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Boguslavskaya, Vera V., Ekaterina A. Budnik, Aleksandr S. Mamontov, and Thi Kim Ngoc Trinh. "Nationally oriented lexicography and RFL training." Voprosy leksikografii, no. 24 (2022): 5–29. http://dx.doi.org/10.17223/22274200/24/1.
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The article presents the description and comprehension of the experience of developments in the field of linguistic and regional studies and nationally oriented educational lexicography. The latter is based on the ideas of nationally oriented education and associated with the creation of a linguo-cultural dictionary for citizens of Vietnam who study Russian as a foreign language. Today’s reality is considered to be largely aimed at purely applied aspects of knowledge, including in teaching foreign languages and, in particular, Russian as a foreign language (RFL). In this regard, dictionaries are becoming very significant, among which a special place belongs to the so-called “linguo-cultural dictionary”, which has a relatively recent history of use. Information obtained with the help of such lexicographic sources contributed and contributes to students’ deeper understanding of Russian in real situations. But, since a foreigner “in general” does not exist in nature, the so-called “nationally oriented education”, learning with regard to the national culture of the addressee, becomes more and more relevant. Nationally oriented education implies optimizing the teaching of a specific foreigner the ability to communicate primarily with a native representative of the Russian language and culture, i.e. teaching Russian not just as a foreign language, but as a means of intercultural communication. In this regard, a group of employees of the Pushkin State Russian Language Institute, the authors of this article, together with foreign partners, began to create a concept for a linguo-cultural learner’s dictionary of the so-called “active” type, intended for the Vietnamese audience. This dictionary, as conceived by the developers of the concept, will be focused mainly on a nonphilological audience that will be able to use the relevant information in communication with Russian-speaking partners in business, joint production, etc. As an example, against the background of the Vietnamese linguistic culture, the concept “family” is considered. This concept is part of the basic system of values of the native representatives of the Russian language and culture and in the future nationally oriented linguo-cultural dictionary intended for the Vietnamese audience. The authors declare no conflicts of interests.
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Farysenkova, Lyubov V., and Elnura I. Zhellali. "Forming a methodical thesaurus of a foreign author of a manual on Russian as a foreign language." Russian Language Studies 18, no. 4 (2020): 422–38. http://dx.doi.org/10.22363/2618-8163-2020-18-4-422-438.
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The article aims at investigating the specifics of the modern practice of training foreign authors of Russian as a foreign language (RFL) textbooks and identifying the prospects for the formation of a professional thesaurus of this group on the basis of modern educational technologies. This issue is really relevant, since, as it is shown in the article, there are currently almost no methodological studies and manuals addressed to this group of trainees. At the same time, practice shows that foreign colleagues are in urgent need of diverse methodological support from Russian methodologists. The paper shows that in 1970-1980-s, when such support was purposefully implemented, modern textbooks on RFL were created in foreign countries, which contributed to the Russian language spreading in Europe, Asia and Africa. The research materials were textbooks on the Russian language for foreigners, which marked a certain stage in teaching methods of RFL development. The authors of the article rely on general scientific theoretical research methods: comparative analysis of available sources of information, comparative analysis of the conceptual system of the topic under research, synthesis of their own points of view (or positions), based on the analysis of various ways of solving the problem. The article resulted in the proposed topic of training and consulting materials for potential foreign authors of RFL textbooks, which are supposed to be based on the developed electronic platform, as well as the introduction of materials of the round table Designing a communicative textbook of RFL into the system of professional training and advanced training. The authors concluded that potential foreign authors of RFL textbooks are currently in urgent need of systematic scientific and methodological support. In this regard, it is recommended to intensify work with this contingent, using the potential of domestic methodological research, both classic and modern.
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Chistova, E. V., T. K. Verenich, and E. V. Eremina. "MOODLE-BASED ONLINE COURSE ON TRAINING RUSSIAN AS A FOREIGN LANGUAGE: PECULIARITY OF INSTRUCTIONAL DESIGN." Vektor nauki Tol'yattinskogo gosudarstvennogo universiteta. Seriya Pedagogika i psihologiya, no. 2 (2021): 29–35. http://dx.doi.org/10.18323/2221-5662-2021-2-29-35.
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Due to the proliferation of advanced information technologies and overall digitalization in the post-Covid period, the education system is currently subjected to drastic changes, which in their turn predetermine a new area of theoretical and practical research investigating the issues of distance learning similarly referred to as online learning, e-learning, Web-based training. The present paper reveals the role of digital pedagogy in the modern educational process, evaluates the effectiveness of the most popular learning platform in Russia – the learning management system – Moodle. The brief analysis of the existing online RFL (Russian as a Foreign Language) courses shows a great discrepancy between the insufficient offer and increasing demand for such products in the Chinese educational market. The author describes the experience of the Siberian Federal University in the implementation of the online course “Business Russian” in the educational space of the PRC, featuring the core elements of the course design such as objectives stated, resources used, forms of assessment suggested, as well as the demands and the requirements to the flexible all-in-one approach to Moodle course delivery. The work also provides the interpretation of the poll results, which provide valuable insights into the impressions and the opinions of the students from different countries who have already taken the course.
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Ши, А. В. "TEACHING RUSSIAN AS A FOREIGN LANGUAGE TO STUDENTS THROUGH THE PRISM OF CHINESE MENTALITY." Журнал "Вестник Челябинского государственного педагогического университета", no. 3(181) (September 27, 2024): 235–51. http://dx.doi.org/10.25588/cspu.2024.181.3.011.
