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检索条件"丛书名=Communications in Computer and Information Science"

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Natural Language Processing Techniques to Identify Work Profiles from Online Job Postings 1

引用

4th International Conference on Advanced Research in Technologies information Innovation and Sustainability-ARTIIS-Annual

作者： Ferreira, Alejandro Gomez, Walter Grunewald, Ingrid Univ Catolica Temuco Dept Ind Proc Temuco Chile Univ la Frontera Dept Math Engn Temuco Chile Consorcio Univ Estado Chile Santiago Chile

ISBN: (数字)9783031832079

ISBN: (纸本)9783031832062;9783031832079

The present study generates a new methodology which allows us to study the job market in order to identify work profiles based on job openings published online. The methodology includes 5 stages: Web scraping, Data pre-processing, Document filtering (job offers), Topic Modeling, and the Concept Grouping Stage and profile characterization. As a case study, we consider the Psychology profession, for which a corpus of 6,407 job listings was generated. In this case, document filtering was done based on Word2Vec and BERT, with the latter emerging as the better alternative. The corpus was thus reduced to 4,314. For the case study, we also constructed a graphic schema in order to visualize the job offers' location and the graduation profiles with regards to the work profiles identified. The results from the Topic Modeling stage and the graphic projection are presented on dashboards, allowing for user interaction. The methodology developed has potential to help Higher Education Institutions redesign their curricula and review their graduation profiles, both fundamental aspects needed in their Accreditation processes, their continuous improvement and quality assurance processes

关键词： Natural language processing Machine learning Data intelligence Working market Work profiles

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On the Calculation of the Boiler Thermal Diagram 2nd

On the Calculation of the Boiler Thermal Diagram

引用

2nd International Conference on information Technologies and Their Applications

作者： Zhurbenko, Mykola Bardadym, Tamara NASU VM Glushkov Inst Cybernet Kyiv Ukraine

ISBN: (纸本)9783031734168;9783031734175

The complex technical object usually can be described as a set of technological components (blocks). Its functional diagram can be represented by an oriented multi-graph. The vertices of the graph correspond to separate components (blocks) of a technical object. The blocks are characterized by design parameters. The graph may contain feedback loops. Blocks' output parameters can be determined from the values of their input parameters. The software developed in C++ language serves for calculating functional diagrams of steam boilers. The software determines also the values of derived output parameters from the design parameters values. It can be used to improve the technical characteristics of an object and determine control parameters for various modes of its operation. The calculation of the thermal scheme is based on the use of a model heat exchanger. In this case, the calculation of the thermal scheme is reduced to an iterative solution of a system of linear equations. A brief description of the software is provided.

关键词： Steams Boilers Functional Diagram Optimal Design Numerical Algorithm Software

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Software Practice and Experience on Smart Mobility Digital Twin in Transportation and Automotive Industry 4th

Software Practice and Experience on Smart Mobility Digital T...

引用

24th International Conference Web Engineering (ICWE)

作者： Kang, Jonggu Sungshin Womens Univ Seoul South Korea

ISBN: (纸本)9783031751097;9783031751103

A digital twin is a virtual representation of a physical entity, serving as a pivotal convergence technology that facilitates the diagnosis, optimization, prediction, and problem-solving of the corresponding physical entity. It is widely applicable across diverse sectors, including automobiles, manufacturing, logistics, and smart cities. The automotive industry, in particular, is actively integrating digital twin throughout the entire product lifecycle from research and development, production, sales, and services to enhance the overall customer experience. This paper presents insights into software practices and experiences related to the implementation of smart mobility digital twin. Drawing from lessons learned in digital twin projects, we outline guidelines for effective application. It is expected to gradually improve transportation convenience and utility value for customers through a comprehensive analysis that integrates the digital twin of the vehicle with those of the surrounding environment, including traffic patterns and human behavior, in conjunction with spatio-temporal information.

关键词： Digital Twin Internet of Things Mobility Connected Vehicle Software Defined Vehicle Smart City Transportation Automotive

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Empirical Analysis of Conformer Impact on the CTC-CRF Model in Kazakh Speech Recognition 2nd

Empirical Analysis of Conformer Impact on the CTC-CRF Model ...

