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Incremental Transitive Closure for Zonal Abstract Domain 1

引用

14th International NASA Formal Methods symposium (NFM)

作者： Ballou, Kenny Sherman, Elena Boise State Univ Boise ID 83725 USA

ISBN: (数字)9783031067730

ISBN: (纸本)9783031067730;9783031067723

the Zonal numerical domain is an efficient, weakly-relational abstract domain in static analysis by abstract interpretation. Compared to the Interval domain, the Zonal domain is capable of discovering weak relations between two program variables. To reason about Zonal states, it is imperative that they are transformed into a canonical closed form. this task is accomplished through the transitive closure operation commonly implemented as the all-pairs shortest path algorithm, with O(n(3)) complexity, where n is the number of program variables. In this work, we explore the closed form of Zonal states in the context of a data-flow analysis framework. Also, we present an incremental transitive closure algorithm that preserves a closed form of an updated Zonal state. the algorithm reduces the overall analysis complexity to O(n(2)). We evaluate our approach by performing intra-procedural Zonal analysis on 63 real-world programs. the results show an improvement in runtime, especially on large programs. For example, an hour-long analyzer run with the traditional Zonal implementation has been reduced to a minute with the proposed incremental Zonal variant.

关键词： data flow analysis

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Enabling Comparative analysis of Election data in Ecuador 21

Enabling Comparative Analysis of Election Data in Ecuador

引用

14th International symposium on Visual Information Communication and Interaction, VINCI 2021

作者： Méndez, Gonzalo Gabriel Moreno, Oscar Escuela Superior Politécnica Del Litoral Guayaquil Ecuador

ISBN: (纸本)9781450386470

We present an interactive visualization tool that enables exploration and comparative analyses of election data in multi-partisan systems. We motivate and explain our design in the context of the Ecuadorian political landscape. We demonstrate the tool with data from Ecuador's three most recent presidential elections. Our tool enables both relative and absolute comparisons of the election results. © 2021 Owner/Author.

关键词： data visualization

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Target Recognition through Time-Domain Scattering Echo based on CNN

Target Recognition Through Time-Domain Scattering Echo based...

引用

International symposium on Antennas, Propagation and EM theory (ISAPE)

作者： Yuquan Yang Guangbin Guo Yanchun Zuo Rui Wang Wei Liu School of Physics Xidian University Xi'an China School of Electronic Physics Xidian University Xian China

ISBN: (数字)9798350353129

ISBN: (纸本)9798350353136

In this paper, based on the shooting and bouncing ray (SBR) method to obtain a large number of target time-do main scattering echo data, an electrically large-size target echo dataset is produced, and two kinds of tank targets are recognized by using the convolutional neural network (CNN) model. the results show that compared with the target recognition using optical images, the target recognition by timedomain electromagnetic scattering data is better, and the minimum recognition accuracy of CNN for similar targets is above 95%.

关键词： Image recognition Target recognition Antenna theory Optical propagation Optical computing Optical imaging data models Convolutional neural networks Optical scattering Time-domain analysis

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Grounded theory-Driven Knowledge Production Features Mining: One Empirical Study Based on Big data Technology 4th

Grounded Theory-Driven Knowledge Production Features Mining:...

引用

4th International Conference on Big data and Security, ICBDS 2022

作者： Xu, Hao Li, Yiyang Wang, Mulan Peng, Yufang Chen, Qinwei Liu, Pengcheng Li, Yijing School of Economics and Management Nanjing Institute of Technology Jiangsu Nanjing211167 China School of Information Management Nanjing University Jiangsu Nanjing210023 China Nanjing University of Information Technology Jiangsu Nanjing210044 China

ISBN: (纸本)9789819932993

Grounded theory can help scholars solve complex management problems and build a link between practice and theory and has received much attention in recent years. this paper takes CNKI as primary data source, constructs professional retrieval strategy, realizes initial collection of academic papers related to grounded theory, and then combines content analysis methods to manually annotate 2358 papers from titles, keywords, abstracts, and full texts. To realize whether one paper uses grounded theory approach to conduct research. Using the scientific knowledge graph drawing tool CiteSpace, combined with information visualization analysis and social network analysis methods, to identify characteristics of knowledge production driven by grounded theory as a knowledge carrier. the research indicates: In terms of research focus, related research focuses on the multidisciplinary application of grounded theoretical analysis methods and their integration with qualitative research, mixed research, case study and other methods, and focuses on revealing influencing factors of various research issues;in terms of time, grounded theory became the central node of complex networks in 2004, and began to focus on the integration and application of various research tools in 2006, with apparent characteristics of temporal changes;in terms of the features of scientific research collaboration, the grounded theory-driven scientific research collaboration process has formed multiple research sub-networks oriented to the fields of management and education. In the institutional cooperation network, it is found that the large-scale institutional cooperation network driven by the grounded theoretical analysis method has not yet formed and the formed ones were driven by grounded theory can be well used in key links such as innovation management, management consulting decision making, etc. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Complex networks

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Teaching innovation results based on double helix teaching strategy and ADDIE model- Take the Big data and visualization course for example

Teaching innovation results based on double helix teaching s...

