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1
Motomura, Yoichi. "Future Artificial Intelligence Technology". Proceedings of the Symposium on Evaluation and Diagnosis 2016.15 (2016): 0spec. http://dx.doi.org/10.1299/jsmesed.2016.15.0spec.
2
Torgautova, B. A., e K. M. Osmonaliyev. "On the issue of criminal liability for acts committed with the use of artificial intelligence for criminal purposes". Eurasian Scientific Journal of Law, n. 1 (6) (19 aprile 2024): 41–47. http://dx.doi.org/10.46914/2959-4197-2024-1-1-41-47.
Abstract (sommario):
This article discusses criminal liability committed with the use of artificial intelligence (AI) for criminal purposes. The paper identifies such problems as a dynamically developing environment with the participation of artificial intelligence, which forms criminological risks, namely, obtaining information in telecommunications networks and information infrastructure facilities, which, as stated in the article, are not protected from any attacks. In the study, we rely on the scientific works of foreign and domestic authors, which were published in different periods of time on the study of artificial intelligence, as well as information disseminated by the media. Thus, based on this problem, the need for the introduction of regulatory regulation in the situation with artificial intelligence and protection from various attacks was considered.
3
Belkova, Elena. "Works Created by Artificial Intelligence Technologies". Academic Law Journal 23, n. 2 (12 luglio 2022): 153–60. http://dx.doi.org/10.17150/1819-0928.2022.23(2).153-160.
Abstract (sommario):
In the context of the growing use of artificial intelligence technologies, including in the field of intellectual property, civil law science is tasked with developing new conceptual approaches to the legal assessment of the results of activities related to the use of artificial intelligence technologies. The current theory of copyright does not apply to such an object as a work generated by artificial intelligence technology, since artificial intelligence itself is the result of human creative activity. The article considers the possibility of recognizing the qualities of the subject of law in robots with artificial intelligence. Approaches to understanding the work created by artificial intelligence technologies as an object of intellectual rights and its place among other objects to which intellectual rights arise are analyzed. The question of authorship of works generated by artificial intelligence technologies and subjects with intellectual rights to these results is being investigated. It is concluded that it is impossible to recognize authorship for works created by artificial intelligence technologies due to the latter›s lack of legal personality. It is proposed to amend the list of objects of intellectual rights, taking into account the possibilities of artificial intelligence technologies, to produce works in the field of science, literature, art. The lack of personal non-property rights to such works is justified. Entities that have an exclusive right to works generated by artificial intelligence technologies have been identified – technology developers. Proposals have been made to amend Russian civil law.
4
Larrondo, Manuel Ernesto, e Nicolas Mario Grandi. "Artificial intelligence, algorithms and freedom of expression". Metaverse 2, n. 2 (1 settembre 2021): 11. http://dx.doi.org/10.54517/m.v2i2.1790.
Abstract (sommario):
<p>Artificial <span style="font-family: 'Times New Roman';">i</span>ntelligence can be presented as an ally when moderating violent content or apparent news, but its use without human intervention to contextualize and adequately translate the expression leaves open the risk of prior censorship. This is currently under debate in the international arena since, as Artificial Intelligence lacks the capacity to contextualize what it moderates, it is being presented more as a tool for indiscriminate prior censorship than as a moderation aimed at protecting freedom of expression. Therefore, after analyzing international legislation, reports from international organizations and the terms and conditions of Twitter and Facebook, we suggest five proposals to improve algorithmic content moderation. First, we propose that States make their domestic legislation compatible with international standards of freedom of expression. We also urge them to develop public policies consisting of implementing legislation to protect the working conditions of human supervisors of automated content removal decisions. For their part, we believe that social networks should present clear and consistent terms and conditions, adopt internal policies of transparency and accountability about how AI operates in the dissemination and removal of online content and, finally, should conduct prior human rights impact assessments of their AI.</p>
5
Larrondo, Manuel Ernesto, e Nicolas Mario Grandi. "Artificial intelligence, algorithms and freedom of expression". Metaverse 2, n. 2 (1 settembre 2021): 11. http://dx.doi.org/10.54517/met.v2i2.1790.
Abstract (sommario):
<p>Artificial <span style="font-family: 'Times New Roman';">i</span>ntelligence can be presented as an ally when moderating violent content or apparent news, but its use without human intervention to contextualize and adequately translate the expression leaves open the risk of prior censorship. This is currently under debate in the international arena since, as Artificial Intelligence lacks the capacity to contextualize what it moderates, it is being presented more as a tool for indiscriminate prior censorship than as a moderation aimed at protecting freedom of expression. Therefore, after analyzing international legislation, reports from international organizations and the terms and conditions of Twitter and Facebook, we suggest five proposals to improve algorithmic content moderation. First, we propose that States make their domestic legislation compatible with international standards of freedom of expression. We also urge them to develop public policies consisting of implementing legislation to protect the working conditions of human supervisors of automated content removal decisions. For their part, we believe that social networks should present clear and consistent terms and conditions, adopt internal policies of transparency and accountability about how AI operates in the dissemination and removal of online content and, finally, should conduct prior human rights impact assessments of their AI.</p>
6
Golenkov, V. V., N. A. Gulyakina, V. P. Ivashenko e D. V. Shunkevich. "Intelligent Computer Systems of New Generation and Complex Technology of Their Development, Application and Modernization". Doklady BGUIR 22, n. 2 (16 aprile 2024): 70–79. http://dx.doi.org/10.35596/1729-7648-2024-22-2-70-79.
Abstract (sommario):
The paper considers the trends in the development of artificial intelligence technologies in BSUIR for the last five years, lists the main results obtained during this period both in the field of development of artificial intelligence technologies themselves, and in the field of education in artificial intelligence and realization of interaction between teams of specialists working in this field. The necessity of transition to new-generation intelligent computer systems with a high level of interoperability and creation of an appropriate complex technology for their development, maintenance and operation is substantiated. The problems hindering the active development and implementation of new generation intelligent computer systems are considered. The concept of semantic space as a basis for representation and integration of knowledge in intelligent computer systems of new generation is considered. The principles of implementation of hardware platform for interpretation of information processes in the semantic space – associative semantic computer – are considered.
7
Xu, Yina. "Editorial". Metaverse 2, n. 2 (30 dicembre 2021): 1. http://dx.doi.org/10.54517/m.v2i2.1867.
8
Xu, Yina. "Editorial". Metaverse 2, n. 2 (30 dicembre 2021): 1. http://dx.doi.org/10.54517/met.v2i2.1867.
9
Ferrein, Alexander, e Thomas Meyer. "A Brief Overview of Artificial Intelligence in South Africa". AI Magazine 33, n. 1 (15 marzo 2012): 99–103. http://dx.doi.org/10.1609/aimag.v33i1.2357.
