the external attentional subscale of 0.726. After analyzing the results, a good level of mental imagery was found that can be perfected, identifying four behavioral patterns. The attentional style highlighted an internal dimension, which highlighted 3 behavioral patterns. At the level of senior mini-football players, in addition to physical, technical and tactical training, psychological training plays an essential role. Cognitive abilities regarding mental imagery and attention are psychological foundations whose development contributes to obtaining significant sports performances in the mini-football game.","PeriodicalId":504804,"journal":{"name":"BRAIN. Broad Research in Artificial Intelligence and Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141837242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alexandra Cristina Rusu, R. Chistol, Simona-Irina Damian, Klara Brînzaniuc, Karin Ursula Horvath
Diabetic retinopathy (DR) is a microvascular disorder caused by the long-term effects of diabetes mellitus and among the primary causes of blindness worldwide. Early detection of DR is the key to its effective treatment and subsequent reduction of associated economic burden, but manual screening is time-consuming and of limited availability. A highly sensitive and specific automatic diagnostic tool would significantly improve screening programs and allow referring for further evaluation and treatment in an ophthalmology clinic only patients with significant lesions or with changes between two successive evaluations. Several deep learning-based automated diagnosis tools have been proposed to aid screening but their implementation with minimal costs is not accessible to physicians with no coding knowledge. We aimed to develop a fundus images classification model with no coding knowledge by using generative artificial intelligence (AI) implemented in Windows 11 operating system under subscription (Copilot Pro), a free image analysis tool (Fiji ImageJ2), and Vertex AI, a machine learning (ML) platform launched by Google in 2021. For this purpose, we selected a total of 2961 labelled cases from the APTOS 2019 database of DR fundus images. Images were batch segmented using a Java ImageJ script generated by Copilot Pro and based on the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm. Segmented images were used to train an automated ML classification model to detect DR severity (5 classes – no DR, mild non-proliferative DR, moderate DR, severe DR, proliferative DR). The model achieved an area under the precision-recall curve of 0.889, with a precision rate of 83.8% and a recall rate of 77%. In conclusion, generative AI implemented into Windows operating system together with a free imaging processing tool and Vertex AI allow ophthalmologists with no coding knowledge to benefit from publicly available image databases (thousands of cases) to develop accurate automated diagnostic tools. Such tools have the potential to facilitate screening especially in areas with few specialists.
糖尿病视网膜病变（DR）是一种由糖尿病长期影响引起的微血管疾病，也是全球失明的主要原因之一。早期发现糖尿病视网膜病变是有效治疗和减轻相关经济负担的关键，但人工筛查耗时且可用性有限。高灵敏度和特异性的自动诊断工具将极大地改进筛查计划，并使眼科诊所仅对有明显病变或在两次连续评估之间有变化的患者进行进一步评估和治疗。目前已提出了几种基于深度学习的自动诊断工具来帮助筛查，但没有编码知识的医生无法以最低成本实施这些工具。我们的目标是开发一种无需编码知识的眼底图像分类模型，方法是使用 Windows 11 操作系统中的生成式人工智能（AI）、免费图像分析工具（Fiji ImageJ2）和谷歌于 2021 年推出的机器学习（ML）平台 Vertex AI。为此，我们从 APTOS 2019 DR 眼底图像数据库中选取了 2961 个标记病例。我们使用 Copilot Pro 生成的 Java ImageJ 脚本，基于对比度受限自适应直方图均衡化（CLAHE）算法对图像进行了批量分割。分割后的图像被用于训练自动 ML 分类模型，以检测 DR 的严重程度（5 个等级：无 DR、轻度非增殖性 DR、中度 DR、重度 DR、增殖性 DR）。该模型的精确度-召回曲线下面积为 0.889，精确率为 83.8%，召回率为 77%。总之，在 Windows 操作系统中实施的生成式人工智能以及免费的成像处理工具和 Vertex AI，可以让没有编码知识的眼科医生从公开的图像数据库（成千上万的病例）中获益，从而开发出准确的自动诊断工具。这些工具具有促进筛查的潜力，尤其是在专家较少的地区。
{"title":"Potential Screening, Grading and Follow-Up of Diabetic Retinopathy in Primary Care Using Artificial Intelligence – How Hard Would It Be to Implement? An Ophthalmologist’s Perspective","authors":"Alexandra Cristina Rusu, R. Chistol, Simona-Irina Damian, Klara Brînzaniuc, Karin Ursula Horvath","doi":"10.18662/brain/15.2/576","DOIUrl":"https://doi.org/10.18662/brain/15.2/576","url":null,"abstract":"Diabetic retinopathy (DR) is a microvascular disorder caused by the long-term effects of diabetes mellitus and among the primary causes of blindness worldwide. Early detection of DR is the key to its effective treatment and subsequent reduction of associated economic burden, but manual screening is time-consuming and of limited availability. A highly sensitive and specific automatic diagnostic tool would significantly improve screening programs and allow referring for further evaluation and treatment in an ophthalmology clinic only patients with significant lesions or with changes between two successive evaluations. Several deep learning-based automated diagnosis tools have been proposed to aid screening but their implementation with minimal costs is not accessible to physicians with no coding knowledge. We aimed to develop a fundus images classification model with no coding knowledge by using generative artificial intelligence (AI) implemented in Windows 11 operating system under subscription (Copilot Pro), a free image analysis tool (Fiji ImageJ2), and Vertex AI, a machine learning (ML) platform launched by Google in 2021. For this purpose, we selected a total of 2961 labelled cases from the APTOS 2019 database of DR fundus images. Images were batch segmented using a Java ImageJ script generated by Copilot Pro and based on the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm. Segmented images were used to train an automated ML classification model to detect DR severity (5 classes – no DR, mild non-proliferative DR, moderate DR, severe DR, proliferative DR). The model achieved an area under the precision-recall curve of 0.889, with a precision rate of 83.8% and a recall rate of 77%. In conclusion, generative AI implemented into Windows operating system together with a free imaging processing tool and Vertex AI allow ophthalmologists with no coding knowledge to benefit from publicly available image databases (thousands of cases) to develop accurate automated diagnostic tools. Such tools have the potential to facilitate screening especially in areas with few specialists.","PeriodicalId":504804,"journal":{"name":"BRAIN. Broad Research in Artificial Intelligence and Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141675124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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