引用

2nd International Conference on information Technologies and Their Applications

作者： Oralbekova, Dina Mamyrbayev, Orken Alimhan, Keylan Zhumazhan, Nurdaulet Inst Informat & Computat Technol Alma Ata Kazakhstan Acad Logist & Transport Alma Ata Kazakhstan Eurasian Natl Univ LN Gumilyov Nur Sultan Kazakhstan Joldasbekov Inst Mech & Engn Alma Ata Kazakhstan

ISBN: (纸本)9783031734199;9783031734205

The enhancement of quality and efficiency in contemporary speech technology systems is increasingly reliant on the application of machine learning techniques. Recent advancements have highlighted the superior performance of end-to-end speech recognition methods. Integrating multiple end-to-end model architectures within a single network has yielded competitive outcomes. This study focuses on the development and evaluation of an integrated Connectionist Temporal Classification-Conditional Random Field system, augmented with the Conformer, to enhance the recognition accuracy of a low-resource language such as Kazakh. Due to the limited electronic and digital resources in the Kazakh language, extensive efforts are required for the collection and compilation of a comprehensive speech and text corpus. Additionally, this necessitates the development of novel mathematical models and algorithms to address the challenges in automatic speech recognition for agglutinative (Turkic) languages. The research findings demonstrate that the incorporation of the Conformer model alongside CTC-CRF frameworks significantly improves speech recognition outcomes. The system, utilizing the ResNet network and RNN-based language models, further enriched with the Conformer, attained optimal performance, enhancing the recognition accuracy by 1.6%.

关键词： Automatic Speech Recognition CTC-CRF Model Conformer Kazakh Language Low-resource Language

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Integration of Multi-feature Analysis with Lightweight CNN Model for Heart Sound Classification 4th

Integration of Multi-feature Analysis with Lightweight CNN M...

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4th International Conference on Advanced Network Technologies and Intelligent Computing-ANTIC-Annual

作者： Mohanty, Subhra Patra, Sabyasachi IIIT Bhubaneswar Dept CSE Bhubaneswar Odisha India

ISBN: (纸本)9783031837890;9783031837906

Detecting cardiac diseases is crucial due to their widespread prevalence globally. Auscultation is the first step in diagnosing, and professionals depend primarily on their knowledge and experience in this area. Automating this process using artificial intelligence (AI) could significantly improve efficiency. AI has demonstrated the potential to enhance the accuracy of heart sound classification by analyzing relevant features and learning their relationships with different cardiac diseases. The 2016 PhysioNet/CinC Challenge database, which contains cardiac sound recordings, is one of the publicly accessible datasets used in this research. The developed model achieves a maximum accuracy of 91.04%. Furthermore, the study extends its contribution by employing Explainable Artificial Intelligence (XAI) to elucidate model predictions, enhancing interpretability. Notably, the novelty lies in the CNN model's ability to classify heart sounds by integrating audio-specific features for improved classification performance.

关键词： artificial intelligence PhysioNet/CinC Challenge XAI CNN audio-specific features

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Avoiding the Unconfoundednes Assumption: Counterfactual Inference Considering Unobserved Confounders 6th

Avoiding the Unconfoundednes Assumption: Counterfactual Infe...

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6th Pacific Causal Inference Conference

作者： Zhao, Yonghe Peng, Yun Sun, Huiyan Jilin Univ Sch Artificial Intelligence Changchun Peoples R China Baidu Netdisk Dept Data Anal Beijing Peoples R China

ISBN: (纸本)9789819778119;9789819778126

Counterfactuals are the basis of causal inference in observational studies. The fundamental challenge in counterfactual inference lies in addressing the impact of both observed and unobserved confounders. Despite the multitude of proposed methods aimed at addressing observed confounding bias, these approaches are contingent upon the untestable assumption of Unconfoundedness, which posits the absence of unobserved confounders. In this paper, we present a practical framework of Counterfactual Inference Considering Unobserved Confounders (CIUC), which effectively addresses the influence of both observed and unobserved confounders, thereby enabling precise estimation of counterfactual outcomes. Specifically, the CIUC framework begin by employing variational learning to derive the distribution of unobserved confounders disentangled from observed covariates, relaxing the untestable assumption of Unconfoundedness. Furthermore, within the framework, we incorporate a balanced representation model that takes into account both observed and unobserved confounders. This integration guarantees the attainment of unbiased inferences. The CIUC framework is versatile, as it can accommodate both discrete and continuous treatment variables. Additionally, it seamlessly integrates with various existing counterfactual inference models, making it applicable across a wide range of scenarios. In contrast to the majority of existing methods, the CIUC framework goes beyond by offering confidence intervals for the counterfactual outcomes, which proves highly advantageous for risk-sensitive tasks. Extensive experiments conducted on synthetic, semi-synthetic, and real-world datasets provide compelling evidence of the CIUC's outstanding performance in generating unobserved confounders, learning balanced representations, and accurately estimating treatment effects at both group and individual levels.

关键词： Counterfactual Inference Unobserved Confounder Confounding Adjustment Variational Learning Balanced Representation

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Personalized Recommendation Algorithm Based on Knowledge Graphs with High-Order information 42nd

Personalized Recommendation Algorithm Based on Knowledge Gra...

