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2023 Workshops of the EDBT/ICDT Joint conference, EDBT/ICDT-WS 2023

作者： Stamatopoulos, Vassilis Maroulis, Stavros Kozanis, Konstantinos Psarros, Ioannis Papastefanatos, George Giannopoulos, Giorgos Terrovitis, Manolis ATHENA Research Center Greece

Solar photovoltaic (PV) modules are a popular source of clean energy, and effective monitoring and optimization of their performance requires the ability to explore and analyze the measurement data from their sensors. In this work, we introduce a tool for the visual analysis of such data stored in raw measurement files, offering efficient interactive visualization directly on the files. The tool includes a soiling detection module, and novel UI modules that combine time series data visualization with advanced solar panel analytics presentation. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). CEUR Workshop Proceedings (***)

关键词： Solar energy

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Analyzing a Decade of Evolution: Trends in Natural Language Processing 26th

Analyzing a Decade of Evolution: Trends in Natural Language ...

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26th International conference on data Warehousing and Knowledge Discovery (DaWaK)

作者： Jonker, Richard A. A. Almeida, Tiago Matos, Sergio Univ Aveiro LASI IEETA DETI Aveiro Portugal

ISBN: (纸本)9783031683220;9783031683237

Natural Language Processing (NLP) stands at the forefront of the rapidly evolving landscape of Machine Learning, witnessing the emergence and evolution of diverse methodologies over the past decade. This study delves into the dynamic trends within the NLP domain, specifically spanning the years 2010 to 2022, through an empirical analysis of papers presented at conferences hosted by the Association for Computational Linguistics (ACL). We utilize ChatGPT in order to extract meaningful information from the data before performing an in depth analysis. Our investigation encompasses an exploration of several key aspects, namely computational trends, research trends and geographic trends. We further investigate the entry cost into NLP, the longevity of hardware and the environmental impact of NLP. The code to run our system is publicly available at https://***/ieeta-pt/nlp-trends.

关键词： data Analytics Natural Language Processing data Extraction NLP Trends

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Imaginations Generate Images for Multi-modal Machine Translation 1

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13th International conference on Computer Engineering and Networks (CENet)

作者： Yang, Xiaona Sun, Wenli Wei, Wei Li, Yinlin Shi, Xiayang Zhengzhou Univ Light Ind Zhengzhou Peoples R China Wuhan Second Ship Design & Res Inst Wuhan Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

ISBN: (数字)9789819992430

ISBN: (纸本)9789819992454;9789819992430;9789819992423

Multi-modal machine translation (MMT) aims at exploring better translation systems by integrating the visual annotation which presents the content described in the bilingual parallel sentence pair into the conventional only-text neural machine translation (NMT). However, existing methods heavily rely on the manual annotated images data set. The cost of manual image annotation is relatively high at this stage. In this paper, we propose the generative imagination network with transformer to automatically generate visual annotations semantic-equivalent with source and target sentences. The proposed model receives the inputs of source-target bilingual sentences and generates visual annotations for MMT. Experiments analysis demonstrate that our model can generate high-quality annotated images and prompt the performance of MMT. Additionally, we use our model to generate annotated images for a famous English-German IWSLT-2015, the experimental results show the improvement for MMT.

关键词： Multi-modal machine translation visual annotation

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"Does the exploration of the Temporomandibular Joint Using a Deep Subfascial Technique Result in a Superior Operative Outcome?"

