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7th international conference on Communication and Electronics Systems, ICCES 2022

ISBN: (纸本)9781665496346

the proceedings contain 301 papers. the topics discussed include: a new method for blood cell image segmentation and counting based on PCNN and autowave;an edge-based approach for segmentation of prostate ultrasound images using phase symmetry;discrimination of intended movements based on nonstationary EMG for a prosthetic hand control;fuzzy image fusion application in detecting coronary layers in IVUS pictures;ARMA modeling for the diagnosis of controlled epileptic activity in young children;ERP qualification exploiting waveform, spectral and time-frequency infomax;switching space-time interference cancellation for OFDM systems with unsynchronized cells;the phase invariance condition for the ultra-wideband voltage controlled attenuator;new global blind equalization with auto phase rotation correction;simulation-based validation of improved bp-based decoding algorithms of LDPC codes;exponentially-modulated filter bank transmultiplexer with fine-coarse adaptive filtering;and adaptive context for generic pattern matching in ad hoc social networks.

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Research overview of urban carbon emission measurement and future prospect for GHG monitoring network

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ENERGY REPORTS 2023年 9卷 231-242页

作者： Xiong, Tianlong Liu, Yawen Yang, Chao Cheng, Qing Lin, Shu Tsinghua Univ Sichuan Energy Internet Res Inst Chengdu 61000 Peoples R China Sinopec Shanghai Offshore Oil Bur Shanghai 201200 Peoples R China

the majority of anthropogenic carbon dioxide emissions originate from cities, nonetheless, it is common to have inaccuracies and uncertainties in urban carbon emission measurement. Many countries have devoted much effort to improve the accuracy and consistency of urban emission data through improving measurement tools and inversion models. the paper presents achievements of research in the U.S and Europe, as well as discusses their technical impacts and obstacles. the paper provides an overwiew of the technical impacts and research gaps of CO2-USA network and the Carbosense CO2 sensor network in Switzerland, we discuss the spatial and temporal distribution characteristics of greenhouse gas concentrations and explain the principles of carbon emission inversion method. the CO2-USA network applies an interdisciplinary approach to estimate urban carbon emission to simulate the transport process of CO2 molecules in the atmosphere. the Carbosense network employs dense networks to observe the changing process of carbon dioxide emissions via enhancing data quality of low-cost carbon dioxide sensors. the purpose of this paper is to propose a novel framework of GHG observing network which combines carbon emission estimation method and real-time greenhouse gas monitoring network. the framework applies in-situ sites and mobile observations to build high-resolution emissions inventories and gain greenhouse gas concentration mappings in the urban regions. It provides governments with reliable measurement results for planning research directions for carbon emission management in China over the next few years.(c) 2023 the Authors. Published by Elsevier Ltd. this is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Carbon emissions Urban greenhouse gas observing network Carbon inversion modeling Urban carbon sources sinks

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modeling of a thick Cylindrical Pneumatic Leg for a Soft Parallel Robot

Modeling of a Thick Cylindrical Pneumatic Leg for a Soft Par...

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IEEE international conference on Soft Robotics (RoboSoft)

作者： Zeinab Awada Hamza El Jjouaoui Marc Gouttefarde Yassine Haddab LIRMM Univ Montpellier CNRS Montpellier France

Soft manipulators have experienced a significant development over the past few years thanks to their versatility, compliance, and safety. Soft manipulators made of hyperelastic materials present a modeling challenge due to their combined geometric and material nonlinearity, alongside their leveraged compliance. this paper considers a thick cylindrical pneumatic actuator in the context of a soft parallel robot. the input pressure and the external axial force to which it is subjected are modeled. the analytical solutions for these models are then derived using the Yeoh strain energy density function. the advantage of using the Yeoh material model is guaran-teeing the existence of an analytical solution regardless of the material used for the fabrication of the cylindrical actuator. the accuracy of the models is evaluated using Finite Element Analysis, and a sensitivity analysis is also carried out to test their robustness. Finally, experimental results are provided and the importance of the material characterization is highlighted. the purpose of this work is to lay the foundation for future studies in modeling a soft parallel robot with three soft thick cylindrical “legs”.

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Towards Fair and Privacy-Aware Transfer Learning for Educational Predictive modeling: A Case Study on Retention Prediction in Community Colleges 25

Towards Fair and Privacy-Aware Transfer Learning for Educati...

