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23rd Iberoamerican Conference on Software engineering, CIbSE 2020

作者： de Souza Doreste, Andréa Cristina Travassos, Guilherme Horta Systems Engineering and Computer Science Program COPPE Federal University of Rio de Janeiro Brazil

In Software engineering, context can be understood as the overall set of information used to characterize the situation of an entity. A software system is context-aware if it uses the context to provide relevant information or services to the user. Nowadays, different types of software systems with a profound impact on the user's life can be considered context-aware (e.g., ubiquitous and Internet of Things software systems). Therefore, it is crucial to guarantee that they behave correctly. Software Testing is the primary process for verifying system behavior. Because of the particularities of Context-Aware Software Systems (CASS), conventional testing methods are not enough to test such systems. Based on that, we propose CATS#, a technique to support software engineers with the specification of CASS test cases and capture not only the context itself but its variation as well. CATS# is an evolution of the CATS (Context-Aware Test Suite) Design technique. It introduces two relevant evolutions: test case models and a new test template. The test case models were proposed after we searched for context-aware applications through the literature and realized that the context could affect the test process in different manners. The test template was proposed to capture the variation of context by specifying which variation should occur during the test case and when it should occur. We selected one example application to apply our technique, deriving different types of test cases and showing its relevance in these initial steps. © CIbSE 2020.

关键词： Software testing

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Jointprop: Joint Semi-supervised Learning for Entity and Relation Extraction with Heterogeneous Graph-based Propagation 61

Jointprop: Joint Semi-supervised Learning for Entity and Rel...

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61st Annual Meeting of the Association for Computational Linguistics, ACL 2023

作者： Yandan, Zheng Anran, Hao Tuan, Luu Anh School of Computer Science and Engineering Interdisciplinary Graduate Program-HealthTech Nanyang Technological University Singapore

ISBN: (纸本)9781959429722

Semi-supervised learning has been an important approach to address challenges in extracting entities and relations from limited data. However, current semi-supervised works handle the two tasks (i.e., Named Entity Recognition and Relation Extraction) separately and ignore the cross-correlation of entity and relation instances as well as the existence of similar instances across unlabeled data. To alleviate the issues, we propose Jointprop, a Heterogeneous Graph-based Propagation framework for joint semi-supervised entity and relation extraction, which captures the global structure information between individual tasks and exploits interactions within unlabeled data. Specifically, we construct a unified span-based heterogeneous graph from entity and relation candidates and propagate class labels based on confidence scores. We then employ a propagation learning scheme to leverage the affinities between labelled and unlabeled samples. Experiments on benchmark datasets show that our framework outperforms the state-of-the-art semi-supervised approaches on NER and RE tasks. We show that the joint semi-supervised learning of the two tasks benefits from their codependency and validates the importance of utilizing the shared information between unlabeled data. © 2023 Association for Computational Linguistics.

关键词： Extraction

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A linear time algorithm for pricing european sequential barrier options

A linear time algorithm for pricing european sequential barr...

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13th Computing: The Australasian Theory Symposium, CATS2007

作者： Gao, Peng van der Meyden, Ron School of Computer Science and Engineering UNSW and Formal Methods Program National ICT Australia Australia

ISBN: (纸本)1920682465

Financial derivatives are contracts concerning rights and obligations to engage in future transactions on some underlying financial instrument. A major con-cern in financial markets is to compute an expected value of such contracts as a basis for trading decisions. The Cox, Ross and Rubinstein (CRR) binomial tree model is a popular discrete approach to such compu-tations, which requires time quadratic in the number of discrete temporal steps to contract termination. Lyuu has shown that barrier options can be valued with respect to the CRR model in linear time, us-ing a combinatorial method. The paper develops a generalization of Lyuu's result, showing that a class of more complex options comprised of a sequence of barriers can be valued in linear time. © 2007, Australian computer Society, Inc.

关键词： Clustering algorithms

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A 3D Dual-band Electrically Small Monopole Antenna for Internet of Sea Applications

A 3D Dual-band Electrically Small Monopole Antenna for Inter...

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2021 IEEE International Symposium on Antennas and Propagation and North American Radio science Meeting, APS/URSI 2021

作者： Liao, Hanguang Bilal, Rana Muhammad Shamim, Atif Electrical and Computer Engineering Program King Abdullah University of Science and Technology Thuwal Saudi Arabia

ISBN: (纸本)9781728146706

Sensing and retrieving data from ocean to land are challenging and expensive tasks, while the Internet of Sea (IoS) concept can help to monitor ocean environment in a low-cost way. In this paper, an Electrically Small (ES) dual-band monopole antenna is proposed for the IoS application. Dual-band operation (GSM-900, LoRa, and BLE bands) and vertical polarization are maintained in a very compact size. The proposed antenna operates as a folded monopole antenna at 900MHz, and as a simple monopole antenna at 2.4 GHz, by combining the top-loaded folded monopole antenna and the 2-layer monopole feeding structure. The proposed antenna has ka of 0.45 at the LB, with a decent polarization purity and radiation efficiency of 54%. The proposed antenna is designed with a low-cost additive manufacturing material system. © 2021 IEEE.