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JOURNAL OF ORAL AND MAXILLOFACIAL SURGERY 2023年第9期81卷 1072-1082页

作者： Mohanty, Sujata Shankar, Hemavathy Chaudhary, Zainab Sharma, Pankaj Verma, Anjali Gupta, Arpit Maulana Azad Inst Dent Sci Dept Oral & Maxillofacial Surg New Delhi India Maulana Azad Inst Dent Sci Dept Oral & Maxillofacial Surg Floor 1MAMC ComplexBahadur Shah Zafar Marg New Delhi 110002 India

Purpose: The literature is replete with various approaches for the temporomandibular joint (TMJ), each with its own distinct advantages and disadvantages. None of these approaches, however, have been associated with superior operative outcomes. The purpose of this study was to measure the efficacy of three operative approaches to TMJ, namely superficial, subfascial, and deep subfascial approaches. The aim was to contrast selected intraoperative and postoperative outcomes among these surgical approaches. Methods: This was a prospective randomized clinical trial of subjects presenting to outpatient department. The primary predictor variables were three dissection planes of TMJ: Group-I (superficial), Group-ii (subfascial), and Group-iiI (deep subfascial). The primary outcome variables were quality of surgical field employing fromme scale, dissection time in minutes, amount of blood loss in milliliters, and facial nerve function (FNF) using House-Brackmann scale. The secondary outcome variables were postoperative pain using visual-analog scale and swelling in millimeters measured on 1st, 3rd, and 7th postoperative days and quality of life using facial clinimetric evaluation questionnaire at 6-month follow-up. Age, gender, side, diagnosis, and type of surgery were the covariates. The data were analyzed using descriptive, comparative, and regression analysis. A P value of less than .05 was considered statistically significant. Result: The study included thirty subjects (8 males and 22 females) with various TMJ disorders ranging in age from 8 years to 65 years (mean 27.83 +/- 10.52). On evaluation of intraoperative parameters, subfascial approach had statistically significant superior quality of surgical field (Group-I: 1.90 +/- 0.57;Group-ii: 1.10 +/- 0.32;Group-iiI: 1.40 +/- 0.52;P value = .006), statistically significant shortest dissection time (Group-I: 18.30 +/- 3.74 min;Group-ii: 13.240 +/- 1.96 min;Group-iiI: 16.20 +/- 1.99 min;with P value = .03), and statistical

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The Galactic bulge exploration ii. Line-of-sight velocity templates for single-mode RR Lyrae stars

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ASTRONOMY & ASTROPHYSICS 2024年第5期685卷

作者： Prudil, Z. Smolec, R. Kunder, A. Koch-Hansen, A. J. Dekany, I. European Southern Observ Karl Schwarzschild Str 2 D-85748 Garching Germany Heidelberg Univ Astron Rechen Inst Zentrum Astron Monchhofstr 12-14 D-69120 Heidelberg Germany Polish Acad Sci Nicolaus Copernicus Astron Ctr Bartycka 18 PL-00716 Warsaw Poland St Martins Univ 5000 Abbey Way SE Lacey WA 98503 USA

We present a new set of tools to derive systemic velocities for single-mode RR Lyrae stars from visual and near-infrared spectra. We derived scaling relations and line-of-sight velocity templates using both APOGEE and Gaia spectroscopic products combined with photometric G-band amplitudes. We provide a means to estimate systemic velocities for the RR Lyrae subclasses, RRab and RRc. Our analysis indicates that the scaling relation between the photometric and line-of-sight velocity amplitudes is nonlinear, with a break in a linear relation occurring around approximate to 0.4 mag in both the V-band and G-band amplitudes. We did not observe such a break in the relation for the first-overtone pulsators. Using stellar pulsation models, we further confirm and examine the nonlinearity in scaling relation for the RRab subclass. We observed little to no variation with stellar parameters (mass, metallicity, and luminosity) in the scaling relation between the photometric and line-of-sight velocity amplitudes for fundamental-mode pulsators. We observed an offset in the scaling relation between the observations and stellar pulsation models, mainly in the low-amplitude RR Lyrae regime. This offset disappears when different sets of convective parameters are used. Thus, the Fourier amplitudes obtained from the photometry and line-of-sight velocity measurements can be utilized to constrain convective parameters of stellar pulsation models. The scaling relations and templates for APOGEE and Gaia data accurately predict systemic velocities compared to literature values. In addition, our tools derived from the Gaia spectra improve the precision of the derived systemic velocities by approximately 50 percent and provide a better description of the uncertainty distribution in comparison with previous studies. Our newly derived tools will be used for RR Lyrae variables observed toward the Galactic bulge.