Abstract (sommario):
One of the consequences of the growth in AI research in South Africa in recent years is the establishment of a number of research hubs involved in AI activities ranging from mobile robotics and computational intelligence, to knowledge representation and reasoning, and human language technologies. In this survey we take the reader through a quick tour of the research being conducted at these hubs, and touch on an initiative to maintain and extend the current level of interest in AI research in the country.
10
Li, Wanting, Haiyan Liu, Feng Cheng, Yanhua Li, Sijin Li e Jiangwei Yan. "Artificial intelligence applications for oncological positron emission tomography imaging". European Journal of Radiology 134 (gennaio 2021): 109448. http://dx.doi.org/10.1016/j.ejrad.2020.109448.
11
Olukunle, Ibukun, e Foluke Rachael. "Artificial intelligence and accounting practice in Nigerian banking industry". BOHR International Journal of Finance and Market Research 2, n. 1 (2023): 61–69. http://dx.doi.org/10.54646/bijfmr.2023.23.
Abstract (sommario):
This study critically examined the impact of artificial intelligence on accounting practice in the Nigerian banking industry. To attain the objectives of the study, a regression and correction model comprising independent variables (automation process, expert system, and intelligent agent) and dependent variables (accounting practice) was specified for the study. The data for this study were obtained from a primary source where a survey was carried out on banking industries in Nigeria; 133 respondents were chosen as the sample size, of which 128 were returned. The data were analyzed using regression method of inferential statistics to test the significance of hypotheses using the t-statistics of co-efficient with the generated p-values. The findings revealed that all three variables (automation process, expect system, and intelligent agent) have a significant effect on accounting practice in deposit money banks (DMBs) industries in Nigeria. Therefore, the conclusion is that artificial intelligence enhances accounting practice in selected DMBs industries in Nigeria. It was recommended that banking industries and accountants, by improving their knowledge of artificial intelligence and enhancing their performance, will be able to eliminate some unwanted accounting costs.
12
Kozlova, N. V. "Intellectual property law: In the hands of artificial creator". Digital Law Journal 2, n. 2 (18 luglio 2021): 65–70. http://dx.doi.org/10.38044/2686-9136-2021-2-2-65-70.
13
Kott, A. G., D. A. Legkodymov e E. A. Fursova. "Transformation of business systems and international logistics technologies under the influence of digitization trends". Transport Technician: Education and Practice 5, n. 1 (15 marzo 2024): 83–88. http://dx.doi.org/10.46684/2687-1033.2024.1.83-88.
Abstract (sommario):
The scientific article refl ects the main results of a comprehensive researching of the process of transformation of business systems and international logistics technologies under the influence of digitalization trends, primarily artificial intelligence, in the context of the widespread introduction of Industry 4.0 conceptual approaches into economic, production and distribution cycles.In the context of the globalization of the economy and the rapid development of technology, key changes in the processes of managing integrated supply chains under the influence of digital technologies and intelligent systems are considered. The aspects discussed in this article, ranging from digital tools in warehouse management to the use of blockchain and artificial intelligence in international logistics, highlight the importance of innovation in this area. Modern technologies such as warehouse management systems, robotic technologies, blockchain and artificial intelligence show potential for improving the efficiency of logistics processes and optimizing costs.The scientific significance of this study lies in understanding these technological changes and their impact on international logistics structures. The emphasis in the work is on identifying the main trends affecting the efficiency and sustainability of logistics systems in the context of digitalization at the present stage of scientific and technological progress and informatization of society. In conditions of constant competition, the timely introduction of new technologies is one of the critical factors for the successful positioning of a company in the market.
14
Garni, Stefanie Nicole, Nando Mertineit, Gerd Nöldge, Keivan Daneshvar e Frank Mosler. "Regulatory Needs for Radiation Protection Devices based upon Artificial Intelligence". Swiss Journal of Radiology and Nuclear Medicine 5, n. 1 (24 febbraio 2024): 5. http://dx.doi.org/10.59667/sjoranm.v5i1.11.
Abstract (sommario):
Artificial intelligence (AI) is increasingly employed in radiation protection, encompassing both medical devices and software. These technologies are integrated with AI throughout their manufacturing and application processes. This article underscores the imperative for comprehensive regulation in the utilization of AI. Decisions regarding AI application should not solely rest with manufacturers, medical professionals, or patients. Instead, an overarching "neutral" authority must be engaged to regulate, review, and enforce adherence to established protocols. The authors contend that relying on "self-regulation" within the free market, absent clear guidelines, proves to be inadequately effective and leads to patient's radiation protection safety issues.
15
Thadphoothon, Janpha. "ELT in the Age of Artificial Intelligence (AI): Working with Machines". Journal of NELTA 27, n. 1-2 (31 dicembre 2022): 202–12. http://dx.doi.org/10.3126/nelta.v27i1-2.53203.
Abstract (sommario):
Since 2016, the development of artificial intelligence (AI) has been strong and pervasive, including its roles in business and education. In ELT, in particular, several machine learning models have been implemented such as speech recognition, grammar correction, chatbots, and translation. ELT is in the middle of a rapid and disruptive change and the magnitude of which is paramount that we have never witnessed before. Under this situation, ELT practitioners may have to acquire additional skills and competencies so as to be relevant and thrive in this rapid change and move the field forward to the next level. In this paper, the researcher proposes ELT 3.0, a new vision where working with the machines needs to be incorporated into the existing roles of the ELT teachers.
16
Rana, Humza, e Minhaj Ahmad Khan. "Detection of Malware Attacks using Artificial Neural Network". VAWKUM Transactions on Computer Sciences 11, n. 2 (31 dicembre 2023): 98–112. http://dx.doi.org/10.21015/vtcs.v11i2.1692.
Abstract (sommario):
Malware attacks are increasing rapidly as the technology continues to become prevalent. These attacks have become extremely difficult to detect as they continuously change their mechanism for exploitation of vulnerabilities in software. The conventional approaches to malware detection become ineffective due to a large number of varying patterns and sequences, thereby requiring artificial intelligence-based approaches for the detection of malware attacks. In this paper, we propose an artificial neural network-based model for malware detection. Our proposed model is generic as it can be applied to multiple datasets. We have compared our model with different machine-learning approaches. The experimentation results show that the proposed model can outperform other well-known approach as it achieves 99.6\% , 98.9\% and 99.9\% accuracy on the Windows API call dataset, Top PE Imports Dataset and Malware Dataset, respectively.
17
Diego Felipe, Arbeláez-Campillo, Villasmil Espinoza Jorge Jesus e Rojas-Bahamón Magda Julissa. "Artificial intelligence and the human condition: Opposing entities or complementary forces?" Metaverse 2, n. 2 (17 settembre 2021): 9. http://dx.doi.org/10.54517/m.v2i2.1792.