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15th international conference on Learning Analytics and Knowledge

作者： Yao, Chengyuan Cortez, Carmen Yu, Renzhe Columbia Univ Teachers Coll New York NY 10027 USA

ISBN: (纸本)9798400707018

Predictive analytics is a widely used application of learning analytics, but many resource-constrained institutions lack the capacity to develop their own predictive models or rely on proprietary models trained in different contexts with little transparency. In this context, transfer learning holds promise for expanding reliable and equitable access to predictive analytics, but this potential remains underexplored given existing legal and technical constraints. In this paper, we examine transfer learning strategies in the context of retention prediction at two-year community colleges in the United States, which enroll the most postsecondary students from underserved communities with higher dropout rates than selective universities. We envision a scenario where community colleges can collaborate with each other and with four-year universities to develop retention prediction models under privacy constraints, and evaluate the risks and potential improvement strategies of cross-institutional model transfer for different stakeholders. using detailed administrative records from 4 research universities and 23 community colleges, which cover more than 800,000 students across 7 cohorts, we first identify performance and fairness degradation when source (external) models are deployed at a target institution without any localization. Fortunately, publicly available institution-level contextual information can be used to forecast these performance drops and offer early guidance for model portability. For model developers under data privacy regulations, sequential training that selects training institutions based on demographic similarities proves useful for enhancing the general fairness of resulting models without compromising performance. For target institutions without local data to fine-tune source models, we find that customizing evaluation thresholds for different sensitive groups is more successful than established transfer learning techniques at improving performance an

关键词： Predictive Analytics Transfer Learning Algorithmic Fairness Privacy Intersectionality College Retention Community Colleges Higher Education

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Groundwater Level modeling Artificial Intelligence Approach of Features and Abilities

Groundwater Level Modeling Artificial Intelligence Approach ...

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international conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： Girish Kalele Centre for Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

Creating precise soft computing techniques for estimating groundwater levels (GWL) to improve water resource scheduling and administration is crucial. Machine Learning (ML) algorithms have significantly improved GWL projection over the last twenty years. this research briefly summarizes the most widely used Artificial intelligence (AI) techniques and reviews the limited edition on AI approaches for groundwater level (GWL) modeling and estimation. Despite some flaws, the GWL temporal sequence in various groundwater can be effectively simulated and forecasted using AI methods if it is designed correctly. Examining these stages in the context of GWL modeling is advantageous due to the reliance of some phases of AI modeling on knowledge acquisition or iterative experimentation. the articles under review produced many limited and broad outcomes that can serve as valuable guidelines for scientists who wish to conduct comparative research in this area. this study also offers a few fresh concepts in the related field of inquiry for creating novel techniques and enhancing modeling quality.

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modeling information gathering for decisions in business processes 42

Modeling information gathering for decisions in business pro...

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42nd international conference on Conceptual modeling: ER Forum, 7th Symposium on Conceptual modeling Education, SCME 2023, Project Exhibitions, Posters and Demos, and Doctoral Consortium, ER-Companion 2023

作者： Eshuis, Rik Eindhoven University of Technology P.O. Box 513 5600 MB Netherlands

While process models typically contain decisions, the common view is that decision aspects of business processes are best modeled separately from the process behavior to achieve reuse and reduce complexity. To facilitate this, Decision Model and Notation (DMN) has been proposed as standard for modeling decision points in processes, complementing standards for process modeling such as Business Process Model and Notation (BPMN) and Case Management Model and Notation (CMMN). Decisions are taken based on input information elements, which are gathered in the process steps leading to a decision point corresponding to the decision. While research has been performed on integrated modeling of business processes and their decisions, there is less research on how to model information gathering for decisions in business processes. this paper discusses different strategies for information gathering for decisions in business processes, ranging from structured to flexible. Structured information gathering strategies can be encoded in process models, while flexible approaches compute efficient information gathering strategies based on decision support techniques. © 2023 CEUR-WS. All rights reserved.

关键词： Business Process modeling context Decision modeling Flexibility Knowledge-intensive Processes

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Towards a Mobile, Intelligent, Personalized and Adaptive E-learning System Considering Learners’ context in Semi-nomadic and Conflict Zones 7th

Towards a Mobile, Intelligent, Personalized and Adaptive E-l...