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Введение. В статье рассматривают особенности обучения русскому языку как иностранному (РКИ) через призму китайского национального характера и менталитета в XXI веке. Показаны различия как в системе образования, так и в методике преподавания обучения русскому языку в России и в Китае. Акцентируется внимание на том, что обучение русскому языку как иностранного в российских вузах преподавателям необходимо не только владеть знаниями по своему учебному предмету, но понимать культурные и национальные особенности обучающихся из Китая. Материалы и методы. Основными методами исследования явились метод сравнительно-исторического анализа, анализ, систематизация, обобщение научно-методической литературы по проб-леме исследования. На основании проведенного анализа, посвященного исследованиям национальных особенностей китайской аудитории, целесообразно выделить важные черты их менталитета, которые необходимо учитывать в образовательной практике РКИ. Результаты. Отмечено, что национальный характер и менталитет китайцев обусловлен, прежде всего, доминированием в китайской культуре конфуцианства, почтительного отношения к природе, семье и миролюбию. Определено, что при обучении РКИ китайской аудитории российским преподавателям необходимо учитывать специфические национальные черты обучающихся. Для успешной коммуникации с китайскими обучающимися необходимо понимать не только мотивы изучения русского языка, но особенности их национального характера и менталитета. Обсуждение. Выделены критерии эффективности обучения РКИ китайских студентов К ним отнесены: четкость постановки задачи и инструктаж к выполнению задания, практичность моделируемых речевых ситуаций, тематическое содержание с акцентом на национальные ценности, методическая организация обучения с опорой на традиционный подход Китая в образовании студентов. Выделены национальные черты китайской аудитории и варианты организации обучения РКИ. Заключение. Сделан вывод о том, что основными методическими особенностями организации обучения РКИ следует считать учет национального характера и менталитета китайских студентов, ориентацию на коллективное или самостоятельное выполнение заданий, уважительное отношение к обучающимся, оптимальное сочетание устных и письменных заданий, онлайн- и оффлайн-взаимодействия, взаимосвязь пассивных и активных методов обучения. Ключевые слова: русский язык как иностранный; китайцы; национальный характер; менталитет; образование взрослых; педагогика высшей школы. Основные положения: – определена актуальность проблемы обучения РКИ через призму китайского национального характера и менталитета в XXI веке; – выявлены национальные черты китайской аудитории и варианты организации обучения РКИ; – выделены критерии эффективности обучения РКИ китайских студентов. Introduction. The article examines the features of teaching Russian as a foreign language (hereinafter referred to as RFL) through the prism of the Chinese national character and mentality in the 21st century. The differences are shown both in the education system and in the teaching methods of teaching the Russian language in Russia and China. Attention is focused on the fact that teaching Russian as a foreign language in Russian universities requires teachers to have good knowledge of their academic subject, but to understand the cultural and national characteristics of students from China. Materials and methods. The main research methods were the method of comparative historical analysis, analysis, systematization, generalization of scientific and methodological literature on the research problem. Based on the analysis conducted on the research of the national characteristics of the Chinese audience, it is advisable to highlight the following important features of their mentality that must be taken into account in the educational practice of RFL. Results. It is noted that the national character and mentality of the Chinese is determined, first of all, by the dominance of Confucianism in Chinese culture, a respectful attitude towards nature, family and peacefulness. It has been determined that when teaching RFL to Chinese audiences, Russian teachers need to take into account the specific national characteristics of students. For successful communication with Chinese students, it is necessary to understand not only the motives for learning the Russian language, but the peculiarities of their national character and mentality. Discussion. The criteria for the effectiveness of teaching RFL to Chinese students are highlighted, these include clarity of task setting and instructions for completing the task, practicality of simulated speech situations, thematic content with an emphasis on national values, methodological organization of training based on the traditional Chinese approach to student education. The national features of the Chinese audience and options for organizing RFL training are highlighted. Conclusion. It is concluded that the main methodological features of the organization of teaching RFL should be considered taking into account the national character and mentality of Chinese students, focus on collective or independent completion of tasks, respectful attitude towards students, the optimal combination of oral and written tasks, online and offline interactions, passive and active teaching methods. Keywords: Russian as a foreign language; Chinese; national character; Mentality; Adult education; Higher education pedagogy. Highlights: The relevance of the problem of teaching RFL through the prism of the Chinese national character and mentality in the 21st century is determined; National features of the Chinese audience and options for organizing RFL training have been identified; Criteria for the effectiveness of teaching RFL to Chinese students are highlighted.
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Yun, Lyudmila Gienovna. "System of exercises for teaching general knowledge of Russian language and specialty language to Chinese engineering students." Samara Journal of Science 8, no. 1 (2019): 322–30. http://dx.doi.org/10.17816/snv201981319.
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The paper deals with the problem of optimizing the language training process for Chinese engineering students in the framework of joint Sino-Russian programs. The existing curricula on the Russian language as a foreign language (RFL) used to train future engineers have several disadvantages, and therefore do not provide a high level of subject and language competences. This is primarily due to weak contacts between teachers of special disciplines and teachers of the Russian language, the lack of coordination of teaching methods used by Russian and Chinese teachers of Russian. Features of training in a non-linguistic and linguistic environment predetermine the expediency of interconnected teaching of all types of speech activity in Russian. In this case, the system of exercises should be based on taking into account the ethno-psychological characteristics of Chinese students and the learning strategies they use when learning a foreign language. Particular attention should be paid to teaching the language of the specialty on the material of authentic video lectures of subject teachers in Russian. The author concludes that it is necessary to develop nationally oriented teaching aids for Chinese students-non-philologists who study in joint training programs for engineers in 2 + 2 and 3 + 1 schemes.
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Zahraei, Seyed Hassan, and Maria Yu Sidorova. "Authorization as the Problem of the Choice of Case: System of Russian Syntax and the Problems of Teaching RFL." Proceedings of Southern Federal University. Philology 2020, no. 1 (2020): 198–206. http://dx.doi.org/10.18522/1995-0640-2020-1-198-206.
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One of the critical and difficult moments in the development of the Russian language by foreigners is the transfer of subjective meanings. The existing terminological and methodological difficulties in studying this issue do not remove the need to teach in the course of Russian language for foreigners means of expressing subjective meanings. The problem is aggravated by the discrepancies between the description of these means in the grammars of the Russian language, including the academic one and the actual functioning. This is most clearly manifested in the functioning of variable prepositional-case forms (for example, вслед чему-либо, кому-либо – вслед зачем-либо, кем-либо, where only the second form can be used in the function of the authorizer: вслед за академиком Виноградовым). The particular difficulty for foreigners is also deanonymization prepositionalcase forms, the paradigm of values which includes the authorization, such as у кого-либо, для кого-либо, and the like. As a result, the elaboration of a system of rules of use and a system of exercises for training the use of means of expression of subjective meanings requires not only methodological but also theoretical justification. We offer such a justification in the form of systematization of these means based on the concept of «authorization» as used in the functional-communicative grammar of G. A. Zolotova, and a typology of syntaxes made in the same concept (free, structurally-driven, connected). The developed system of rules and exercises is implemented in a textbook for Iranian advanced students and tested in teaching in higher educational institutions of Iran. It includes the development of syntagmatic and paradigmatic of substantive and verbal authorization means, differentiation of syntactic synonymy and limitation of syntactic homonymy, considering stylistic parameters. The rules provide the maximum approximation to the living modern use of substantive and verbal authorization means in compliance with the methodological principles of compactness and consistency of the formulation. The exercises require the development of authorization tools in context, so that students confidently include them in any sentence structure. The interrelated development of form, meaning and function corresponds to the trilateral essence of the language sign, which makes the proposed model of training not only methodically effective, but also theoretically solid and modern.