Abstract (sommario):
<p>In the 21st century<span style="font-family: 'Times New Roman';">,</span> artificial intelligence is constituted as a force that in many ways surpasses fiction, because in a certain way it is already present in all areas of social life, from internet search engines to determine tastes and preferences in accessing digital information, to intelligent refrigerators capable of issuing purchase orders to maintain the availability of certain foods as they run out. The aim of this essay is to analyze the possible ethical, ontological and legal issues arising from the widespread use of artificial intelligence in today’s societies, as a preliminary attempt to resolve the question posed in the title. Methodologically, it is an essay developed using written documentary sources, such as: Literary works, international press articles and refereed articles published in scientific journals. It is concluded, that AI have the potential to disrupt the lifestyles of civilization in general in many ways reaching, even, to alter the human condition in a negative way by changing its identity and genetic integrity and weakening the protagonist of people in the construction of their own realities.</p>
18
Diego Felipe, Arbeláez-Campillo, Villasmil Espinoza Jorge Jesus e Rojas-Bahamón Magda Julissa. "Artificial intelligence and the human condition: Opposing entities or complementary forces?" Metaverse 2, n. 2 (17 settembre 2021): 9. http://dx.doi.org/10.54517/met.v2i2.1792.
Abstract (sommario):
<p>In the 21st century<span style="font-family: 'Times New Roman';">,</span> artificial intelligence is constituted as a force that in many ways surpasses fiction, because in a certain way it is already present in all areas of social life, from internet search engines to determine tastes and preferences in accessing digital information, to intelligent refrigerators capable of issuing purchase orders to maintain the availability of certain foods as they run out. The aim of this essay is to analyze the possible ethical, ontological and legal issues arising from the widespread use of artificial intelligence in today’s societies, as a preliminary attempt to resolve the question posed in the title. Methodologically, it is an essay developed using written documentary sources, such as: Literary works, international press articles and refereed articles published in scientific journals. It is concluded, that AI have the potential to disrupt the lifestyles of civilization in general in many ways reaching, even, to alter the human condition in a negative way by changing its identity and genetic integrity and weakening the protagonist of people in the construction of their own realities.</p>
19
Belousov, Yu V., e O. I. Timofeeva. "Forecast of the digitalization impact on public financial management". World of new economy 16, n. 4 (17 gennaio 2023): 113–23. http://dx.doi.org/10.26794/2220-6469-2022-16-4-113-123.
Abstract (sommario):
Modern digital technologies based on artificial intelligence and big data have a significant impact on many areas of the socioeconomic life of society. At present, digitalization has not affected the public financial management system to a small extent. However, this particular area has a high potential for the use of big data and artificial intelligence, as it is based on significant amounts of information, including unstructured information. At the same time, the process, mechanism and forms of the digital technologies impact on public finance management have been little studied in the scientific literature. The paper forecasts changing in the public financial management system that may occur under the influence of digital technologies in the medium and long term. The authors used a methodical approach based on extrapolation for forecasting. Nowadays, digital technologies have significantly influenced some sectors of the socio-economic people’s activity. The forms and mechanisms of such influence had been extrapolated to the public financial management system and, primarily, to various stages of the budget process.
20
Bilski, Piotr, e Jacek Wojciechowski. "Artificial intelligence methods in diagnostics of analog systems". International Journal of Applied Mathematics and Computer Science 24, n. 2 (26 giugno 2014): 271–82. http://dx.doi.org/10.2478/amcs-2014-0020.
Abstract (sommario):
Abstract The paper presents the state of the art and advancement of artificial intelligence methods in analog systems diagnostics. Firstly, the diagnostic domain is introduced and its problems explained. Then, computational intelligence approaches usable for fault detection and identification are reviewed. Particular groups of methods are presented in detail, explaining their usefulness and drawbacks. Examples, such as the induction motor or the electronic filter, are provided to show the applicability of the presented approaches for monitoring the state of analog objects from engineering domains. The discussion section reviews the presented approaches, their future prospects and problems to be solved.
21
Rizal, Fathur, Fuadz Hasyim, Kamil Malik e Yudistira Yudistira. "Implementasi Algoritma Convolutional Neural Networks (CNN) Untuk Klasifikasi Batik". COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi 2, n. 2 (22 febbraio 2022): 40–47. http://dx.doi.org/10.33650/coreai.v2i2.3365.
Abstract (sommario):
Batik adalah salah satu budaya khas Indonesia dan sudah diakui sebagai warisan budaya Internasional oleh UNESCO (The United Nations Educational, Scientific and Cultural Organization) pada tanggal 2 Oktober 2009. Batik telah menjadi warisan budaya turun temurun di seluruh Indonesia khususnya di daerah Jawa. Saat ini ada ratusan motif kain batik dari seluruh penjuru Indonesia. Banyaknya pola batik di Indonesia mengakibatkan sulitnya masyarakat mengidentifikasi motif pada batik. penelitian ini dapat mempermudah pengenalan pola batik. Salah satu teknologi kecerdasan buatan dengan sebutan artificial intelligence (AI) adalah pembelajaran mesin dengan menggunakan metode computer vision Salah satu model pembelajaran mesin tersebut adalah jaringan syaraf tiruan (JST) dengan menggunakan banyak lapisan, sehingga dengan adanya model tersebut maka dapat lebih baik lagi performa komputasi dengan menggunakan teknik Deep Learning. Metode yang digunakan adalah Convolutional Neural Networks (CNN) dengan melakukan klasifikasi gambar pada batik berbasis komputer dengan memanfaatkan kecerdasan buatan (artificial intelligence). Hasil dari penelitian yang telah dilakukan pada pengujian terhadap 200 dataset dan 20 label diperoleh nilai akurasi yang tertinggi adalah “Batik Megamendung dan Batik Celup” dengan nilai akurasi 80% dan 60%, hasil accuracy yang diperoleh dari proses pelatihan model dari 200 epoch yang tertinggi adalah 90%.
22
Yolvi, Ocaña-Fernández, Valenzuela-Fernández Luis Alex, Vera-Flores Miguel Angel e Rengifo-Lozano Raúl Alberto. "Artificial intelligence (AI) applied to public management". Metaverse 2, n. 1 (15 gennaio 2021): 8. http://dx.doi.org/10.54517/m.v2i1.1795.
