Reviewerly/exHarmony huggingface dataset:
Attention-based neural networks for clinical prediction modelling on electronic health records

Abstract Background Deep learning models have had a lot of success in various fields. However, on structured data they have struggled. Here we apply four state-of-the-art supervised deep learning models using the attention mechanism and compare against logistic regression and XGBoost using discrimination, calibration and clinical utility. Methods We develop the models using a general practitioners database. We implement a recurrent neural network, a transformer with and without reverse distillation and a graph neural network. We measure discrimination using the area under the receiver operating characteristic curve (AUC) and the area under the precision recall curve (AUPRC). We assess smooth calibration using restricted cubic splines and clinical utility with decision curve analysis. Results Our results show that deep learning approaches can improve discrimination up to 2.5% points AUC and 7.4% points AUPRC. However, on average the baselines are competitive. Most models are similarly calibrated as the baselines except for the graph neural network. The transformer using reverse distillation shows the best performance in clinical utility on two out of three prediction problems over most of the prediction thresholds. Conclusion In this study, we evaluated various approaches in supervised learning using neural networks and attention. Here we do a rigorous comparison, not only looking at discrimination but also calibration and clinical utility. There is value in using deep learning models on electronic health record data since it can improve discrimination and clinical utility while providing good calibration. However, good baseline methods are still competitive.
Strategy Research of Building Smart Library

With the wide application of AR, big data and other technologies, the construction of smart library has gradually become the focus of people's attention. Especially under the promotion of the construction and development of the smart city, the library has become the main place to carry the local culture. Compared with traditional libraries, smart library introduces information technology as support in the construction of operation mode and the development of service and management system, and takes the humanized management concept runs through the whole process of library construction, realizing the internal interaction between "people" and "library". This research takes the construction of intelligent library as the research theme, expounds the significance and current situation of building intelligent library, and puts forward the cultivation strategy of building intelligent library, in order to provide reference for the construction of intelligent library.
The practical path of smart library construction in the era of science and technology

The intelligent library is not only a place to store and transmit information, but also a comprehensive space for learning, research, communication and entertainment. It uses modern scientific and technological means to provide users with more convenient, personalized and interactive services, making the dissemination and acquisition of knowledge more efficient and accurate. Based on this, this paper studies the era of science and technology wisdom library construction practice path, analyzes the significance of science and technology era wisdom library construction, the practice of science and technology era wisdom library construction, and gives the era of wisdom library construction practice path, through the study of this paper, for the future development of the library to provide some useful enlightenment and reference.
Metaverse: The future field of online education

Promoting the digitization of online education is an important task for the development of modern education. The meta-universe is a digital space parallel to the real world, and it is a collection of many high technologies, which can provide the theoretical basis of embodied cognition, distributed cognition and immersive cognition for online education. The meta-universe enabling online education can expand the learning boundary of online education, deepen the learning experience of online education, and construct multi-dimensional teaching evaluation and other educational practice fields. Promoting the research and development of meta-universe education technology, building the rational framework of meta-universe education, forming the ethical concept of meta-universe education and other approaches provide practical paths for meta-universe enabling online education.
Multiple Sclerosis Characteristics Do Vary According to Age of Disease Onset (4621)

Saturday, April 17April 13, 2021Free AccessMultiple Sclerosis Characteristics Do Vary According to Age of Disease Onset (4621)Saloua Mrabet, Amira Souissi, Amina Nasri, Amina Gargouri, Imen Kacem, and Riadh GouiderAuthors Info & AffiliationsApril 13, 2021 issue96 (15_supplement)https://doi.org/10.1212/WNL.96.15_supplement.4621 Letters to the Editor
Personalized Federated Learning with Attention Mechanisms

With the rapid development of science and technology, machine learning and deep learning technology have more and more applications in our daily life. At the same time, people pay more and more attention to the protection of their own privacy. And in recent years, various countries have introduced a series of laws and regulations to protect people's data privacy. In this case, the traditional method of pooling the data of each user for model training is no longer applicable, and the data of each user can only be saved in the hands of the user himself, which has a profound impact on the development of artificial intelligence technology. To solve this dilemma, the industry has proposed the concept of federated learning. Due to the data imbalance problem between each user, the prediction ability of the global aggregation model obtained by federated learning on the local specific data of each user needs to be improved. Therefore, personalization is an issue that federated learning needs to pay attention to.In order to improve the personalization ability, this paper proposes a federated transfer learning algorithm with attention mechanism. After each user obtains the global aggregation model of federated learning, the attention module is added to the local model, and then the parameters of the low-level neurons are frozen during training, and only the parameters of the high-level neurons and the attention module are updated. Finally, each user obtains a unique model that is more suitable for local data. In this paper, we conduct experiments to analyze the performance of this algorithm and the federated transfer algorithm and federated learning algorithm in terms of accuracy. The experimental results show that on the convolutional neural network model, the federated transfer learning algorithm applying the attention mechanism has improved the accuracy compared with the federated transfer algorithm and the federated learning algorithm.
Multi-branch mutual learning net for vehicle re-identification