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I., V. Zhukovyts'kyy, M. Pakhomova V., O. Ostapets D., and I. Tsyhanok O. "DETECTION OF ATTACKS ON A COMPUTER NETWORK BASED ON THE USE OF NEURAL NETWORKS COMPLEX." Science and Transport Progress. Bulletin of Dnipropetrovsk National University of Railway Transport, no. 5(89) (July 7, 2020): 68–79. https://doi.org/10.15802/stp2020/218318.
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<strong>Purpose.</strong> The article is aimed at the development of a methodology for detecting attacks on a computer network. To achieve this goal the following tasks were solved: to develop a methodology for detecting attacks on a computer network based on an ensemble of neural networks using normalized data from the open KDD Cup 99 database; when performing machine training to identify the optimal parameters of the neural network which will provide a sufficiently high level of reliability of detection of intrusions into the computer network. <strong>Methodology.</strong> As an architectural solution of the attack detection module, a two-level network system is proposed, based on an ensemble of five neural networks of the multilayer perceptron type. The first neural network to determine the category of attack class (DoS, R2L, U2R, Probe) or the fact that there was no attack; other neural networks – to detect the type of attack, if any (each of these four neural networks corresponds to one class of attack and is able to identify types that belong only to this class). <strong>Findings.</strong> The created software model was used to study the parameters of the neural network configuration 41–1–132–5, which determines the category of the attack class on the computer network. It is determined that the optimal training speed is 0.001. The ADAM algorithm proved to be the best for optimization. The ReLU function is the most suitable activation function for the hidden layer, and the hyperbolic tangent function – for the output layer activation function. Accuracy in test and validation samples was 92.86 % and 91.03 %, respectively. <strong>Originality.</strong> The developed software model, which uses the Python 3.5 programming language, the integrated development environment PyCharm 2016.3 and the Tensorflow 1.2 framework, makes it possible to detect all types of attacks of DoS, U2R, R2L, Probe classes. <strong>Practical value.</strong> Graphical dependencies of accuracy of neural networks at various parameters are received: speed of training; activation function; optimization algorithm. The optimal parameters of neural networks have been determined, which will ensure a sufficiently high level of reliability of intrusion detection into a computer network.
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Ignatovitch, Tatiana V. "Teaching Russian as a Foreign Language with the Use of LearningApps Service." Russian Language Studies 19, no. 1 (2021): 51–65. http://dx.doi.org/10.22363/2618-8163-2021-19-1-51-65.
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The article describes the experience of using applications of the LearningApps service in the practice of teaching Russian as a foreign language (hereinafter - RFL) to students of the Institute of International Education, Henan University of Science and Technology in the 2018-2020 academic years. The relevance of the topic is due to the lack of a comprehensive description of the potential of the LearningApps service simulators in traditional and distance teaching of foreigners. The purpose of the article is to show the possibilities of LearningApps service simulators as an accompanying electronic resource in teaching various aspects of RFL. The study of the service teaching potential was carried out using the analysis of scientific literature and the study of the service functionality, observation and generalization of pedagogical experience, conversations with students and teachers. In the course of the study, the positive and negative aspects of the resource under consideration were identified. Its advantages for a student are interactivity, individual trajectory of the student's performance, the possibility of receiving prompt advice and multiple execution, game form, availability of a large variety of task templates (more than 20). The advantages of the resource for a teacher are simplicity in learning, lack of linkage of exercises with a certain training platform, which allows including them in printed and electronic teaching aids, availability of ready-made exercises in the public database or possibility to make your own exercises based on them, the ability to use it for different methodological purposes: demonstration, search for information, formation of skills and abilities in different types of speech activity, the possibility of intensive learning of vocabulary, grammar, speaking, listening, control, conducting students individual work, depending on the level of language proficiency. The disadvantages include the impossibility of quick assessment using a point-rating system, the absence of the Cyrillic font in some templates, the absence of some templates in the database. The prospects for using the resource are associated with the need to develop distance learning of RFL.
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Jingyuan Fan, Jingyuan Fan, Guiqin Yang Jingyuan Fan, and Jiyang Gai Guiqin Yang. "DDoS Attack Detection System Based on RF-SVM-IL Model Under SDN." 電腦學刊 32, no. 5 (2021): 031–43. http://dx.doi.org/10.53106/199115992021103205003.
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The data forwarding plane in the Software Defined Network (SDN) is decoupled from the network control plane, which can realize the unified control of the whole network by the controller. Although centralize control provide great convenient in many cases, it is vulnerable to malicious attacks, especially for one of the most threatening attack - Distributed Denial of Service (DDoS). We innovatively propose a machine learning hybrid DDoS attack detection model which provide high precision within short-term. We named our model as RF-SVM-IL, which represents an integration of integrates Random Forest (RF), Support Vector Machine (SVM) and Incremental Learning (IL). The combination of RF and SVM can detect detect attacks in two layers and filter out the easily misclassified samples. Then IL is added to filter new samples to avoid repeated iteration training, and improve the adaptability of the model to dynamic data. Compared with other methods, RF-SVM-IL can detect DDoS attacks in SDN with higher accuracy and shorter time. The experimental results show that the average detection accuracy of RF-SVM-IL model is as high as 98.54%, and the detection time is as low as 2.386s.
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Kuznetsov, Andrey Andreevich. "New type of learning environment based on a cross-platform learning model: methodology and testing." Moscow University Pedagogical Education Bulletin, no. 1 (March 30, 2021): 57–75. http://dx.doi.org/10.51314/2073-2635-2021-1-57-75.
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The author presents a multi-component practical study of a new type of electronic educational environment on the example of the author’s cross-platform project Langteach-online, aimed at teaching foreign students Russian. A new type of elearning environment will allow you to create online courses without the use of Western learning management systems, such as LMS Moodle, Schoology, and others with the integration of mobile devices that are trained in the learning process in mixed and distance formats. The methodology of this study will allow creating multidisciplinary online courses for teachers without special training in information technology and programming, which is especially relevant in the context of the Covid-19 pandemic. Russian cross-platform project Langteach-online is used in teaching foreign citizens Russian at the bachelor’s and master’s levels in a number of higher educational institutions of the Russian Federation in order to form a creative professional personality of a foreign graduate. The multi-format of organized tasks and materials (text, video, audio, graphics, presentations) allows us to talk about the possibility of using cross-platform projects of this type not only for teaching practical courses in foreign languages and RFL, but also other disciplines that are taught in schools and higher educational institutions. Training based on this model can be carried out both in blended and distant formats. The system of technical and methodological organization of a cross-platform project has the fexibility to use it inside the personal web resource of a teacher or educational institution.
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Avdeyeva, Irina Borisovna, and Nadezhda Vladimirovna Krasnokutskaya. "Cognitive styles in methodology of Russian as a foreign language." SHS Web of Conferences 127 (2021): 02014. http://dx.doi.org/10.1051/shsconf/202112702014.