Abstract (sommario):
<p>The implementation of systems based on artificial intelligence (AI) has passed the barrier of the academic field and due to its potentialities has been developing in other fields such as public management so there is an urgent need to have an updated overview in this regard. This article aims to address the analysis of AI by highlighting its transcendence in the field of management, public administration and government, highlighting the significant opportunities, impact assessment and the potential posed by AI. The present review provides a panoramic and significative overview about AI and its impact on the field of management and public administration, about its achievements, as well as sensitive controversies. Finally, the critical opportunities and challenges of AI application in the public sector are shown.</p>
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Yolvi, Ocaña-Fernández, Valenzuela-Fernández Luis Alex, Vera-Flores Miguel Angel e Rengifo-Lozano Raúl Alberto. "Artificial intelligence (AI) applied to public management". Metaverse 2, n. 1 (15 gennaio 2021): 8. http://dx.doi.org/10.54517/met.v2i1.1795.
Abstract (sommario):
<p>The implementation of systems based on artificial intelligence (AI) has passed the barrier of the academic field and due to its potentialities has been developing in other fields such as public management so there is an urgent need to have an updated overview in this regard. This article aims to address the analysis of AI by highlighting its transcendence in the field of management, public administration and government, highlighting the significant opportunities, impact assessment and the potential posed by AI. The present review provides a panoramic and significative overview about AI and its impact on the field of management and public administration, about its achievements, as well as sensitive controversies. Finally, the critical opportunities and challenges of AI application in the public sector are shown.</p>
24
Yolvi, Ocaña-Fernández, Valenzuela-Fernández Luis Alex, Vera-Flores Miguel Angel e Rengifo-Lozano Raúl Alberto. "Artificial intelligence (AI) applied to public management". Metaverse 3, n. 2 (15 ottobre 2022): 8. http://dx.doi.org/10.54517/m.v3i2.1795.
Abstract (sommario):
<p>The implementation of systems based on artificial intelligence (AI) has passed the barrier of the academic field and due to its potentialities has been developing in other fields such as public management so there is an urgent need to have an updated overview in this regard. This article aims to address the analysis of AI by highlighting its transcendence in the field of management, public administration and government, highlighting the significant opportunities, impact assessment and the potential posed by AI. The present review provides a panoramic and significative overview about AI and its impact on the field of management and public administration, about its achievements, as well as sensitive controversies. Finally, the critical opportunities and challenges of AI application in the public sector are shown.</p>
25
Kuteynikov, D. L., O. A. Izhaev, V. A. Lebedev e S. S. Zenin. "Privacy in the realm of Artificial Intelligence Systems Application for Remote Biometric Identification". Lex Russica, n. 2 (28 febbraio 2022): 121–31. http://dx.doi.org/10.17803/1729-5920.2022.183.2.121-131.
Abstract (sommario):
The paper analyzes legal approaches to solving key problems of human rights implementation in the conditions of mass exploitation of artificial intelligence (AI) systems in the public space. Within the framework of the study, the emphasis is placed on the features of the legal regulation of the use of artificial intelligence systems for remote biometric identification. The use of these systems is currently only beginning to acquire a regulatory legal framework and law enforcement practice in most countries. The study analyzes several different models of legal regulation that are typical of individual countries and regions, such as the United Kingdom, the United States, China, the EU and Russia.In the UK, the use of real-time facial recognition systems in public spaces is allowed, but the set of scenarios and situations of their use is significantly limited by legislation and law enforcement practice. In the United States, both at the federal and state levels, there are no general rules that form a unified legal approach to regulating the area in question. The EC has developed a draft Regulation on Harmonized AI Rules (Artificial Intelligence Act), which is supposed to prohibit the use of AI systems for remote biometric identification of individuals in real time in public places. There is no special regulatory regulation of this sphere of public relations in the PRC. The development of these systems in China is controlled by the state, which, due to the high centralization of power, leads to the risk of human rights violations and the creation of an atmosphere of total surveillance of citizens without any legally established framework and restrictions. In Russia, the state is actively deploying these systems at the federal and regional levels in the absence of a specialized regulatory framework. Human rights are protected only by the general norms of the Constitution of the Russian Federation and legislation, law enforcement practice is mainly aimed at ensuring the interests of the state.
26
Brait, Maximilian, Eduard Koppensteiner, Gerhard Schindelbacher, Jiehua Li e Peter Schumacher. "Artificial Intelligence Approaches to Determine Graphite Nodularity in Ductile Iron". Journal of Casting & Materials Engineering 5, n. 4 (21 dicembre 2021): 94–102. http://dx.doi.org/10.7494/jcme.2021.5.4.94.
Abstract (sommario):
The complex metallurgical interrelationships in the production of ductile cast iron can lead to enormous differences in graphite formation and local microstructure by small variations during production. Artificial intelligence algorithms were used to describe graphite formation, which is influenced by a variety of metallurgical parameters. Moreover, complex physical relationships in the formation of graphite morphology are also controlled by boundary conditions of processing, the effect of which can hardly be assessed in everyday foundry operations. The influence of relevant input parameters can be predetermined using artificial intelligence based on conditions and patterns that occur simultaneously. By predicting the local graphite formation, measures to stabilise production were defined and thereby the accuracy of structure simulations improved. In course of this work, the most important dominating variables, from initial charging to final casting, were compiled and analysed with the help of statistical regression methods to predict the nodularity of graphite spheres. We compared the accuracy of the prediction by using Linear Regression, Gaussian Process Regression, Regression Trees, Boosted Trees, Support Vector Machines, Shallow Neural Networks and Deep Neural Networks. As input parameters we used 45 characteristics of the production process consisting of the basic information including the composition of the charge, the overheating time, the type of melting vessel, the type of the inoculant, the fading, and the solidification time. Additionally, the data of several thermal analysis, oxygen activity measurements and the final chemical analysis were included.Initial programme designs using machine learning algorithms based on neural networks achieved encouraging results. To improve the degree of accuracy, this algorithm was subsequently adapted and refined for the nodularity of graphite.
27
Meldo, A. A., L. V. Utkin e T. N. Trofimova. "Artificial intelligence in medicine: current state and main directions of development of the intellectual diagnostics". Diagnostic radiology and radiotherapy 11, n. 1 (1 aprile 2020): 9–17. http://dx.doi.org/10.22328/2079-5343-2020-11-1-9-17.