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7th EAI international conference on Innovations and interdisciplinary Solutions for Underserved Areas, InterSol 2024

作者： Maiga, Alhoudourou Almaimoune Hotte, Richard Camara, Gaoussou Abid, Mariem Masmoudi, Anis Université Alioune Diop Bambey Senegal Institut d’intelligence artificielle appliquée UniversitéTELUQ Québec Canada

ISBN: (纸本)9783031864926

According to the UNESCO (2023), the sub-Saharan Africa has the highest rate of out-of-school children for economic, cultural, socio-political and geopolitical reasons. Improving school attendance rates in such areas requires a preliminary study to understand the local realities and meet the expectations of learners and, above all, their parents, who have the power to decide whether or not to send them to school. In this paper, we study and design mobile-based, intelligent, personalized and adaptive e-learning solution in semi-nomadic and conflict zones. this solution is part of the AMI (Intelligence-Mediated Learning) project which aims to design, develop, and implement a mobile learning system made up of educational applications accessible from micro terminals (such as smartphones, tablets, and other devices). To properly assess the learning needs in such context, four field surveys were carried out in Kalani, a community in northern Mali, located in a conflict zone with a high rate of non-schooling and out-of-school children, where both sedentary and nomadic families live. these surveys made it possible to collect, analyze and process data of 100 Kalani children aged between 6 and 11, to build up a model that guide the implementation of our proposed educational solution. the data analysis revealed a strong link between the learners’ interests and the needs expressed by the community. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2025.

关键词： Teaching

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NXDG 2024 - Proceedings of the 1st NeXt-Generation Data Governance Workshop 2024, co-located with 20th international conference on Semantic Systems, SEMANTiCS 2024

NXDG 2024 - Proceedings of the 1st NeXt-Generation Data Gove...

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1st NeXt-Generation Data Governance Workshop, NXDG 2024

the proceedings contain 7 papers. the topics discussed include: towards cultivating decentralized data privacy, interoperability and trust with semantic PETs and visualizations;using ODRL to represent access rights to public records at the National Archives (UK);towards time privacy policies in ODRL;me want cookie! towards automated and transparent data governance on the web;defining a new perspective: enterprise information governance;mapping data governance requirements between the European Union's AI Act and ISO/IEC 5259: a semantic analysis;and initiating interdisciplinary research for future-proof data protection in the context of data spaces and semantic interoperable data sharing.

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modeling the Impact of the Quality of the Political and Economic Environment on Population Migration 7

Modeling the Impact of the Quality of the Political and Econ...

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7th international conference on Future Networks and Distributed Systems, ICFNDS 2023

作者： Zaitsev, Andrey Rodionov, Dmitriy Khudaykulov, Sadirdin Tuxliev, Bozor Stetsyunic, Yulia Konnikov, Evgenii Dmitriev, Nikolay Peter The Great St.Petersburg Polytechnic University Polytechnicheskaya 29 St.Petersburg195251 Russia Tashkent State University Of Economics Islam Karimov street 49 Tashkent100066 Uzbekistan Pushkin Leningrad State University St. Petersburg Russia

ISBN: (纸本)9798400709036

Migration is a significant socio-political indicator that is important to monitor and control whenever necessary, because migration can affect the social and economic situation in the country. this paper presents a study of the relationship between the level of migration and the quality of the political environment, which directly affects the state of sus-tainability of the country. the study includes several groups of countries: "established", "stable", and "at risk". the purpose of the study is to develop a model for managing the migration flow through managing the information en-vironment in order to improve the well-being and other socio-economic indicators. It also proposes to develop rec-ommendations on migration level control. the key component of the study is the analysis of the information envi-ronment that reflects political stability. As a result, we have identified a number of problems related to the impact of migration on the socio-economic indicators of countries, and determined the relationship between the level of migration and the news (mass media) background. On the basis of the obtained conclusions, new relations can be built in the context of this issue, and the study of impact of the quality of political environment on increasing migration can be continued. © 2023 ACM.

关键词： Population dynamics

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Probabilistic Fuzzy Frequent Item Sets Mining (PPFIM) 7

Probabilistic Fuzzy Frequent Item Sets Mining (PPFIM)

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7th international conference on Cloud Computing and Big Data Analytics, ICCCBDA 2022

作者： Li, Fayuan Zhang, Zeyuan Cheng, Bo Zhang, Peng Training Center for Engineering Practices Northwestern Polytechnical University Xi'an China School of Computer Science Northwestern Polytechnical University Xi'an China

ISBN: (纸本)9781665487115

the double superposition of fuzziness and randomness makes the mining of uncertain fuzzy item sets more complex. Based on the calculation of item set fuzziness, this paper integrates the randomness of possible world model to solve the problem of mining fuzzy frequent item sets based on probability threshold. Fuzzy theory and uncertainty are based on linguistic information and are extended to deal with partial truth concepts. In the fuzzy probabilistic context, an itemset X is called fuzzy frequent if the fuzzy probability that X occurs in at least minSup transactions is above a given threshold \tau. We designed a dynamic programming-based algorithm to compute the frequent fuzzy probability. Experiments were conducted to evaluate the performance of the proposed approach. © 2022 IEEE.

关键词： Cloud computing Uncertainty Itemsets Databases Heuristic algorithms Computational modeling Linguistics

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