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This article attempts to consider the types of cognitive activity of students in the process of learning foreign languages, including Russian as a foreign language. It contains a synthesis on this topic and practical results of the material implementation developed with the consideration of linguo-cognitive styles of students. Special attention is paid to the analytical cognitive style that is inherent in the students of technical fields. Considering the features of the linguo-cognitive picture of students with a predominantly analytical cognitive style, the authors conclude that these features are innate to the students from European countries who speak European languages and studied within the European educational system. Attention is paid to the consideration of cognitive styles in the existing training materials on RFL. The textbook, created by a group of authors (editor-in-chief Avdeyeva), which is addressed to students of the engineering field, was given as an example. Moreover, the article analyses the special course by Krasnokutskaya, developed at the Pushkin State Russian Language Institute and addressed to European students studying Russian as a foreign language. Based on the analysis and testing of mentioned training materials, conclusions on the feasibility of further development of such manuals are drawn.
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Wang, Zhongxiao. "Evaluation Method of the Influence of Sports Training on Physical Index Based on Deep Learning." Security and Communication Networks 2021 (September 29, 2021): 1–8. http://dx.doi.org/10.1155/2021/6924262.
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With the rapid development of deep learning, computer vision has also become a rapidly developing field in the field of artificial intelligence. Combining the physical training of deep learning will bring good practical value. Physical training has different effects on people’s body shape, physical function, and physical quality. It is mainly reflected in the changes of relevant physical indicators after physical training. Therefore, the purpose of this article is to study the method of evaluating the impact of sports training on physical indicators based on deep learning. This paper mainly uses the convolutional neural network in deep learning to design sports training, then constructs the evaluation system of physical index impact, and finally uses the deep learning algorithm to evaluate the impact of physical index. The experimental results show that the accuracy of the algorithm proposed in this paper is significantly higher than that of the other three algorithms. Firstly, in the angular motion, the accuracy of the mean algorithm is 0.4, the accuracy of the variance algorithm is 0.2, the accuracy of the RFE algorithm is 0.4, and the accuracy of the DLA algorithm is 0.6. Similarly, in foot racing and skill sports, the accuracy of the algorithm proposed in this paper is significantly higher than that of other algorithms. Therefore, the method proposed in this paper is more effective in the evaluation of the impact of physical training on physical indicators.
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Alahmed, Shahad, Qutaiba Alasad, Maytham M. Hammood, Jiann-Shiun Yuan, and Mohammed Alawad. "Mitigation of Black-Box Attacks on Intrusion Detection Systems-Based ML." Computers 11, no. 7 (2022): 115. http://dx.doi.org/10.3390/computers11070115.
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Intrusion detection systems (IDS) are a very vital part of network security, as they can be used to protect the network from illegal intrusions and communications. To detect malicious network traffic, several IDS based on machine learning (ML) methods have been developed in the literature. Machine learning models, on the other hand, have recently been proved to be effective, since they are vulnerable to adversarial perturbations, which allows the opponent to crash the system while performing network queries. This motivated us to present a defensive model that uses adversarial training based on generative adversarial networks (GANs) as a defense strategy to offer better protection for the system against adversarial perturbations. The experiment was carried out using random forest as a classifier. In addition, both principal component analysis (PCA) and recursive features elimination (Rfe) techniques were leveraged as a feature selection to diminish the dimensionality of the dataset, and this led to enhancing the performance of the model significantly. The proposal was tested on a realistic and recent public network dataset: CSE-CICIDS2018. The simulation results showed that GAN-based adversarial training enhanced the resilience of the IDS model and mitigated the severity of the black-box attack.
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Kohrt, Brieanne K., Tory M. Lincoln, and Artemio D. Brambila. "Embedding DBT Skills Training Within a Transactional-Ecological Framework to Reduce Suicidality in a Navajo Adolescent Female." Clinical Case Studies 16, no. 1 (2016): 76–92. http://dx.doi.org/10.1177/1534650116668271.
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American Indian/Alaska Native (AI/AN) youth have higher rates of suicidality than any other ethnic or cultural group in the United States. Dialectical behavior therapy (DBT) is an evidence-based treatment that has been found to reduce suicidality in adolescents, but there is little literature speaking to its efficacy with the AI/AN population. The transactional-ecological model of suicidality helps identify protective factors that can be bolstered at the individual, familial, community, and spiritual levels to reduce suicidality and suicidal contagion in AI/AN youth. The current study examines a case where DBT was culturally adapted and embedded within a transactional-ecological framework to treat a 14-year-old Navajo female with Major Depressive Disorder with psychotic features who presented to a psychiatric inpatient facility following a suicide attempt. The patient’s wish to die was motivated by her belief that her death could lead to positive changes in an extended family system plagued by historical trauma, alcoholism, suicide, and domestic violence. Ongoing assessment was conducted using the Suicide Status Form (SSF), Suicide Probability Scale (SPS), Reasons for Living Scale for Adolescents (RFL-A), and the DBT diary card. Navajo healing traditions were used in conjunction with DBT skills training and enhancement of ecological protective factors. Initial reduction in depression and suicidality was complicated by an increase in homicidal ideation. A comprehensive psychiatric evaluation was completed, and treatment was modified through medication changes, increased mindfulness practice, bolstering support systems, and engagement in a Navajo healing ceremony. Implications for clinicians treating suicidality in Navajo youth are discussed.
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Taniguchi, Koutaro, and Yong Yu. "Evaluation of Short-Term Clinical Effects of a Novel Repetitive Facilitation Exercise Training Program Using a Hemiplegic Elbow Extension Rehabilitation System." Machines 12, no. 2 (2024): 85. http://dx.doi.org/10.3390/machines12020085.
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Repetitive Facilitation Exercise (RFE) is known as an effective rehabilitation method that can elicit brain plasticity. In our previous study, we developed a hemiplegic upper limb rehabilitation system that can train the elbow and shoulder based on RFE theory. The system consists of a selective Arm-DoF constrainable mechanism and a multiple facilitative stimulus timing and duration control system. The selective Arm-DoF constrainable mechanism has three DoF, making it possible to selectively restrict a DoF of the shoulder or elbow. The multiple facilitative stimulation timing and duration control system only has an electrical stimulation source and a vibrator and no large actuators to perform the training exercise. In this study, we undertook an evaluation of the short-term clinical effects of a proposed elbow training program using the hemiplegic upper limb rehabilitation system. The training method consists of two sets, each involving 50 repetitions of the elbow extension exercise programmed in our system. We evaluated the short-term training effects through clinical trials for five stroke patients using the above method. In the evaluation, 10 repetitions of pre/post-tests without any facilitative stimulus were performed before and after the two sets of training. As a result, the maximum angular velocities or the average angular velocities of the elbow extensions improved significantly in most subjects. These results indicate that the quickness or the smoothness of elbow extension movements in the hemiplegic limb improved. Therefore, our clinical experiments support the short-term clinical benefits of the proposed method as well as the practicality of quantitative evaluation using our system.