Abstract (sommario):
The main difference between artificial intelligence (AI) systems and simple automated algorithms is the ability to learn, synthesize and conclude. The AI system is trained on a set of examples, including pictures, characteristics of patients with a certain disease, then it allows to generalize a lot of such examples and get some general functional dependence, which brings in line the patient data and a certain diagnosis. The system can be named intelligent if this synthetizing ability is realized. Although the AI systems are now becoming more understood and accepted by doctors, a deeper understanding of «how it works» is needed. The article provides a detailed review of the application of methods and models of artificial intelligence in the diagnostics of cancer based on the of multimodal instrumental data. The basic concepts of artificial intelligence and directions of its development are presented. From the point of view of data processing, the stages of development of AI systems are identical. The stages of intellectual processing of diagnostic data are considered in the paper. They include the acquisition and use of training databases of oncological diseases, pre-processing of images, segmentation to highlight the studied objects of diagnosis and classification of these objects to determine whether they are malignant or benign. One of the problems limiting the acceptance of AI systems development by the medical community is the imperfection of the explainability of the results obtained by intelligent systems. Authors pay attention to importance of the development of so-called explanatory intelligence, because its absence currently significantly inhibits the introduction and use of intelligent diagnostic systems in medicine. In addition, the purpose of the article is a way to develop the interaction between a radiologists and data scientists.
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Ghulam, Ali, Rahu Sikander e Farman Ali. "AI and Machine Learning-based practices in various domains: A Survey". VAWKUM Transactions on Computer Sciences 10, n. 1 (30 giugno 2022): 21–41. http://dx.doi.org/10.21015/vtcs.v10i1.1257.
Abstract (sommario):
In several projects in computational biology (CB), bioinformatics, health informatics(HI), precision medicine(PM) and precision agriculture(PA) machine learning(ML) has become a primary resource. In this paper we studied the use of machine learning in the development of computational methods for top five research aeras. The last few years have seen an increased interest in Artificial Intelligence (AI), comprehensive ML and DL techniques for computational method development. Over the years, an enormous amount of research has been biomedical scientists still don’t have more knowledge to handle a biomedical projects efficiently and may, therefore, adopt wrong methods, which can lead to frequent errors or inflated tests. Healthcare has become a fruitful ground for artificial intelligence (AI) and machine learning due to the increase in the volume, diversity, and complexity of data (ML). Healthcare providers and life sciences businesses already use a variety of AI technologies. The review summarizes a traditional machine learning cycle, several machine learning algorithms, various techniques to data analysis, and effective use in five research areas. In this comprehensive review analysis, we proposed 10 ten rapid and accurate practices to use ML techniques in health informatics, bioinformatics, computational and systems biology, precision medicine and precision agriculture, avoid some common mistakes that we have observed several hundred times in several computational method works.
29
Rantanen, Esa M., John D. Lee, Katherine Darveau, Dave B. Miller, James Intriligator e Ben D. Sawyer. "Ethics Education of Human Factors Engineers for Responsible AI Development". Proceedings of the Human Factors and Ergonomics Society Annual Meeting 65, n. 1 (settembre 2021): 1034–38. http://dx.doi.org/10.1177/1071181321651038.
Abstract (sommario):
This panel discussion is third in a series examining the educational challenges facing future human factors and ergonomics professionals. The past two panels have focused on training of technical skills in data science, machine learning, and artificial intelligence to human factors students. This panel discussion expands on these topics and argues for a need of new and broader training curricula that include ethics for responsible development of AI-based systems that will touch lives of everybody and have widespread societal impacts.
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Padala, Venkatsai Siddesh, Kathan Gandhi e Pushpalatha Dasari. "Machine Learning: The New Language for Applications". IAES International Journal of Artificial Intelligence (IJ-AI) 8, n. 4 (1 dicembre 2019): 411. http://dx.doi.org/10.11591/ijai.v8.i4.pp411-421.
Abstract (sommario):
<p>Machine learning and artificial intelligence are becoming a major influence in various research and commercial fields. This review attempts to explain machine learning techniques and applications in various fields. Challenges and future directions are also proposed, including data analysis suggestions, effective algorithms based on the situation, industrial implementation, organization’s risk tolerance, cost-benefit comparisons and the future of machine learning techniques. Applications discussed in this paper range from technological development and health care to financial issues and sports analytics.</p>
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Stefanova, Tsvetelina, e Slavi Georgiev. "Possibilities for using AI in mathematics education". Mathematics and Education in Mathematics 53 (16 marzo 2024): 117–25. http://dx.doi.org/10.55630/mem.2024.53.117-125.
Abstract (sommario):
Artificial intelligence could be used as a powerful and innovative tool in mathematics education. It is poised to transform the way of learning and teaching this subject.The main objective of our study is to provide a more complete and thorough understanding of the role and impact of using AI in mathematics education by determining the trends, the AI methods, the technological applications and the opportunities for utilizing AI by teachers and students. The potential benefits and threats caused by the use of AI are also discussed.
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Kokin, A. V. "Forensic Expertise in the Era of the Fourth Industrial Revolution (Industry 4.0)". Theory and Practice of Forensic Science 16, n. 2 (30 luglio 2021): 29–36. http://dx.doi.org/10.30764/1819-2785-2021-2-29-36.
Abstract (sommario):
The fourth industrial revolution basing on computer and information technologies, various software, hardware is rapidly gaining momentum in the modern world. First of all, these include big data processing technologies, blockchain, Internet of things, virtual and augmented reality, 3D printing, printed electronics, artificial intelligence, robotics, biotechnology. Alongside the positive effects, it is expected that the revolution will lead to some negative social consequences, including the growth of intellectual and high-tech crime. The article aims to analyze the causes and conditions of emerging new crime resulting from Industry 4.0 and their effect on the development of forensic science.The author highlights that the specific factors which will determine the future of forensic activity are: the appearance of creative and well-educated individuals, the emergence of “grey areas” in law, the development of global partnerships interested in international supranational rule-making, increasing of transnational crime. The rapid development of science and technology will require investigators and courts to promptly solve various specific scientific and technical tasks, eventually determining the objects and subjects of new forensic examinations, primarily from the field of information technology. Specialists predict a breakthrough in the development of cognitive computing and expert systems equipped with artificial intelligence, which has considerable potential in forensic science. There are signs of the shaping of a common forensic space, which will include not only existing elements of the institute of forensic examination (state and non-state institutions) but large industrial corporations, as well as the most active, technologically advanced individuals.
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Klimashin, A. G. "Internet-technologies as tool for personal protection during large-scale virus infections". Proceedings of the National Academy of Sciences of Belarus, Humanitarian Series 66, n. 3 (5 agosto 2021): 278–82. http://dx.doi.org/10.29235/2524-2369-2021-66-3-278-282.
Abstract (sommario):
The article describes how internet-technologies can contribute to the protection of the individual during the spread of viral diseases or natural disasters. Remote work is largely implemented by modern internet-technologies that provide joint data processing and effective communication between members of different communities. At the same time, the communication must remain protected from leaks of personal information. Artificial intelligence actively uses in searching medicines. In this time all of this increase degree of using informational technologies and we have sharpened the range of information security problems.
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Rivière, Jérémy, Carole Adamn e Sylvie Pesty. "Un ACA sincère, affectif et expressif comme compagnon artificiel". Revue d'intelligence artificielle 28, n. 1 (febbraio 2014): 67–99. http://dx.doi.org/10.3166/ria.28.67-99.