关键词： techniques: radial velocities stars: variables: RR Lyrae Galaxy: bulge Galaxy: kinematics and dynamics

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Right Tool, Right Job: Recommendation for Repeat and exploration Consumption in Food Delivery 24

Right Tool, Right Job: Recommendation for Repeat and Explora...

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18h ACM conference on Recommender Systems (RecSys)

作者： Li, Jiayu Sun, Aixin Ma, Weizhi Sun, Peijie Zhang, Min Tsinghua Univ Quan Cheng Lab DCST Beijing Peoples R China Nanyang Technol Univ CCDS Singapore Singapore Tsinghua Univ AIR Beijing Peoples R China Tsinghua Univ DCST Beijing Peoples R China

ISBN: (纸本)9798400705052

From e-commerce to music and news, recommender systems are tailored to specific scenarios. While researching generic models applicable to various scenarios is crucial, studying recommendations based on the unique characteristics of a specific and vital scenario holds both research and, more importantly, practical value. In this paper, we focus on store recommendations in the food delivery scenario, which is an intriguing and significant domain with unique behavior patterns and influential factors. First, we offer an in-depth analysis of real-world food delivery data across platforms and countries, revealing that (i) repeat and exploration orders are both noticeable behaviors and (ii) the influences of historical and collaborative situations on repeat and exploration consumption are distinct. Second, based on the observations, we separately design two simple yet effective recommendation models: RepRec for repeat orders and ExpRec for exploration ones. An ensemble module is further proposed to combine recommendations from two models for a unified recommendation list. Finally, experiments are conducted on three datasets spanning three countries across two food delivery platforms. Results demonstrate the superiority of our proposed recommenders on repeat, exploration, and combined recommendation tasks over various baselines. Such simple yet effective approaches will be beneficial for real applications. This work shows that dedicated analyses and methods for domain-specific characteristics are essential for the recommender system studies.

关键词： Food Delivery Recommendation Repeat Consumption User Behavior Modeling Context-aware Recommendation

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Exploratory analysis of Zero-Shot Lunar Crater Detection using SAM for Chandrayaan-2 Images 3

Exploratory Analysis of Zero-Shot Lunar Crater Detection usi...

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3rd International conference on Communication, Control, and Intelligent Systems, CCIS 2024

作者： Koranglekar, Kaustubh Prateek, K. Kumar, Shankar Biswas, Dheeraj Kumar Khanna, Nitin Department of Mechatronics Bhilai India Department of Electrical Engineering Bhilai India Department of Computer Science and Engineering Bhilai India

ISBN: (纸本)9798331528201

This paper explores the application of a zero-shot lunar crater detection method based on the Segment Anything Model (SAM) for high-resolution Digital Terrain Model (DTM) images from ISRO's Chandrayaan-ii mission. A pre-trained transformer-based instance segmentation model, SAM, is used to segment and identify lunar craters without requiring training data. The proposed method is capable of detecting craters in varying crater sizes and shapes, highlighting its potential for generalizable planetary feature detection. This work investigates the applicability of general-purpose deep learning models in planetary exploration and offers insights for efficient lunar surface analysis. © 2024 IEEE.