To address the problem that the global feature extraction ability of single-branch network is low and does not have the sensitivity of specific scenes due to the interference of factors such as occlusion caused by fixed camera shooting and scale scaling caused by vehicle driving from far and near in vehicle re-identification, ML Net (Mutual Learning Net) is proposed. Firstly, the multi-branch structure of the network consists of one master branch and three slave branches, the master branch is responsible for the feature learning task in general complex scenes, and the three slave branches are responsible for the feature learning task under image occlusion, scale scaling, and vehicle color change, so that the network can be sensitive to specific scenes. Finally, the models are trained in each branching stage jointly with Label Smoothing Cross Entropy Loss, Triplet Loss and KL (Kullback-Leibler Divergence) Loss. The experimental results show that the proposed ML Net network achieves advanced experimental results on two publicly available datasets, VeRi776 and VehicleID.
Application Analysis of Target Image Retrieval Technology in Computer Vision

Computer vision is a field of study that explores how computers can understand and perceive their surroundings and objects by processing visual information, such as images or videos. Among its applications, image retrieval is a crucial direction that allows users to quickly find similar images or related information by inputting a single image. This article takes image retrieval as the starting point, defining its basic principles and delving into the practical applications of target image retrieval technology in computer vision. Its aim is to classify and cluster images, enabling faster and more accurate searches for desired images.
SOCIALIZATION OF THERMAL COMFORT STANDARDS AT SMKN 4 SOUTH TANGERANG

Vocational High School (SMK) is a formal education unit that provides education that prepares students to work in specific fields. Students can continue their vocational education after completing their education at the junior high school level. SMK Negeri 4 South Tangerang is one of the 4th Vocational High Schools in the City of South Tangerang, specializing in Building Modeling and Information Design, Health Services, Animation, and Visual Communication Design. SMKN 4 South Tangerang is located on Jalan Sumatra-Tidore, Jombang Village, Ciputat District, South Tangerang City, Banten Province, with a land area of 4,562 m2. Currently, SMK Negeri 4 South Tangerang uses a natural air circulation system with openings in each class; then, each class uses a fan for artificial air circulation. There are four types of building comfort: thermal comfort, space comfort, and audio comfort. Space comfort is related to the comfort of movement space and relationships between spaces. Meanwhile, thermal comfort is an essential part of building comfort because room temperature influences the feeling of comfort. This is because every human being has sensors on their skin that work when there are hot or cold temperatures. Thermal comfort conditions that comply with standards will help the teaching and learning process be streamlined at SMK Negeri 4 South Tangerang. So that SMK Negeri 4 South Tangerang has thermal comfort that meets standards, Budi Luhur University organizes Community Service activities to socialize the achievement of thermal comfort at SMK Negeri 4 South Tangerang. The method of implementing activities uses the concept of Problem Solving. At the same time, the Problem-Solving concept uses input stages, problem-solving processes, and output. The aim of socializing the achievement of thermal comfort is so that the management of SMK Negeri 4 South Tangerang knows how to achieve thermal comfort standards so that students at the School are comfortable when carrying out the teaching process.
OPTIMIZATION OF PUBLIC SPEAKING SKILLS FOR IMPROVEMENT OF HUMAN RESOURCES MANAGEMENT OF RPTRA &amp; PKK KELURAHAN PETUKANGAN UTARA

A community engagement initiative conducted in collaboration between Budi Luhur University's Faculty of Communication and Creative Design and North Petukangan Subdistrict, Jakarta, has yielded significant results. The program focused on enhancing public speaking skills and has left a notable impact. Participants in the Public Speaking Workshop reported substantial improvements in their ability to communicate effectively in public. They gained practical speaking techniques, overcame stage fright, and developed a better understanding of their audience, resulting in a boost in self-confidence. Participants expressed increased confidence and motivation to address audiences, a valuable asset in their roles at RPTRA and PKK North Petukangan Subdistrict.&#x0D; Furthermore, the positive community response indicated a growing interest in similar programs, emphasizing the increasing awareness of the significance of public speaking skills for human resource development and community progress. The most significant impact was observed in human resource management at RPTRA and PKK, where enhanced speaking skills enable leaders and facilitators to communicate, motivate, and lead more effectively. In conclusion, this community engagement program has brought about positive changes in human resource development and community management in North Petukangan Subdistrict. It illustrates how higher education can benefit local communities, enabling them to realize their full potential.
Artificial Intelligence and High-Quality Development of Henan Province's Economy