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Lukić, Bojan, Jasper Sprockhoff, Alexander Ahlbrecht, Siddhartha Gupta e Umut Durak. "Iterative Scenario-Based Testing in an Operational Design Domain for Artificial Intelligence Based Systems in Aviation". SNE Simulation Notes Europe 33, n. 4 (dicembre 2023): 183–90. http://dx.doi.org/10.11128/sne.33.tn.10666.
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Poduzova, E. B. "A User Agreement, a Confidentiality Agreement: Content Features in the context of the Use of Artificial Intelligence Technologies". Actual Problems of Russian Law 18, n. 2 (6 ottobre 2022): 71–78. http://dx.doi.org/10.17803/1994-1471.2023.147.2.071-078.
Abstract (sommario):
Artificial Intelligence technologies have a wide scope of application, in particular, they are used to process large amounts of information; these technologies constitute one of the elements of Big Data. In the information environment, conclusion and execution of a user agreement and confidentiality agreement are of particular importance. These agreements form a reliable means of regulating the information interaction between their parties. There is no solution either in the doctrine or in jurisprudence to a number of problems related to these agreements, in particular the problems of their legal characterization, constitutive features and content, including formulation of a number of conditions. The paper provides recommendations for solving these problems, in particular, it determines constitutive features, legal characterization of the user agreement and confidentiality agreement, suggests the wording of separate conditions for the agreements under consideration. When writing the article, the author relied on the effective legislation, civil doctrine, judicial and business practice.
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Seliverstov, P. V., V. V. Shapovalov e O. V. Aleshko. "Introduction of telemedicine technologies based on artificial intelligence into practice of providing outpatient care for medical examination". Medical alphabet, n. 28 (9 novembre 2023): 44–49. http://dx.doi.org/10.33667/2078-5631-2023-28-44-49.
Abstract (sommario):
To date, the main focus in the implementation of medical activities is focused on the organization of outpatient care for the population. It is at the level of primary health care, where it is possible to carry out primary prevention measures and the formation of a healthy lifestyle, these issues should be given special attention when providing medical care to the population. One of the main tasks of modern healthcare is to reduce the number of chronic non-communicable diseases of the adult population using modern tools of early preclinical diagnostics. To date, one of the most promising areas that have a significant impact on modern healthcare is digital telemedicine technologies based on artificial intelligence. They can be confidently attributed to the most popular and rapidly developing groups of services developed for primary health care for the purpose of primary diagnostics. Nevertheless, no matter how fast information technologies develop, the opinions of experts in the subject area remain relevant, which significantly enrich the results of the expert opinion.
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Rustam, Zuherman, Fildzah Zhafarina, Jane Eva Aurelia e Yasirly Amalia. "Twin support vector machine using kernel function for colorectal cancer detection". Bulletin of Electrical Engineering and Informatics 10, n. 6 (1 dicembre 2021): 3121–26. http://dx.doi.org/10.11591/eei.v10i6.3179.
Abstract (sommario):
Nowadays, machine learning technology is needed in the medical field. therefore, this research is useful for solving problems in the medical field by using machine learning. Many cases of colorectal cancer are diagnosed late. When colorectal cancer is detected, the cancer is usually well developed. Machine learning is an approach that is part of artificial intelligence and can detect colorectal cancer early. This study discusses colorectal cancer detection using twin support vector machine (SVM) method and kernel function i.e. linear kernels, polynomial kernels, RBF kernels, and gaussian kernels. By comparing the accuracy and running time, then we will know which method is better in classifying the colorectal cancer dataset that we get from Al-Islam Hospital, Bandung, Indonesia. The results showed that polynomial kernels has better accuracy and running time. It can be seen with a maximum accuracy of twin SVM using polynomial kernels 86% and 0.502 seconds running time.
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Yahya Zebari, Amar, Saman M. Almufti e Chyavan Mohammed Abdulrahman. "Bat algorithm (BA): review, applications and modifications". International Journal of Scientific World 8, n. 1 (23 gennaio 2020): 1. http://dx.doi.org/10.14419/ijsw.v8i1.30120.
Abstract (sommario):
Generally, Metaheuristic algorithms such as ant colony optimization, Elephant herding algorithm, particle swarm optimization, bat algorithms becomes a powerful methods for solving optimization problems. This paper provides a timely review of the bat algorithm and its new variants.Bat algorithm (BA) is a Swarm based metaheuristic algorithm developed in 2010 by Xin-She Yang, BA has been inspired by the foraging behavior of micro bats, algorithm carries out the search process using artificial bats as search agents mimicking the natural pulse loudness and emission rate of real bats. It has become a powerful swarm intelligence method for solving optimization prob-lems over continuous and discrete spaces. Nowadays, it has been successfully applied to solve problems in almost all areas of opti-mization, and it found to be very efficient. As a result, the literature has expanded significantly, a wide range of diverse applications and case studies has been made base on the bat algorithm.
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Sotirova-Valkova, Kalina. "A pilot conceptualisation of the data space ecosystems for cultural heritage". Mathematics and Education in Mathematics 53 (16 marzo 2024): 92–98. http://dx.doi.org/10.55630/mem.2024.53.092-098.
Abstract (sommario):
The digital heritage sector is among the nine common European data spaces out- lined in the EU Data Act: Health, Industrial, Agriculture, Finance, Mobility, Green Deal, Energy, Public Administration, and Skills. The data space concept is complex, and being linked with the data ecosystem brings together methodologies and techniques from numerous domains: artificial intelligence (AI), text/data mining, data visualisation, mapping, image analysis, audio analysis, network analysis, and rights management. There is a need for clarifying data terminology in use for the GLAM field and transferable methodology to strengthen its’ ongoing datafication and digital skill set. The paper offers a comprehensive literature review (incl. EU Data (space) policy documents) on data spaces and data ecosystems aimed at (1) formulating the main challenges in data collection, data processing, and data maturity for heritage-related information systems and (2) justification of the necessary mindset and digital skill set change for a mature museum. General conclusions are made as well as rec- ommendations for the Bulgarian GLAM sector.
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Carpenter, Chris. "Artificial-Intelligence and Machine-Learning Technique for Corrosion Mapping". Journal of Petroleum Technology 74, n. 01 (1 gennaio 2022): 99–102. http://dx.doi.org/10.2118/0122-0099-jpt.