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Dr Mekala R, Balachandar S, and Dr Chinnaiyan R. "Machine learning approaches for optimal prediction of liver fibrosis cruelty." South Asian Journal of Engineering and Technology 12, no. 1 (2022): 132–41. http://dx.doi.org/10.26524/sajet.2022.12.20.
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 Noninvasive assessment of severity of liver fibrosis is crucial for understanding histology and making decisions on antiviral treatment for chronic HBV in view of the associated risks of biopsy. aimed to develop a computer-assisted assessment system for the evaluation of liver disease severity by using machine leaning classifier based on physical-layer with serum markers. The retrospective data set, including 920 patients, was used to establish Decision Tree classifier (DTC), Random Forest Classifier (RFC), Logistic Regression Classifier (LRC), and Support Vector Classifier (SVC) for liver fibrosis severity assessment. Training and testing samples account for 50% of the data set, respectively. The best indicator combinations were selected in random combinations of 24 indicators including 67 108 760 group indicators by four different machine learning classier. The resulting classifiers prospectively tested in 50% testing patients, and the sensitivity, septicity, overall accuracy, and receiver operating characteristics (ROC) were used to compare four classifiers to existed 19 models. Results show that the RFC-based classifier system, with 9 indicators, is feasible to assess severity for liver fibrosis with diagnostic accuracy (greater than 0.83) superior to existing 19 models. Additional studies based on a large data set with full serum markers and imaging information are necessary to enhance diagnostic accuracy and to expand clinical application.
 
 
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Barkah, Azhari Shouni, Siti Rahayu Selamat, Zaheera Zainal Abidin, and Rizki Wahyudi. "Impact of Data Balancing and Feature Selection on Machine Learning-based Network Intrusion Detection." JOIV : International Journal on Informatics Visualization 7, no. 1 (2023): 241. http://dx.doi.org/10.30630/joiv.7.1.1041.
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Unbalanced datasets are a common problem in supervised machine learning. It leads to a deeper understanding of the majority of classes in machine learning. Therefore, the machine learning model is more effective at recognizing the majority classes than the minority classes. Naturally, imbalanced data, such as disease data and data networking, has emerged in real life. DDOS is one of the network intrusions found to happen more often than R2L. There is an imbalance in the composition of network attacks in Intrusion Detection System (IDS) public datasets such as NSL-KDD and UNSW-NB15. Besides, researchers propose many techniques to transform it into balanced data by duplicating the minority class and producing synthetic data. Synthetic Minority Oversampling Technique (SMOTE) and Adaptive Synthetic (ADASYN) algorithms duplicate the data and construct synthetic data for the minority classes. Meanwhile, machine learning algorithms can capture the labeled data's pattern by considering the input features. Unfortunately, not all the input features have an equal impact on the output (predicted class or value). Some features are interrelated and misleading. Therefore, the important features should be selected to produce a good model. In this research, we implement the recursive feature elimination (RFE) technique to select important features from the available dataset. According to the experiment, SMOTE provides a better synthetic dataset than ADASYN for the UNSW-B15 dataset with a high level of imbalance. RFE feature selection slightly reduces the model's accuracy but improves the training speed. Then, the Decision Tree classifier consistently achieves a better recognition rate than Random Forest and KNN.
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Alzahrani, Abdulsalam O., and Mohammed J. F. Alenazi. "Designing a Network Intrusion Detection System Based on Machine Learning for Software Defined Networks." Future Internet 13, no. 5 (2021): 111. http://dx.doi.org/10.3390/fi13050111.
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Software-defined Networking (SDN) has recently developed and been put forward as a promising and encouraging solution for future internet architecture. Managed, the centralized and controlled network has become more flexible and visible using SDN. On the other hand, these advantages bring us a more vulnerable environment and dangerous threats, causing network breakdowns, systems paralysis, online banking frauds and robberies. These issues have a significantly destructive impact on organizations, companies or even economies. Accuracy, high performance and real-time systems are essential to achieve this goal successfully. Extending intelligent machine learning algorithms in a network intrusion detection system (NIDS) through a software-defined network (SDN) has attracted considerable attention in the last decade. Big data availability, the diversity of data analysis techniques, and the massive improvement in the machine learning algorithms enable the building of an effective, reliable and dependable system for detecting different types of attacks that frequently target networks. This study demonstrates the use of machine learning algorithms for traffic monitoring to detect malicious behavior in the network as part of NIDS in the SDN controller. Different classical and advanced tree-based machine learning techniques, Decision Tree, Random Forest and XGBoost are chosen to demonstrate attack detection. The NSL-KDD dataset is used for training and testing the proposed methods; it is considered a benchmarking dataset for several state-of-the-art approaches in NIDS. Several advanced preprocessing techniques are performed on the dataset in order to extract the best form of the data, which produces outstanding results compared to other systems. Using just five out of 41 features of NSL-KDD, a multi-class classification task is conducted by detecting whether there is an attack and classifying the type of attack (DDoS, PROBE, R2L, and U2R), accomplishing an accuracy of 95.95%.
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Wang, Zhao, Yifan Hu, Shiyang Yan, Zhihao Wang, Ruijie Hou, and Chao Wu. "Efficient Ring-Topology Decentralized Federated Learning with Deep Generative Models for Medical Data in eHealthcare Systems." Electronics 11, no. 10 (2022): 1548. http://dx.doi.org/10.3390/electronics11101548.
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By leveraging deep learning technologies, data-driven-based approaches have reached great success with the rapid increase of data generated for medical applications. However, security and privacy concerns are obstacles for data providers in many sensitive data-driven scenarios, such as rehabilitation and 24 h on-the-go healthcare services. Although many federated learning (FL) approaches have been proposed with DNNs for medical applications, these works still suffer from low usability of data due to data incompleteness, low quality, insufficient quantity, sensitivity, etc. Therefore, we propose a ring-topology-based decentralized federated learning (RDFL) scheme for deep generative models (DGM), where DGM is a promising solution for solving the aforementioned data usability issues. Our RDFL schemes provide communication efficiency and maintain training performance to boost DGMs in target tasks compared with existing FL works. A novel ring FL topology and a map-reduce-based synchronizing method are designed in the proposed RDFL to improve the decentralized FL performance and bandwidth utilization. In addition, an inter-planetary file system (IPFS) is introduced to further improve communication efficiency and FL security. Extensive experiments have been taken to demonstrate the superiority of RDFL with either independent and identically distributed (IID) datasets or non-independent and identically distributed (Non-IID) datasets.