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42nd National Conference on Theoretical computer science

作者： Zhang, Siyao Wang, Zhihui Hu, Jinru Chen, Jianrui Shaanxi Normal Univ Sch Comp Sci Xian 710199 Peoples R China

ISBN: (纸本)9789819614899;9789819614905

With the rapid development of network technology, recommendation systems attract increasing research because of its wide applications in e-commerce. Nevertheless, most existing recommendation models based on graph neural networks do not consider the transitivity of subgraph structures in interactive data. This makes the models unable to capture the complex dependencies and mutual influences between users and items, resulting in the inability to achieve high-quality personalized recommendations. To address the above challenge, we propose a novel recommendation algorithm based on knowledge graph with high-order graph convolutional network, named KG(2)CN. Firstly, we introduce the subgraph structure on the knowledge graph to capture high-order contextual information between users and items. Secondly, the mined subgraph information and graph convolutional network are combined to learn high-order features of users and items. Finally, the decoder is applied to predict the ratings of target users on the uninteracted items, thereby recommending the Top-K items. Experimental results on the Book-Crossing and *** datasets show that the proposed KG(2)CN obtains better performance in F1 score and AUC metrics.

关键词： Recommendation Algorithm Knowledge Graph Graph Convolutional Network High-order Pattern

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A Note to the Construction of t-Norms Based on T^nM 4th

A Note to the Construction of t-Norms Based on T<SUP>nM</SUP...

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4th International Conference on Artificial Intelligence Logic and Applications

作者： Zheng, Liteng Li, Gang Qilu Univ Technol Sch Math & Stat Shandong Acad Sci Jinan 250353 Peoples R China

Triangular norms are extensively applied in fuzzy logic. The transformation of the nilpotent minimum t-norm using a non-decreasing transformation yielding a special type of triangular norm is discussed. Some character... 详细信息

ISBN: (纸本)9789819603534;9789819603541

关键词： triangular norm nilpotent minimum pseudo-inverse non-decreasing transformation

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SACC: Secure-Cooperative Adaptive Cruise Control for Unmanned Vehicles 7th

SACC: Secure-Cooperative Adaptive Cruise Control for Unmanne...

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8th Asia Pacific Web and Web-Age information Management Joint International Conference on Web and Big Data

作者： Ran, Wen Li, Changlong Sha, Edwin H-M. East China Normal Univ Dept Comp Sci Shanghai Peoples R China

ISBN: (纸本)9789819600540;9789819600557

With the development of autonomous driving, the data security of the collaboration between vehicles plays a more important role. The research of auto drive systems is still in its infancy, this paper shows that the security mechanisms either depend on hardware or introduce high latency. This paper proposes a novel data protection strategy for efficient coordination across vehicle systems. Our design is based on an observation that the security demand in different phases varies. Specifically, for the external system, this paper proposes an information security scheme with a fine-grained attribute selection mechanism, which has the flexibility of encryption attribute selection. For the internal system, this paper proposes a dual-channel RSA encryption scheme that makes the control information transmission more robust and saves encryption delay. Experimental results illustrate that both security and low latency can be ensured with the proposed SACC.

关键词： Data Security Unmanned Vehicles CACC Attribute-based Encryption

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Optimizing Gesture Recognition for Real-Time Mouse Control with MEG-YOLOv5 5th

Optimizing Gesture Recognition for Real-Time Mouse Control w...

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5th China Intelligent Robotics Academic Conference

作者： Liu, Yingqi Ma, Jitong Chen, Xiao Jin, Sinian Ju, Moran Wang, Xinnian Dalian Maritime Univ Informat Sci & Technol Coll Dalian 116026 Peoples R China Dalian Maritime Univ Coll Int Collaborat Dalian 116026 Peoples R China

ISBN: (纸本)9789819616138;9789819616145

With the rapid development of human-computer interaction technology, gesture recognition systems have been widely recognized as critical technologies for improving the naturalness and efficiency of interactions, and they play essential roles in industrial production, scientific research, and so on. In actual applications, existing gesture mouse control systems often lack accuracy and delay in response, failing to meet demand. To solve this problem, we propose a gesture control mouse system based on MobileNetV3-Efficient Channel Attention-Ghost Yolov5 by replacing the YOLOv5 backbone network, Cspdarknet53, with the lightweight MobileLeNetv3 and integrating ECA and GhostNet into the backbone network. The results showed that this technique could identify gestures effectively and accurately and had high processing speed. The improved gesture control mouse system surpassed the existing technology in nine experimental environments. The model execution time was reduced by 8%, and the recognition accuracywas improved by 4%. These advantages provide more opportunities to improve the user experience, improve production efficiency, and solve practical problems.

关键词： MEG-YOLOv5 ECA mechanism gesture recognition real-time human-computer interaction

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