Abstract (sommario):
This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 202801, “Automated Corrosion Mapping AI and Machine Learning,” by Marc Majors and Travis Harrington, Occidental, and Eric Ferguson, Abyss Solutions, et al. The paper has not been peer reviewed. The complete paper discusses risk reduction and increased fabric-maintenance (FM) efficiency using artificial-intelligence (AI) and machine-learning (ML) algorithms to analyze full-facility imagery for atmospheric corrosion detection and classification. With this tool, a comprehensive and objective analysis of a facility’s health is achievable in a matter of weeks from the time of data collection. This application of AI and ML is a novel approach aimed at gaining a comprehensive understanding of facility-coating integrity and external corrosion threats. Introduction Atmospheric corrosion is the most-significant asset-integrity threat in the Gulf of Mexico (GOM). Offshore facilities require constant inspection and FM—and the significant financial obligation of these activities—to stay ahead of rapid equipment degradation. In general, regulatory codes in the GOM require a visual inspection of pressure equipment and piping on a 5-year frequency at minimum. A common approach is to inspect 20% of the facility per year, with a rolling 5-year inspection plan, to balance the inspection work through time. As a result, in a 5-year inspection cycle, the owner or operator of the facility will not see the condition of the piping or equipment for the 4 years between inspection cycles. Considering the complexity, high areas, overwater, and other difficult-to-inspect areas, gathering data for inspection can be costly and time-consuming and can yield a variable quality of results. An effective asset-integrity program requires full visibility of asset and equipment condition. Prioritizing areas for nondestructive examination (NDE) on high-consequence equipment and piping allows for effective risk reduction and FM planning. To that end, AI and ML are being harnessed to detect, classify, quantify, and report the condition of piping and equipment in the GOM.
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& et al., Ibrahim. "ARTIFICIAL NEURAL NETWORK MODELING OF THE WATER QUALITY INDEX FOR THE EUPHRATES RIVER IN IRAQ". IRAQI JOURNAL OF AGRICULTURAL SCIENCES 51, n. 6 (23 dicembre 2020): 1572–80. http://dx.doi.org/10.36103/ijas.v51i6.1184.
Abstract (sommario):
This study was aimed to investigate the development and evaluation of artificial intelligence techniques by using multilayer neural network. Levenberg–Marquardt back propagation (LMA) training algorithm was applied for calculating drinking water quality index (WQI) for Euphrates river (IRAQ). The transfer functions in the artificial network model were tangent sigmoid and linear for hidden and output layers, respectively. Eleven neurons presented for good prediction for results of (WQI) with a coefficient of correlation >0.97 and statistically calculated WQI values, inferring that the model predictions explain 94% of the variation in the calculated WQI scores. The WQI score of the Euphrates was 142 considered as poor. The analysis of sensitivity revealed that the total dissolved solids (TDS) is the highest effective variable with the relative importance of (26.3%), followed by electrical conductivity (EC) (23.1%), pH (17.3%), calcium (Ca) (0.149), chlorides (Cl) (11.2%), Hardness (5.7%), Temperature (1.3%), respectively. It can be concluded that the model presented in this study gives a useful alternate to WQI assessment, which use sub indices formulae.
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Chaykina, A. V. "Application of Blockchain Technology in Civil Proceedings". Courier of Kutafin Moscow State Law University (MSAL)), n. 12 (17 marzo 2022): 165–70. http://dx.doi.org/10.17803/2311-5998.2021.88.12.165-170.
Abstract (sommario):
The article examines the institutions of civil procedural law, in which, according to the author, it is possible and necessary to use distributed ledger technology (blockchain technology). The author argues that the technology is applicable not only for private legal purposes, but can signifi -cantly change a number of familiar rules of legal proceedings. In particular, the technology of distributed registers can change the procedural guarantees of the independence of state judges, more often involve active citizens in the administration of justice, change the system for reviewing court decisions, contribute to the unification of judicial practice, and reduce the judicial burden on judges. The author also sees the possible benefits of the technology for cases, the making of decisions on which in the future can be implemented using artificial intelligence and machine data analysis. Thus, subject to the correct use of blockchain technology, the state will be able to ensure the modification of those guarantees of justice that are currently considered poorly implemented or unreliable, including due to the development of digital technologies.
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Sunny Joseph, Ajai, e Elizabeth Isaac. "GPU Accelerated real-time Melanoma Detection". International Journal of Engineering & Technology 7, n. 3 (27 giugno 2018): 1208. http://dx.doi.org/10.14419/ijet.v7i3.13169.
Abstract (sommario):
Melanoma is recognized as one of the most dangerous type of skin cancer. A novel method to detect melanoma in real time with the help of Graphical Processing Unit (GPU) is proposed. Existing systems can process medical images and perform a diagnosis based on Image Processing technique and Artificial Intelligence. They are also able to perform video processing with the help of large hardware resources at the backend. This incurs significantly higher costs and space and are complex by both software and hardware. Graphical Processing Units have high processing capabilities compared to a Central Processing Unit of a system. Various approaches were used for implementing real time detection of Melanoma. The results and analysis based on various approaches and the best approach based on our study is discussed in this work. A performance analysis for the approaches on the basis of CPU and GPU environment is also discussed. The proposed system will perform real-time analysis of live medical video data and performs diagnosis. The system when implemented yielded an accuracy of 90.133% which is comparable to existing systems.
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Chiwamba, Simon Hawatichke, Jackson Phiri, Philip O. Y. Nkunika, Mayumbo Nyirenda, Monica M. Kabemba e Philemon H. Sohati. "Machine Learning Algorithms for automated Image Capture and Identification of Fall Armyworm (FAW) Moths". Zambia ICT Journal 3, n. 1 (7 marzo 2019): 1–4. http://dx.doi.org/10.33260/zictjournal.v3i1.69.
Abstract (sommario):
Automated entomology is one of the field that has received a fair attention from the computer scientists and its support disciplines. This can further be confirmed by the recent attention that the Fall Armyworm (FAW) (Spodoptera frugiperda) has received in Africa particularly the Southern African Development Community (SADC). As the FAW is known for its devastating effects, stakeholders such as the Food and Agriculture Organization (FAO), SADC and University of Zambia (UNZA) have agreed to develop robust early monitoring and warning system. To supplement the stakeholders’ efforts, we choose a branch of artificial intelligence that employs deep neural network architectures known as Google TensorFlow. It is an advanced state-of-the-art machine learning technique that can be used to identify the FAW moths. In this paper, we use Google TensorFlow, an open source deep learning software library for defining, training and deploying machine learning models. We use the transfer learning technique to retrain the Inception v3 model in TensorFlow on the insect dataset, which reduces the training time and improve the accuracy of FAW moth identification. Our retrained model achieves a train accuracy of 57 – 60 %, cross entropy of 65 – 70% and validation accuracy of
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Umak, Rushikesh. "Sharing Healthcare Records in the Cloud Using Attribute-Based Encryption and De-Duplication". International Journal for Research in Applied Science and Engineering Technology 9, n. VII (31 luglio 2021): 3345–50. http://dx.doi.org/10.22214/ijraset.2021.37109.