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Karras, Aristeidis, Anastasios Giannaros, Leonidas Theodorakopoulos, et al. "FLIBD: A Federated Learning-Based IoT Big Data Management Approach for Privacy-Preserving over Apache Spark with FATE." Electronics 12, no. 22 (2023): 4633. http://dx.doi.org/10.3390/electronics12224633.
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In this study, we introduce FLIBD, a novel strategy for managing Internet of Things (IoT) Big Data, intricately designed to ensure privacy preservation across extensive system networks. By utilising Federated Learning (FL), Apache Spark, and Federated AI Technology Enabler (FATE), we skilfully investigated the complicated area of IoT data management while simultaneously reinforcing privacy across broad network configurations. Our FLIBD architecture was thoughtfully designed to safeguard data and model privacy through a synergistic integration of distributed model training and secure model consolidation. Notably, we delved into an in-depth examination of adversarial activities within federated learning contexts. The Federated Adversarial Attack for Multi-Task Learning (FAAMT) was thoroughly assessed, unmasking its proficiency in showcasing and exploiting vulnerabilities across various federated learning approaches. Moreover, we offer an incisive evaluation of numerous federated learning defence mechanisms, including Romoa and RFA, in the scope of the FAAMT. Utilising well-defined evaluation metrics and analytical processes, our study demonstrated a resilient framework suitable for managing IoT Big Data across widespread deployments, while concurrently presenting a solid contribution to the progression and discussion surrounding defensive methodologies within the federated learning and IoT areas.
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Dequidt, Jérémie, Hadrien Courtecuisse, Olivier Comas, et al. "Computer-based training system for cataract surgery." SIMULATION 89, no. 12 (2013): 1421–35. http://dx.doi.org/10.1177/0037549713495753.
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Zhang, Man, and Seung-Soon Shin. "Computer Vision-based Basketball Player Training System." Journal of Digital Contents Society 25, no. 3 (2024): 595–605. http://dx.doi.org/10.9728/dcs.2024.25.3.595.
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Zahorian, Stephen A., and Neiyer S. Correal. "Vowel training experiments with a computer‐based vowel training system." Journal of the Acoustical Society of America 95, no. 5 (1994): 3014. http://dx.doi.org/10.1121/1.408799.
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Machovikov, Alexei, Kirill Stolyarov, Maxim Chernov, Ian Sinclair, and Iliana Machovikova. "Computer-Based Training System for Russian Word Pronunciation." Computer Assisted Language Learning 15, no. 2 (2002): 201–14. http://dx.doi.org/10.1076/call.15.2.201.8192.
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Zang, Hua Dong. "Intelligent Sensor Networks Based Computer Lab Management System." Advanced Materials Research 838-841 (November 2013): 3256–59. http://dx.doi.org/10.4028/www.scientific.net/amr.838-841.3256.
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Current emphasis on practical teaching, students creative thinking higher vocational schools teaching philosophy, the traditional manual management mode of the computer training room shows weak features, mainly for equipment maintenance cycle length and the contradiction between the teaching needs. From teaching management, equipment maintenance, environmental management, safety management, explore computer-based training room sensor network management model.
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Zaloom, Victor, and Prakash Ramachandran. "A computer based training system for process safety management." Computers & Industrial Engineering 31, no. 1-2 (1996): 511–14. http://dx.doi.org/10.1016/0360-8352(96)00187-8.
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Abbas, Qaiser, Sadaf Hina, Hamza Sajjad, Khurram Shabih Zaidi, and Rehan Akbar. "Optimization of predictive performance of intrusion detection system using hybrid ensemble model for secure systems." PeerJ Computer Science 9 (September 4, 2023): e1552. http://dx.doi.org/10.7717/peerj-cs.1552.
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Network intrusion is one of the main threats to organizational networks and systems. Its timely detection is a profound challenge for the security of networks and systems. The situation is even more challenging for small and medium enterprises (SMEs) of developing countries where limited resources and investment in deploying foreign security controls and development of indigenous security solutions are big hurdles. A robust, yet cost-effective network intrusion detection system is required to secure traditional and Internet of Things (IoT) networks to confront such escalating security challenges in SMEs. In the present research, a novel hybrid ensemble model using random forest-recursive feature elimination (RF-RFE) method is proposed to increase the predictive performance of intrusion detection system (IDS). Compared to the deep learning paradigm, the proposed machine learning ensemble method could yield the state-of-the-art results with lower computational cost and less training time. The evaluation of the proposed ensemble machine leaning model shows 99%, 98.53% and 99.9% overall accuracy for NSL-KDD, UNSW-NB15 and CSE-CIC-IDS2018 datasets, respectively. The results show that the proposed ensemble method successfully optimizes the performance of intrusion detection systems. The outcome of the research is significant and contributes to the performance efficiency of intrusion detection systems and developing secure systems and applications.
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Wang, Zi Qing, Bin Shen, Zheng Guo Liu, and Jun Qing Liu. "Remote Repair System Based on VIRTOOLS." Advanced Materials Research 791-793 (September 2013): 1028–31. http://dx.doi.org/10.4028/www.scientific.net/amr.791-793.1028.
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With the increasingly complex new equipment, its maintenance repair training to become a big problem in the process of using the equipment. The traditional training mode by the equipment repair most limit, long development cycle, the characteristics of large investment, based on analysis of virtual repair training system development and function of demand, establish the remote repair system based on VIRTOOLS . The system can create realistic simulation results on the computer, the computer simulation of realistic behavior. The combination of network technology and virtual reality technology organically will provide a technical platform for remote repair service. This paper studies and discusses the architecture of remote repair system based on VIRTOOLS, the key technology and implementation method. And the system structure of remote fault diagnosis system is analyzed.
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Hu, Wen-Chao, Wang-Zhou Dai, Yuan Jiang, and Zhi-Hua Zhou. "Efficient Rectification of Neuro-Symbolic Reasoning Inconsistencies by Abductive Reflection." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 16 (2025): 17333–41. https://doi.org/10.1609/aaai.v39i16.33905.
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Neuro-Symbolic (NeSy) AI could be regarded as an analogy to human dual-process cognition, modeling the intuitive System 1 with neural networks and the algorithmic System 2 with symbolic reasoning. However, for complex learning targets, NeSy systems often generate outputs inconsistent with domain knowledge and it is challenging to rectify them. Inspired by the human Cognitive Reflection, which promptly detects errors in our intuitive response and revises them by invoking the System 2 reasoning, we propose to improve NeSy systems by introducing Abductive Reflection (ABL-Refl) based on the Abductive Learning (ABL) framework. ABL-Refl leverages domain knowledge to abduce a reflection vector during training, which can then flag potential errors in the neural network outputs and invoke abduction to rectify them and generate consistent outputs during inference. ABL-Refl is highly efficient in contrast to previous ABL implementations. Experiments show that ABL-Refl outperforms state-of-the-art NeSy methods, achieving excellent accuracy with fewer training resources and enhanced efficiency.