引用

IEEE International symposium on Information (IT) in Medicine and Education, ITME

作者： Jia Luo Mingming Li Guiyang College of Humanities and Technology&Information Engineering Guiyang China

ISBN: (数字)9798350356670

ISBN: (纸本)9798350356687

"Big data analysis and visualization" course focuses on innovative teaching concepts and content, integrating key skills of data science and ideological and political education. this course not only focuses on teaching professional knowledge of big data processing, analysis and visualization, but also emphasizes the importance of ideological and political education to cultivate students' social responsibility and ethical concepts in the field of data science. According to the teaching pain points of students' weak data thinking ability, lack of practical project training and ideological and political thinking in this course, this paper proposes to reconstruct the "internal spectrum" and "external spectrum" of course design based on the double helix teaching strategy and ADDIE teaching mode, and the teaching objectives of the course clearly show its content structure and its connection with other fields of data science. Guided by the needs of enterprise talents, with the purpose of applying what we have learned and scenario-based case teaching, we will raise our teaching objectives and thinking to a higher level. through online and offline mixed teaching, we will conduct reality training, practical projects and practical tests to create a composite, application-oriented and innovative talent training model that Adapts to the new situation and has the latest thinking and skills. through practical teaching and case studies, students' engineering practice innovation ability has been significantly improved, and they have achieved excellent results in various national and provincial data science competitions, demonstrating the remarkable effect of the course in cultivating students' synthesis ability,Cultivate data science application talents with innovative thinking and cross-border integration.

关键词： Training Technological innovation Analytical models Pain Education Employment data visualization data science Big data data models

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Visual Linking of Feature Values in Immersive Graph visualization Environment 21

Visual Linking of Feature Values in Immersive Graph Visualiz...

引用

14th International symposium on Visual Information Communication and Interaction, VINCI 2021

作者： Sassa, Hinako Cordeil, Maxime Yoshida, Mitsuo Itoh, Takayuki Ochanomizu University Tokyo Japan Monash University Melbourne Australia Toyohashi University of Technology Toyohashi Japan

ISBN: (纸本)9781450386470

there are a variety of graphs where multidimensional feature values are assigned to the nodes. visualization of such datasets is not an easy task since they are complex and often huge. Immersive Analytics is a powerful approach to support the interactive exploration of such large and complex data. Many recent studies on graph visualization have applied immersive analytics frameworks;however, there have been few studies on immersive analytics for visualization of multidimensional attributes associated with the input graphs. this paper presents a new immersive analytics system that supports the interactive exploration of multidimensional feature values assigned to the nodes of input graphs. the presented system displays "label-axes"corresponding to the dimensions of feature values, and "label-edges"that connect label-axes and corresponding to the nodes. the system supports visual linking operations which controls the display of edges that connect a label-axis and nodes of the graph. this paper introduces visualization examples with a graph dataset of Twitter users and reviews by experts on graph data analysis. © 2021 ACM.

关键词： Virtual reality

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14th International symposium on Intelligence Computation and Applications, ISICA 2023

14th International Symposium on Intelligence Computation and...

引用

14th International symposium on Intelligence Computation and Applications, ISICA 2023

ISBN: (纸本)9789819743926

the proceedings contain 44 papers. the special focus in this conference is on Intelligence Computation and Applications. the topics include: Research on Smart Agriculture Big data System Based on Spark and Blockchain;a Multiparty Reversible data Hiding Scheme in Encrypted Domain Based on Hybrid Encryption;packet Performance Predictor Based on Graph Isomorphism Network for Neural Architecture Search;visualization analysis of Convolutional Neural Network Processes;multimedia Information Retrieval Method Based on Semantic Similarity;Research on Intelligent Clustering Scoring of English Text Based on XGBOOST Algorithm;multi-recipient Public-Key Authenticated Encryption with Keyword Search;machine Learning-Assisted Optimization of Direction-Finding Antenna Arrays;research on the Innovative Application of Computer Aided Design in Environmental Design;key Technology and Application Research Based on Computer Internet of things;mutate Suspicious Statements to Locate Faults;petrochemical Commodity Price Prediction Model Based on Wavelet Decomposition and Bayesian Optimization;construction and Quality Evaluation of Learning Motivation Model from the Perspective of Course Ideology and Politics;Study on TNM Classification Diagnosis of Colorectal Cancer Based on Improved Self-supervised Contrast Learning;design and Application of a Teaching Evaluation Model Based on the theory of Multiple Intelligences;edible Oil Price Forecasting: A Novel Approach with Group Temporal Convolutional Network and BetaAdaptiveAdam;artificial Intelligence in Intelligent Clothing: Design and Implementation;research on the Routing Protocol Algorithm Driven by the Dedicated Frequency Points of the Internet of things to Build a Network;research on Communication Power of Cross-Cultural Short Video Based on Qualitative Comparative analysis;research on Bayberry Traceability Platform Based on Blockchain;preface.

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Lightweight Language Model for Speech Synthesis: Attempts and analysis

Lightweight Language Model for Speech Synthesis: Attempts an...

