Novel Machine Learning for Big Data Analytics in Intelligent Support Information Management Systems

Two-dimensional 1 arrays of bi-component structures made of cobalt and permalloy elliptical dots with thickness of 25 nm, length 1 mm and width of 225 nm, have been prepared by a self-aligned shadow deposition technique. Brillouin light scattering has been exploited to study the frequency dependence of thermally excited magnetic eigenmodes on the intensity of the external magnetic field, applied along the easy axis of the elements. Scientific information technology has been developed rapidly. Here, the purposes are to make people's lives more convenient and ensure information management and classification. The machine learning algorithm is improved to obtain the optimized Light Gradient Boosting Machine (LightGBM) algorithm. Then, an Android-based intelligent support information management system is designed based on LightGBM for the big data analysis and classification management of information in the intelligent support information management system. The system is designed with modules of employee registration and login, company announcement notice, attendance and attendance management, self-service, and daily tools with the company as the subject. Furthermore, the performance of the constructed information management system is analyzed through simulations. Results demonstrate that the training time of the optimized LightGBM algorithm can stabilize at about 100s, and the test time can stabilize at 0.68s. Besides, its accuracy rate can reach 89.24%, which is at least 3.6% higher than other machine learning algorithms. Moreover, the acceleration efficiency analysis of each algorithm suggests that the optimized LightGBM algorithm is suitable for processing large amounts of data; its acceleration effect is more apparent, and its acceleration ratio is higher than other algorithms. Hence, the constructed intelligent support information management system can reach a high accuracy while ensuring the error, with apparent acceleration effect. Therefore, this model can provide an experimental reference for information classification and management in various fields.

Unlocking digital archives: cross-disciplinary perspectives on AI and born-digital data

Co-authored by a Computer Scientist and a Digital Humanist, this article examines the challenges faced by cultural heritage institutions in the digital age, which have led to the closure of the vast majority of born-digital archival collections. It focuses particularly on cultural organizations such as libraries, museums and archives, used by historians, literary scholars and other Humanities scholars. Most born-digital records held by cultural organizations are inaccessible due to privacy, copyright, commercial and technical issues. Even when born-digital data are publicly available (as in the case of web archives), users often need to physically travel to repositories such as the British Library or the Bibliothèque Nationale de France to consult web pages. Provided with enough sample data from which to learn and train their models, AI, and more specifically machine learning algorithms, offer the opportunity to improve and ease the access to digital archives by learning to perform complex human tasks. These vary from providing intelligent support for searching the archives to automate tedious and time-consuming tasks. In this article, we focus on sensitivity review as a practical solution to unlock digital archives that would allow archival institutions to make non-sensitive information available. This promise to make archives more accessible does not come free of warnings for potential pitfalls and risks: inherent errors, "black box" approaches that make the algorithm inscrutable, and risks related to bias, fake, or partial information. Our central argument is that AI can deliver its promise to make digital archival collections more accessible, but it also creates new challenges - particularly in terms of ethics. In the conclusion, we insist on the importance of fairness, accountability and transparency in the process of making digital archives more accessible.

New Trends in Melanoma Detection Using Neural Networks: A Systematic Review

Due to its increasing incidence, skin cancer, and especially melanoma, is a serious health disease today. The high mortality rate associated with melanoma makes it necessary to detect the early stages to be treated urgently and properly. This is the reason why many researchers in this domain wanted to obtain accurate computer-aided diagnosis systems to assist in the early detection and diagnosis of such diseases. The paper presents a systematic review of recent advances in an area of increased interest for cancer prediction, with a focus on a comparative perspective of melanoma detection using artificial intelligence, especially neural network-based systems. Such structures can be considered intelligent support systems for dermatologists. Theoretical and applied contributions were investigated in the new development trends of multiple neural network architecture, based on decision fusion. The most representative articles covering the area of melanoma detection based on neural networks, published in journals and impact conferences, were investigated between 2015 and 2021, focusing on the interval 2018–2021 as new trends. Additionally presented are the main databases and trends in their use in teaching neural networks to detect melanomas. Finally, a research agenda was highlighted to advance the field towards the new trends.