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COSÍO, F. ARÁMBULA, M. A. PADILLA CASTAÑEDA, and P. R. SEVILLA MARTÍNEZ. "COMPUTER ASSISTED PROSTATE SURGERY TRAINING." International Journal of Humanoid Robotics 03, no. 04 (2006): 485–98. http://dx.doi.org/10.1142/s0219843606000916.
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We report the current development of a new computer assisted system for local and remote training of transurethral resection of the prostate (TURP). The system is based on a 3D computer model of the prostate gland, which simulates deformations and resections of prostatic tissue. Simulated resections of the prostate can be repeatedly performed by the residents of urology to enhance their training. Automatic prostate recognition software was developed for the construction of a large library of prostate models. We report the software development of the system and show promising preliminary results of a new prostate recognition algorithm.
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Li, Xin, and Zenon J. Pudlowski. "An Interactive Computer-Based Training System for Electrical Engineering Education." International Journal of Electrical Engineering & Education 32, no. 1 (1995): 5–20. http://dx.doi.org/10.1177/002072099503200102.
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An interactive computer-based training system for electrical engineering education A computer learning network including an interactive computer-based training system (ICBTS) for electrical engineering has been developed. This article discusses the integration of instruction design, courseware delivery and students' performance analysis into one flexible system through computer-based learning. It considers the design and development of ICBTS, which is suitable for engineering students at university level.
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Resnick, D., C. Mitchell, and T. Govindaraj. "An embedded computer-based training system for rhino robot operators." IEEE Control Systems Magazine 7, no. 3 (1987): 3–8. http://dx.doi.org/10.1109/mcs.1987.1105304.
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Rambani, Rohit, James Ward, and Warren Viant. "Desktop-Based Computer-Assisted Orthopedic Training System for Spinal Surgery." Journal of Surgical Education 71, no. 6 (2014): 805–9. http://dx.doi.org/10.1016/j.jsurg.2014.04.012.
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Sue Boehmer, Linda. "Micro-computer-based expert system technology applied to industrial training." ISA Transactions 28, no. 1 (1989): 53–57. http://dx.doi.org/10.1016/0019-0578(89)90057-8.
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Fu, Wai-Tat, Daniel Bothell, Scott Douglass, Craig Haimson, Myeong-Ho Sohn, and John Anderson. "Toward a real-time model-based training system." Interacting with Computers 18, no. 6 (2006): 1215–41. http://dx.doi.org/10.1016/j.intcom.2006.07.011.
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Li, Xinyang, and Jingguo Zhang. "A Semantic Feature Enhancement-Based Aerial Image Target Detection Method Using Dense RFB-FE." International Journal on Semantic Web and Information Systems 19, no. 1 (2023): 1–18. http://dx.doi.org/10.4018/ijswis.331083.
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Aerial image target detection is a challenging task due to the complex backgrounds, dense target distribution, and large-scale differences often present in aerial images. Existing methods often struggle to effectively extract detailed features and address the issue of imbalanced positive and negative samples. To tackle these challenges, an aerial image target detection method (dense RFB-FE-CGAM) based on dense RFB-FE and channel-global attention mechanism (CGAM) was proposed. First, the authors design a shallow feature enhancement module using dense RFB feature multiplexing and expand convolution within an SSD network, improving detailed feature extraction. Second, they introduce CGAM, a global attention module, to enhance semantic feature extraction in backbone networks. Finally, they incorporate a focal loss function for joint training, addressing sample imbalance. In experiments, the method achieved an mAP of 0.755 on the DOTA dataset and recall/AP values of 0.889/0.906 on HRSC2016, confirming the effectiveness of dense RFB-FE-CGAM for aerial image target detection.
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Sharit, J., S. Chen, and D. ‐Y M. Lin. "Expert System Based Training for Emergency Management." Journal of Computing in Civil Engineering 7, no. 1 (1993): 6–22. http://dx.doi.org/10.1061/(asce)0887-3801(1993)7:1(6).
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Yu, Shi Lin, Jing Wang, and Chang He Ren. "Design of the Teaching & Training System Based on the Training Ship." Applied Mechanics and Materials 530-531 (February 2014): 1137–41. http://dx.doi.org/10.4028/www.scientific.net/amm.530-531.1137.
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According to the teaching and training needs, we establish the network of education and training systems, which is programmed by taking advantage of training ship data, virtual simulation technology, network and computer technology, and provide a more functional teaching and training platform for the real-ship education.
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Pereira, Carlos. "Double Evolution – A Computer-Based Quality Management System for Enterprise-Specific Training." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 44, no. 11 (2000): 406–9. http://dx.doi.org/10.1177/154193120004401120.
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This paper deals with the development and implementation of a computer-based quality management system for enterprise-specific training. The system can be used by both training organisations and enterprises. It gives training processes a structure and it provides instruments that can be used for the assurance and evaluation of the quality of training.
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Li, He, Gang Zou, Lin Li, and Dehui Yu. "Helicopter Training Simulator Measurement and Control System Based on Computer Simulation Technology." Journal of Physics: Conference Series 2143, no. 1 (2021): 012011. http://dx.doi.org/10.1088/1742-6596/2143/1/012011.
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Abstract With the development of computer software technology and simulation technology, simulation training has been widely used. Helicopter training simulation has become an important part of helicopter training, and its status is becoming more and more important. On the one hand, the air mechanic is responsible for the maintenance and organization of the helicopter during the flight, and on the other hand is responsible for the starting and stopping of the helicopter engine, the operation of related equipment, and the handling of emergencies during the flight. The simulation training has the characteristics of high training efficiency, convenient maintenance and low training cost. It will become an important means for helicopter air mechanics to troubleshoot and deal with special situations. This paper aims to study the helicopter training simulator measurement and control system based on computer software technology. Based on the analysis of the advantages of the simulator instead of the actual installation for training, the helicopter training simulator function and the simulator subsystem, the actual installation simulation instrument and signal are designed. The indicator light, the graphic instrument and the control signal are arranged in the circuit, and then the simulation experiment is carried out on the design. The experimental results show that the design can more accurately simulate the indication of the antenna elevation angle table, which meets the requirements of this article.
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Kiselyova, N. N., A. V. Stolyarenko, V. V. Ryazanov, O. V. Sen’ko, A. A. Dokukin, and V. V. Podbel’skii. "A system for computer-assisted design of inorganic compounds based on computer training." Pattern Recognition and Image Analysis 21, no. 1 (2011): 88–94. http://dx.doi.org/10.1134/s1054661811010081.