引用

International symposium on Chinese Spoken Language Processing

作者： Zhuojun Wu Dong Liu Ming Li School of Computer Science Wuhan University Wuhan Suzhou Municipal Key Laboratory of Multimodal Intelligent Systems Data Science Research Center Duke Kunshan University Kunshan

ISBN: (数字)9798331516826

ISBN: (纸本)9798331516833

large-scale autoregressive text-to-speech (TTS) models can generate speech that is nearly indistinguishable from human speech. However, training large language models (LLMs) is challenging due to memory and computational constraints. this paper describes our TTS method for the 2024 Conversational Voice Clone Challenge (CoVoC). Our approach modifies the LauraGPT model to synthesize mixed Chinese and English text by expanding the Chinese pinyin vocabulary and reducing the number of layers in the decoder-only Transformer architecture. Despite using minimal training data, the performance gap between our method and other constrained systems is relatively small in both subjective and some objective evaluations. this paper discusses our attempt to train lightweight LLMs for zero-shot TTS and analyzes the factors contributing to low performance. Our audio samples can be accessed online 1 1 https://***/lwllmtts/.

关键词： Training Vocabulary Analytical models Computational modeling large language models Memory management Training data Cloning Transformers Text to speech

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Aspect-Based Cross-Modal Sentiment analysis of Fused Adjective-Noun Pairs

Aspect-Based Cross-Modal Sentiment Analysis of Fused Adjecti...

引用

International symposium on Parallel Architectures, Algorithms and Programming (PAAP)

作者： Ping He Huaying Qi Jiayue Cang School of Information Technology Hebei University of Economics and Business Shijiazhuang Hebei China

the objective of an aspect-based sentiment analysis task is to identify the emotional polarity of specific aspects in text sequences. Previous study usually only involve the text modality. However, user-generated comment data generally include not only plain text, but also a large number of image and text data. For ignoring the cross-modal correlation between image and multiple aspects of text, and the problem of alignment between text and image high-level semantics. We propose a new aspect-based cross-modal sentiment analysis model HCMI-PLNT (Hierarchical Cross-Modal Interaction - Pre-LN Transformer). the core idea of this model is to use the hierarchical cross-modal Pre-LN Transformer interaction module to capture the bidirectional deep interaction between aspect, text and image. the high-level semantic feature of images are obtained by extracting adjective-noun pairs (ANPs) from images, and the text is aligned with the high-level semantic of images. the accuracy of HCMI-PLNT model on the TWITTER-15 data set is 78.60%, and the accuracy on the TWITTER-17 data set is 72.43%. the experiment proves the feasibility and effectiveness of the HCMI-PLNT model.

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Accumulated Laboratory data in B12 Vitamin Blood Level Time Dependency Studies in Patients with Myeloma, Lymphocytic Leukemia and Myeloblastic Leukemia in Latvia 14

Accumulated Laboratory Data in B12 Vitamin Blood Level Time ...

引用

14th International Scientific and Practical Conference on Environment. Technology. Resources, ETR 2023

作者： Gavars, Didzis Auce, Agris Tauckels, Eriks Miķelsone, Agnese Tutane, Anna Inese Egils Gulbis Laboratory Riga Stradiņš University Riga Latvia University of Latvia Riga Latvia Egils Gulbis Laboratory Riga Latvia Riga Stradiņš University Riga Latvia

ISBN: (纸本)9781713874881

Vitamin B12 blood level in patients with myeloma (C90 - International Classification of Diseases (ICD-10)), lymphocytic leukemia (C91) and myeloblastic leukemia (C92) prior and after the diagnosis and also BCR-ABL (fusion gene from breakpoint cluster region BCR gene and tyrosine-protein kinase ABL1 (Abelson murine leukemia) gene) tests for C92 patients were studied. Clinical records of 20 C92 patients in Riga East University Hospital were complemented with 6987 B12 clinical test data accumulated in E Gulbis laboratory (EGL) for 7451 patients over 20 years period. BCR-ABL and B12 dynamics for 11 patients with sufficient number of BCRABL and B12 tests were studied. Oracle Cloud with pseudonymized data replica from more than 350 000 000 original EGL clinical test data was used. the data were selected by online analytical processing and SQL built in tools and then used in offline analysis and visualization. Annually there are 107, 189 and 91 confirmed cases of C90, C91 and C92 in Latvia. EGL has 30% more C90-92 patients, due to suspected but later unconfirmed cases. Out of 7451 patients 1386 had one B12 test, two- 548, three and more- 864. the patients with diagnosis fluctuating between C90, C91 and C92 were excluded from the study. the data for the time period of 10 years before and after the first diagnosis were analyzed. Results. Methods and tools for data extraction and analysis from large amount of archived clinical test data were developed and applied. High and very high B12 level was observed for 53% of C92 patients starting from 3 years prior to diagnosis. For C90 and C91 patients B12 level changes around the diagnosis date were also observed although the effect was considerably smaller. analysis of 11 selected patient data with clinical records showed timewise correlation between B12 and BCR-ABL for 3 of the patients. © 2023 Rezekne Higher Education Institution. All rights reserved.

关键词： Genes

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