CheerBrush: A Novel Interactive Augmented Reality Coaching System for Toothbrushing Skills in Children with Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is a common neurodevelopmental disorder that impacts one in every 54 children in the United States. Some children with ASD have learning and fine motor skill challenges that contribute to difficulties completing daily living tasks such as toothbrushing. Lack of toothbrushing skills may cause increased need for dental care and negative social feedback from peers. Technology based intelligent support systems offer the advantages of being accessible, engaging, and cost-effective. In this work, we present a novel interactive augmented reality coaching system, CheerBrush, to improve the toothbrushing skills of children with ASD. CheerBrush allows children to manipulate virtual objects like a toothbrush and toothpaste with their actual hand motions to practice the steps of toothbrushing. The virtual tasks of CheerBrush demonstrate these steps using audio and visual cues, while also showing the brushing process through a virtual avatar. CheerBrush also assesses toothbrushing skills with a custom designed mechatronic toothbrush to evaluate the system's coaching effectiveness. A feasibility study with 12 children (six children with ASD and six typically developing children) was conducted to evaluate the acceptability and effectiveness of CheerBrush. The data showed improvements in the toothbrushing motions and reduced stress for the children in the post-test. CheerBrush detects real-time movement of children and interacts with them by augmented reality, feedback and multimodal hints. We believe that CheerBrush has the potential to provide a low-cost, engaging and, beneficial intelligent support system to improve the toothbrushing skills of children with ASD.

Применение онтологий для решения задач геофизики

The paper covers an intelligent support system that allows to describe and construct solutions to various scientific problems. In this study, in particular, we consider geophysical problems. This system is being developed at the Institute of Computational Mathematics and Mathematical Geophysics of the Russian Academy of Sciences (ICMMG SB RAS) and Institute of Informatics System of the Russian Academy of Sciences (IIS SB RAS). The system contains a knowledge base, the core of which is a set of several interconnected ontologies such as the ontology of supercomputer architectures, the ontology of algorithms and methods. Ontology can be viewed as a set of concepts and how those concepts are linked. As the result, the authors present an ontological description of two geophysical problems via the means of the intelligent support system: 1) the seismic wavefield simulation and 2) the reconstruction of a seismic image through pre-stack time or depth migration. For a better visual understanding of the system described and the results obtained, the paper also contains several schematic diagrams and images. В статье рассматривается система интеллектуальной поддержки, позволяющая описывать и выстраивать решения различных научных задач. В данной работе рассматриваются геофизические задачи. Система разрабатывается в Институте вычислительной математики и математической геофизики Российской академии наук (ИВМГ СО РАН) и Институте систем информатики Российской академии наук (ИИС СО РАН). Система содержит базу знаний, ядром которой является набор из нескольких взаимосвязанных онтологий, таких как онтология суперкомпьютерных архитектур, онтология алгоритмов и методов. Онтологию можно рассматривать как набор концепций и связей между ними. В результате авторы представляют онтологическое описание двух геофизических задач с помощью средств системы интеллектуальной поддержки: 1) моделирование сейсмического волнового поля и 2) реконструкция сейсмического изображения посредством временной или глубинной миграции до суммирования. Для лучшего визуального понимания описанной системы и полученных результатов в работе также есть несколько схематических диаграмм и изображений.

Intelligent support and command system based on WAPI terminal equipment

In order to solve the problem that the process of WAPI terminal connection is troublesome, this paper proposes an intelligent support and command system of WAPI terminal equipment based on centralized control AC + AP architecture. The system stores WAPI certificate on AC (centralized controller), WAPI terminal equipment is associated with AP (wireless access point), and AP equipment notifies AC of the associated events of the terminal, AC equipment and terminal equipment enter authentication and complete certificate authentication. Complete access authentication through AC and terminal equipment, and store the unicast and multicast keys generated by authentication negotiation on AC. This method is more convenient to maintain the certificate. At the same time, on the premise of ensuring the security of the certificate, it also improves the encryption and decryption efficiency and improves the user’s business experience.

Research on influencing factors of information diffusion in online social networks under different themes

Purpose This paper aims to study the factors influencing online social network (OSN) information diffusion under different themes helps to understand information diffusion in general. Design/methodology/approach This study collects data from the Web of Science, use the strategic consulting intelligent support system for word frequency analysis and use keyword clustering to classify themes, then research information themes as influencing factors of OSN information diffusion. Findings Five themes of “natural disaster”, “political event”, “product marketing”, “sport and entertainment” and “health-disease” have been identified. It is found that the research objects, research methods and research theories used by scholars under different themes have different focuses, and the factors affecting information diffusion are different. Research limitations/implications The limitation of this paper is that it only focuses on five typical themes, and there may be more themes. Practical implications The research helps other scholars to conduct in-depth research on the diffusion of OSN information under different topics and focus on the content of the research on OSN information diffusion under different topics. Social implications The research helps other scholars to conduct in-depth research on the diffusion of social network information under different topics, so as to better understand and predict the law of information diffusion. Originality/value The research summarizes the research on information diffusion in OSNs from the theme level and analyses the key points and theories and further enriches the research system on information diffusion in OSNs.