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Zhou, Jian. "Virtual reality sports auxiliary training system based on embedded system and computer technology." Microprocessors and Microsystems 82 (April 2021): 103944. http://dx.doi.org/10.1016/j.micpro.2021.103944.
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O'Neal, Fred, and Peter Fairweather. "THE EVALUATION AND SELECTION OF COMPUTER-BASED TRAINING AUTHORING SYSTEMS." CALICO Journal 2, no. 2 (2013): 27–31. http://dx.doi.org/10.1558/cj.v2i2.27-31.
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Authoring systems for computer-based training are becoming more and more common as hardware costs decrease. Decision makers who must select an authoring system must be sure that the system selected will meet actual training needs both present and future as determined by an in-depth analysis. Assuming the analysis has been done, this paper discusses the steps for selecting a suitable authoring system in some detail.
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Yau, Hong-Tzong, and Chien-Yu Hsu. "Development of a Dental Training System Based on Point-based Models." Computer-Aided Design and Applications 3, no. 6 (2006): 779–87. http://dx.doi.org/10.1080/16864360.2006.10738431.
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Li, Chunguang, and Jianbiao Cui. "Intelligent Sports Training System Based on Artificial Intelligence and Big Data." Mobile Information Systems 2021 (May 22, 2021): 1–11. http://dx.doi.org/10.1155/2021/9929650.
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All activities in training fields are for the improvement of athletes’ competitive abilities. A sports training system is an organizational system to achieve common goals. Competitive ability is one of the main manifestations of the evolution of the training system. With the rapid development of computer technology, people have begun to combine virtual reality and other technologies to achieve scientific sports-assisted training to eliminate traditional sports training that relied purely on experience. Pose estimation obtains the position, angle, and additional information about the human body in the image in a two-dimensional plane or three-dimensional space by establishing the mapping relationship between the human body features and the human body posture. This article demonstrates a golf-assisted training system to realize the transformation from an experience-based sports training method to a human motion analysis method, using artificial intelligence and big data. The swing posture parameters of the trainer and the coach are obtained using the posture estimation of a human body. Based on this information, an auxiliary training system is built. The two parameters of the joint angle trajectory and the posture similarity are used as auxiliary indicators to compare the trainers. The joint angle trajectory is analyzed, and the coach is guided based on the similarity of the posture.
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Guerrero-Osuna, Héctor A., Jesús Antonio Nava-Pintor, Carlos Alberto Olvera-Olvera, Teodoro Ibarra-Pérez, Rocío Carrasco-Navarro, and Luis F. Luque-Vega. "Educational Mechatronics Training System Based on Computer Vision for Mobile Robots." Sustainability 15, no. 2 (2023): 1386. http://dx.doi.org/10.3390/su15021386.
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Boosting by the world’s context, several efforts have been maiden toward the digital transformation of Education. Technology-based active learning has become pivotal in pursuing a more flexible education system. This work presents the development of an Educational Mechatronics (EM) training system based on computer vision that performs as a positioning system for mobile robots in the 2D plane. The results show that the obtained precision, exactitude, and resolution of the EM training system are suitable for robotics applications comprising position, velocity, and acceleration variables. Moreover, an instructional design aligned with the EM conceptual framework, using the EM training system and a LEGO mobile robot, is presented to construct the mechatronic concept: line segment.
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Deng, Biao, and Lian Wei Liu. "Virtual Training System of Special Equipment Operation Based on Virtools." Applied Mechanics and Materials 624 (August 2014): 540–44. http://dx.doi.org/10.4028/www.scientific.net/amm.624.540.
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Considering the problems of long training cycle, low frequency, big loss and high costs existing in traditional training, this article builds a three-dimensional virtual training environment and a interaction training method using virtual reality technology. This application enables trainees to learn a special equipment training knowledge on personal computer. This application can improve the training quality and efficiency, shorten the training cycle, save training funds, reduce equipment loss, has the advantages of safety, and are not affected by the conditions of use and environmental restrictions.
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Wang, Yixiao. "A Distributed System Fault Diagnosis System based on Machine Learning." Scalable Computing: Practice and Experience 25, no. 2 (2024): 1117–23. http://dx.doi.org/10.12694/scpe.v25i2.2622.
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Now days distributed system becomes the mainstream system of information storage and processing. Compared with traditional systems, distributed systems are larger and more complex.However, the average probability of failure is higher and the difficulty, complexity of operation and maintenance are greatly increased. Therefore, it is necessary to use efficient methods to diagnose the system. Our aim is to use the trained model to diagnose the fault data of the distributed system, so we can obtain as high diagnostic accuracy as possible, and create a web side for users to use. The technique we proposed uses the integrated learning approach of Stacking to model the superposition of the raw data. To realize this, we trained with a dataset of 10,000 pieces of data and assessed accuracy every once in a while. Our best training results are about 80.69% accurate and can be used on the web side. By training data sets and analyzing distributed system faults with Stacking technology, a model with a test accuracy of 80.69% was obtained. Through this model and the web platform we built, the fault of distributed system can be diagnosed, and the diagnosis results are better than other models.
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Weiss, Holger, Tobias Ortmaier, Heiko Maass, Gerd Hirzinger, and Uwe Kuehnapfel. "A Virtual-Reality-Based Haptic Surgical Training System." Computer Aided Surgery 8, no. 5 (2003): 269–72. http://dx.doi.org/10.3109/10929080309146063.
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Yao, Jing, and Yanze Li. "Youth Sports Special Skills’ Training and Evaluation System Based on Machine Learning." Mobile Information Systems 2022 (August 8, 2022): 1–10. http://dx.doi.org/10.1155/2022/6082280.
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Nowadays, most sports training adopts such a mode, that is, the coach guides and observes the movements of the trainer on the side, or uses the camera to collect the data information in the training video. After the training, the trainer needs to experience and comprehend it according to the coach’s guidance and suggestions, which leads to a poor training effect to a certain extent, and the training movements are not so standardized. The most important thing is that the physical condition of the trainer will change at any time during the exercise. However, the traditional training mode cannot perceive and predict it at all, and it may even lead to the training volume being too large for the athletes to bear, which also causes irreversible effects on the body. Based on this, this paper aims to use the relevant theories and technologies of machine learning to build a system for the training and evaluation of sports-specific skills. This paper automatically determines and guides the movements of the trainer, which greatly improves the training efficiency. The movements are also more standardized, and the workload of the coaches is also reduced. In addition, the system includes explained functions. It uses holographic projection to play various videos of training and guidance, which brings convenience to trainers to observe and understand specific sports behaviors. Finally, the data results of the experimental subjects were analyzed to verify the effectiveness and feasibility of this training evaluation system, in which their special scores increased by 1.51% compared with the previous ones.