Based on the data of 18 prefecture-level cities in Henan Province from 2013 to 2021, this paper constructs a fixed effect model to empirically analyze the economic impact and mechanism of AI development. It is found that artificial intelligence has a significant role in promoting the high-quality economic development of Henan Province, which is an inverted U-shaped effect. Through the study of artificial intelligence and high-quality economic development in Henan Province, it is of great significance to the rational use of artificial intelligence.
A Generic Error Simulation in Digital Photoelasticity By Jones Calculus

Photoelasticity is a whole field experimental technique to obtain stress fields in both 2-D and 3-D elasticity problems. With advancements in Digital Image Processing (DIP), a separate branch of photoelasticity namely digital photoelasticity came into existence wherein the intensity of the images is used for photoelastic parameter estimation. The accuracy of parameter evaluation by digital photoelastic techniques depends on the choice of the optical arrangements for parameter estimation, the inherent error in optical elements and any misalignments introduced during experimentation. A generic approach to simulation of error in digital photoelasticity by Jones calculus is presented in this paper. The simulation accounts for inherent error in quarter-wave plates and also accommodates the error due to the optical misalignment of the various optical elements. The applicability of the new methodology is shown for the most popular six-step phase shifting technique. The methodology proposed is generic and is applicable to study the influence of error sources on parameter estimation for various techniques proposed in digital photoelasticity.
PcTVI: Parallel MDP Solver Using a Decomposition into Independent Chains

Abstract Markov Decision Processes (MDPs) are useful to solve real-world probabilistic planning problems. However, finding an optimal solution in an MDP can take an unreasonable amount of time when the number of states in the MDP is large. In this paper, we present a way to decompose an MDP into Strongly Connected Components (SCCs) and to find dependency chains for these SCCs. We then propose a variant of the Topological Value Iteration (TVI) algorithm, called parallel chained TVI (pcTVI), which is able to solve independent chains of SCCs in parallel leveraging modern multicore computer architectures. The performance of our algorithm was measured by comparing it to the baseline TVI algorithm on a new probabilistic planning domain introduced in this study. Our pcTVI algorithm led to a speedup factor of 20, compared to traditional TVI (on a computer having 32 cores).
On Parsimonious Modelling via Matrix-Variate t Mixtures

Abstract Mixture models for matrix-variate data have becoming more and more popular in the most recent years. One issue of these models is the potentially high number of parameters. To address this concern, parsimonious mixtures of matrixvariate normal distributions have been recently introduced in the literature. However, when data contains groups of observations with longer-than-normal tails or atypical observations, the use of the matrix-variate normal distribution for the mixture components may affect the fitting of the resulting model. Therefore, we consider a more robust approach based on the matrix-variate C distribution for modeling the mixture components. To introduce parsimony, we use the eigen-decomposition of the components scale matrices and we allow the degrees of freedom to be equal across groups. This produces a family of 196 parsimonious matrix-variate C mixture models. Parameter estimation is obtained by using an AECM algorithm. The use of our parsimonious models is illustrated via a real data application, where parsimonious matrix-variate normal mixtures are also fitted for comparison purposes.
The Death Process in Italy Before and During the Covid-19 Pandemic: A Functional Compositional Approach

Abstract In this talk, based on [1], we propose a spatio-temporal analysis of daily death counts in Italy, collected by ISTAT (Italian Statistical Institute), in Italian provinces and municipalities. While in [1] the focus was on the elderly class (70+ years old), we here focus on the middle class (50–69 years old), carrying out analogous analyses and comparative observations. We analyse historical provincial data starting from 2011 up to 2020, year in which the impacts of the Covid-19 pandemic on the overall death process are assessed and analysed. The cornerstone of our analysis pipeline is a novel functional compositional representation for the death counts during each calendar year: specifically, we work with mortality densities over the calendar year, embedding them in the Bayes space B 2 of probability density functions. This Hilbert space embedding allows for the formulation of functional linear models, which are used to split each yearly realization of the mortality density process in a predictable and an unpredictable component, based on the mortality in previous years. The unpredictable components of the mortality density are then spatially analysed in the framework of Object Oriented Spatial Statistics. Via spatial downscaling of the results obtained at the provincial level, we obtain smooth predictions at the fine scale of Italian municipalities; this also enable us to perform anomaly detection, identifying municipalities which behave unusually with respect to the surroundings.
PENINGKATAN KEMAMPUAN MENULIS TEKS CERITA SEJARAH DENGAN MODEL PEMBELAJARAN EXAMPLES NON EXAMPLES SISWA KELAS XII SMKN 1 PURWOJATI