Abstract (sommario):
Cloud based healthcare computing have changed the face of healthcare in many ways. The main advantages of cloud computing in healthcare are scalability of the required service and the provision to upscale or downsize the data storge, collaborating Artificial Intelligence (AI) and machine learning. The current paper examined various research studies to explore the utilization of intelligent techniques in health systems and mainly focused into the security and privacy issues in the current technologies. E-Healthcare is an emerging field of medical informatics, referring to the delivery of health services and information using the Internet and related technologies. Rendering efficient storage and security for all data is very important for cloud computing. Securing and privacy preserving of data is of high priority when it comes to cloud storage. E-Healthcare is the most important source in the healthcare society. E-healthcare system is now being popularized globally. Implementing the E-healthcare system will have more advantages such as online services for teleconsultation (second medical opinion), e-prescription, e-referral, telemonitoring, telecare etc. E-healthcare system provides high level of security and cost-effective use of patients records, information and communication in support of healthcare and health related issues.
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Jittawiriyanukoon, Chanintorn, e Vilasinee Srisarkun. "Simulation for predictive maintenance using weighted training algorithms in machine learning". International Journal of Electrical and Computer Engineering (IJECE) 12, n. 3 (1 giugno 2022): 2839. http://dx.doi.org/10.11591/ijece.v12i3.pp2839-2846.
Abstract (sommario):
<span>In the production, the efficient employment of machines is realized as a source of industry competition and strategic planning. In the manufacturing industries, data silos are harvested, which is needful to be monitored and deployed as an operational tool, which will associate with a right decision-making for minimizing maintenance cost. However, it is complex to prioritize and decide between several results. This article utilizes a synthetic data from a factory, mines the data to filter for an insight and performs machine learning (ML) tool in artificial intelligence (AI) to strategize a decision support and schedule a plan for maintenance. Data includes machinery, category, machinery, usage statistics, acquisition, owner’s unit, location, classification, and downtime. An open-source ML software tool is used to replace the short of maintenance planning and schedule. Upon data mining three promising training algorithms for the insightful data are employed as a result their accuracy figures are obtained. Then the accuracy as weighted factors to forecast the priority in maintenance schedule is proposed. The analysis helps monitor the anticipation of new machines in order to minimize mean time between failures (MTBF), promote the continuous manufacturing and achieve production’s safety.</span>
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Aleynikova, V. I. "Strategies for translating machine errors in automatically generated texts (using GPT-4 as an example)". Philosophical Problems of IT & Cyberspace (PhilIT&C), n. 1 (27 giugno 2023): 39–52. http://dx.doi.org/10.17726/philit.2023.1.4.
Abstract (sommario):
The article discusses the strategies of translation of «machine texts» on the example of generative transformers (GPT). Currently, the study and development of machine text generation has become an important task for processing and analyzing texts in different languages. Modern technologies of artificial intelligence and neural networks allow us to create powerful tools for activities in this field, which are becoming more and more effective every year. Generative transformers are one of such tools. The study of generative transformers also allows developers to create more accurate and efficient machine translation algorithms, which improves the quality of translations and improves the user experience. In this context, the features of machine texts created by generative transformers, their patterns, errors and imperfections, which require special translation strategies, deserve special interest. Today we can say that the generation of unique and relevant texts is a routine task that has been automated. Nevertheless, certain restrictions for the use of such texts still exist, in particular, their use requires the use of appropriate translation strategies. The paper proposes the author’s typology of translation strategies, where, taking into account the features of AST, it is proposed to add a substrategy of tertiary-moderation translation.
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Xiao, Yue, Zhiqing Zeng, Ziyang Deng, Chao Lin e Zuquan Xie. "An Integrated Approach Fusing CEEMD Energy Entropy and Sparrow Search Algorithm-Based PNN for Fault Diagnosis of Rolling Bearings". Computational Intelligence and Neuroscience 2022 (22 luglio 2022): 1–19. http://dx.doi.org/10.1155/2022/4835157.
Abstract (sommario):
This paper solves the problem of difficulty in achieving satisfactory results with traditional methods of bearing fault diagnosis, which can effectively extract the fault information and improve the fault diagnosis accuracy. This paper proposes a novel artificial intelligence fault diagnosis method by integrating complementary ensemble empirical mode decomposition (CEEMD), energy entropy (EE), and probabilistic neural network (PNN) optimized by a sparrow search algorithm (SSA). The vibration signal of rolling bear was firstly decomposed by CEEMD into a set of intrinsic mode functions (IMFs) at different time scales. Then, the correlation coefficient was used as a selection criterion to determine the effective IMFs, and the signal features were extracted by EE as the input of the diagnosis model to suppress the influence of the redundant information and maximize the retention of the original signal features. Afterwards, SSA was used to optimize the smoothing factor parameter of PNN to reduce the influence of human factors on the neural network and improve the performance of the fault diagnosis model. Finally, the proposed CEEMD-EE-SSA-PNN method was verified and evaluated by experiments. The experimental results indicate that the presented method can accurately identify different fault states of rolling bearings and achieve better classification performance of fault states compared with other methods.
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Kaur, Gurpreet, Mohit Srivastava e Amod Kumar. "Genetic Algorithm for Combined Speaker and Speech Recognition using Deep Neural Networks". Journal of Telecommunications and Information Technology 2 (29 giugno 2018): 23–31. http://dx.doi.org/10.26636/jtit.2018.119617.
Abstract (sommario):
Huge growth is observed in the speech and speaker recognition field due to many artificial intelligence algorithms being applied. Speech is used to convey messages via the language being spoken, emotions, gender and speaker identity. Many real applications in healthcare are based upon speech and speaker recognition, e.g. a voice-controlled wheelchair helps control the chair. In this paper, we use a genetic algorithm (GA) for combined speaker and speech recognition, relying on optimized Mel Frequency Cepstral Coefficient (MFCC) speech features, and classification is performed using a Deep Neural Network (DNN). In the first phase, feature extraction using MFCC is executed. Then, feature optimization is performed using GA. In the second phase training is conducted using DNN. Evaluation and validation of the proposed work model is done by setting a real environment, and efficiency is calculated on the basis of such parameters as accuracy, precision rate, recall rate, sensitivity, and specificity. Also, this paper presents an evaluation of such feature extraction methods as linear predictive coding coefficient (LPCC), perceptual linear prediction (PLP), mel frequency cepstral coefficients (MFCC) and relative spectra filtering (RASTA), with all of them used for combined speaker and speech recognition systems. A comparison of different methods based on existing techniques for both clean and noisy environments is made as well.