关键词： Lunar surface analysis

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Rich Screen Reader Experiences for Accessible data visualization

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COMPUTER GRAPHICS FORUM 2022年第3期41卷 15-27页

作者： Zong, Jonathan Lee, Crystal Lundgard, Alan Jang, JiWoong Hajas, Daniel Satyanarayan, Arvind MIT Cambridge MA 02139 USA Carnegie Mellon Univ Pittsburgh PA 15213 USA UCL London England

Current web accessibility guidelines ask visualization designers to support screen readers via basic non-visual alternatives like textual descriptions and access to raw data tables. But charts do more than summarize data or reproduce tables;they afford interactive data exploration at varying levels of granularity-from fine-grained datum-by-datum reading to skimming and surfacing high-level trends. In response to the lack of comparable non-visual affordances, we present a set of rich screen reader experiences for accessible data visualization and exploration. Through an iterative co-design process, we identify three key design dimensions for expressive screen reader accessibility: structure, or how chart entities should be organized for a screen reader to traverse;navigation, or the structural, spatial, and targeted operations a user might perform to step through the structure;and, description, or the semantic content, composition, and verbosity of the screen reader's narration. We operationalize these dimensions to prototype screen-reader-accessible visualizations that cover a diverse range of chart types and combinations of our design dimensions. We evaluate a subset of these prototypes in a mixed-methods study with 13 blind and visually impaired readers. Our findings demonstrate that these designs help users conceptualize data spatially, selectively attend to data of interest at different levels of granularity, and experience control and agency over their data analysis process. An accessible HTML version of this paper is available at: http://***/pubs/rich-screen-reader-vis-experiences.

关键词： CCS Concepts • Human-centered computing → visualization design and evaluation methods Accessibility design and evaluation methods

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Exploring Deep Learning-Based visual Localization Techniques 3

Exploring Deep Learning-Based Visual Localization Techniques

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2023 IEEE 3rd International conference on data Science and Computer Application, ICDSCA 2023

作者： Yu, Zhuoyi Maynooth University International Engineering College Fuzhou University Fuzhou China

ISBN: (纸本)9798350341546

This comprehensive review paper explores the state of the art in visual localization and navigation, drawing on the principles and methodologies of three significant deep learning networks: visual Localization Network (VLocNet), Deep Fusion Network (DFNet), and Hybrid Frontend Network (HFNet). Each of these networks demonstrates the application of deep learning to spatial awareness and navigation tasks in unique and significant ways. Rather than an exhaustive dissection of these networks, the paper provides an encompassing overview, illuminating their underlying principles, architectural design, and their relative performance within the field. Additionally, the paper delves into the practical implications of these networks, examining their applications in diverse real-world scenarios. It underlines this examination with a comprehensive analysis of existing literature and experimental results, intended to impart a profound understanding of these networks' strengths, limitations, and potential application areas. Ultimately, this review aims to present a valuable compass to researchers navigating the evolving landscape of advancements in visual localization and navigation, thereby fostering enriched understanding and facilitating future exploration and development in this compelling field. © 2023 IEEE.

关键词： Computer vision Deep learning Object recognition Robotics visual localization Convolutional neural networks

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Disinformation analysis and Tracking Dashboard

Disinformation Analysis and Tracking Dashboard

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International conference on Military Communications and Information Systems (ICMCIS)

作者： Mandravickait, Justina Songailait, Milita Kankeviciute, Egle Volcok, Anton Krilavicius, Tomas Vytautas Magnus Univ Fac Informat CARD Kaunas Lithuania Lingo Data CARD Vilnius Lithuania

ISBN: (纸本)9798350343854

The importance of disinformation identification and tracking in the information age is not questionable. War in Ukraine, information attacks in Baltic states, and a number of other disinformation attacks worldwide show that it is becoming a conventional tool in information space. In this paper, we present a disinformation analysis and tracking dashboard. It has 3 main components: Disinformation Analyzer, Match disinformation cases and Model Accuracy. The first component consists of a fined-tuned RoBERTa model for classifying textual input into fake and neutral. The second component contains semantic matching functionality for checking the semantic similarity of input text to the set of known disinformation cases. The third component includes the confusion matrix and model accuracy information. All 3 components have been combined into visual analytics platform for easy inspection and exploration of potential and known disinformation cases. The majority of the work was done during TIDE Hackathon 2023 as a part of the Disinformation Analyzer Challenge.

关键词： fake news disinformation deep learning BERT visual analytics

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