This research is a classroom action research. The purpose of this study is to improve the ability to write historical narrative texts with an example non example learning model for class XII students of SMK Negeri 1 Purwojati, Banyumas Regency. The indicator of the success of this research data is if there is an increase in students' learning mastery based on the minimum completeness criteria (KKM) for Indonesian Language and Literature subjects at SMK Negeri Purwojati, Banyumas Regency, with a value of 70. The conclusion of this study is the use of the model example non example learning can improve the ability to write historical narrative texts for class XII students of SMK Negeri Purwojati, Banyumas Regency, Central Java Province.
Dissociable Systems for Recognizing Places and Navigating through them: Causal and Developmental Evidence. (35)

Wednesday, April 29April 14, 2020Free AccessDissociable Systems for Recognizing Places and Navigating through them: Causal and Developmental Evidence. (35)Stephanie Wahab, Frederik Kamps, Sama Radwan, and Daniel DilksAuthors Info & AffiliationsApril 14, 2020 issue94 (15_supplement)https://doi.org/10.1212/WNL.94.15_supplement.35 Letters to the Editor
Rancang Bangun Aplikasi Posyandu Berbasis Android Menggunakan UML (Studi Kasus: Posyandu Dahlia Perumahan Total Persada)

This research is focused on the design and development of an Android-based Posyandu application using the Unified Modeling Language (UML) approach. Specifically, it examines the case study of Posyandu Dahlia at Total Persada Housing. The purpose of this research is to provide assistance to developers in designing Android-based Posyandu applications by utilizing UML modeling. The findings of this study indicate that the application of UML significantly enhances the quality and efficiency of system design. UML enables development teams to create applications with a well-organized structure, proper functionality, and optimal interaction between components. Therefore, the use of UML can be considered a highly valuable approach in designing public health applications like Posyandu Dahlia. The aim is for this application to contribute to the tasks of the cadres and participants of Posyandu Dahlia.
Perancangan Sistem Informasi Akademik Pada Sma Tangerang 1 Berbasis Web Menggunakan Framework Laravel

The use of web-based information systems has been widely used in various fields, especially in education. In the field of education, this system is referred to as an academic information system, which is a platform designed to facilitate the implementation of administrative tasks in the academic field in educational institutions online. However, currently there are still many educational institutions that still use the old or manual method. SMA Tangerang 1 currently has not optimized the use of information systems effectively and still relies on manual or conventional methods such as using Microsoft Excel and Microsoft Word to input and manage data. In this research, the design of a web-based academic information system is carried out with the aim of increasing efficiency and effectiveness in managing grade management data, subjects, teacher data, student data at SMA Tangerang 1. Designed using the Laravel framework with Model View Control(MVC) architecture. This research adopts the Extreme Programming method in developing the application, resulting in a web-based information system that can be utilized by SMA Tangerang 1. The results of system testing show good performance, in accordance with user expectations.
Conducting sentiment analysis <b>Conducting sentiment analysis</b> , by Lei Lei and Dinlin Liu, Cambridge, Cambridge University Press, 2021, iv++104 pp., $20.00 (paperback), ISBN 978-1-108-82921-2

Click to increase image sizeClick to decrease image size Additional informationFundingThis work is funded by the Outstanding Graduate Education Innovation Funding Project of CCNU (Project No.: 2023CXZZ086) and Graduate Teaching and Research Reform Project of CCNU (Project No.: 2022JG26).
Cultivating Proactive Cybersecurity Culture among IT Professional to Combat Evolving Threats

In the current digital landscape, cybercriminals continually evolve their techniques to execute successful attacks on businesses, thus posing a great challenge to information technology (IT) professionals. While traditional cybersecurity approaches like layered defense and reactive security have helped IT professionals cope with traditional threats, they are ineffective in dealing with evolving cyberattacks. This paper focuses on the need for a proactive cybersecurity culture among IT professionals to enable them combat evolving threats. The paper emphasis that building a proactive security approach and culture can help among IT professionals anticipate, identify, and mitigate latent threats prior to them exploiting existing vulnerabilities. This paper also points out that as IT professionals use reactive security when dealing with traditional attacks, they can use it collaboratively with proactive security to effectively protect their networks, data, and systems and avoid heavy costs of dealing with cyberattack’s aftermaths and business recovery.