关键词： Monopole antennas

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Biomedical data and AI

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science China Life sciences 2025年第5期68卷 1536-1540页

作者： Hao Xu Shibo Zhou Zefeng Zhu Vincenzo Vitelli Liangyi Chen Ziwei Dai Ning Yang Luhua Lai Shengyong Yang Sergey Ovchinnikov Zhuoran Qiao Sirui Liu Chen Song Jianfeng Pei Han Wen Jianfeng Feng Yaoyao Zhang Zhengwei Xie Yang-Yu Liu Zhiyuan Li Fulai Jin Hao Li Mohammad Lotfollahi Xuegong Zhang Ge Yang Shihua Zhang Ge Gao Pulin Li Qi Liu Jing-Dong Jackie Han Peking-Tsinghua Center for Life Sciences (CLS) Academy for Advanced Interdisciplinary StudiesPeking University Center for Quantitative Biology (CQB) Academy for Advanced Interdisciplinary StudiesPeking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program Academy for Advanced Interdisciplinary StudiesPeking University Department of Physics University of Chicago School of Life Sciences Southern University of Science and Technology Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies College of Chemistry and Molecular Engineering Peking University Department of Biotherapy Cancer Center and State Key Laboratory of BiotherapyWest China HospitalSichuan University Department of Biology Massachusetts Institute of Technology Lambic Therapeutics Inc. Changping Laboratory Al for Science Institute Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University Department of Obstetrics and Gynecology West China Second University HospitalSichuan University Peking University International Cancer Institute and Peking University-Yunnan Baiyao International Medical Institute and State Key Laboratory of Natural and Biomimetic Drugs Department of Molecular and Cellular PharmacologySchool of Pharmaceutical SciencesPeking University Health Science CenterPeking University Channing Division of Network Medicine Department of MedicineBrigham and Women's Hospital and Harvard Medical School Center for Artificial Intelligence and Modeling the Carl R.Woese Institute for Genomic BiologyUniversity of Illinois Urbana-Champaign Department of Genetics and Genome Sciences School of Medicine and Department of Computer and Data Sciences and Department of Population and Quantitative Health SciencesCase Western Reserve University Department of Biochemistry and Biophysics University of California Sanger Institute Department of Automation Tsinghua University State Key Laboratory of Multimodal Artificial Intelligence Systems I

The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries, the boundaries of both are constantly expanding, and their connections are becoming closer.

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Optimal Placement of Software Monitors Aiding Systematic Testing

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IEEE Transactions on Software engineering 1975年第4期SE-1卷 403-411页

作者： Ramamoorthy, C.V. Kim, K.H. Chen, W.T. Computer Science Division Department of Electrical Engineering and Computer Sciences University of California Berkeley Calif 94720 United States Department of Electrical Engineering Systems and Computer Science Program University of Southern California Los Angeles Calif. United States

The usefulness of software monitors in testing large ‘programs is discussed. Several types of testing strategies based on the use of monitors are surveyed. Since there is a computational overhead involved in employing monitors, attempts are made to minimize the number of monitors employed. This optimization problem is formulated and analyzed in graph-theoretic terms. Implementation aspects are considered through both discussion and examples. Copyright © 1975 by The Institute of Electrical and Electronics Engineers, Inc.

关键词： Optimal placement overhead program testing software monitor test-input test-output test-path test-run

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Compact Model Build Upon Dynamic Weighting Artificial Neural Network Approach for Complementary Field Effect Transistors

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IEEE Transactions on Electron Devices 2024年第1期71卷 246-253页

作者： Butola, Rajat Li, Yiming Kola, Sekhar Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation The Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program The Institute of Communications Engineering the Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan

In this work, a dynamic weighting-artificial neural network (DW-ANN) methodology is presented for quick and automated compact model (CM) generation. It takes advantage of both TCAD simulations for high accuracy and SPICE simulations for cost-effectiveness. This methodology is developed for gate-all-around (GAA) silicon (Si) nanosheet (NS) complementary field effect transistor (CFET), a potential candidate for future CMOS technology due to its innate properties. The critical process variation (PV) sources that severely degrade the CFET performance are estimated using DW-ANN. It reduces the computation cost and predicts the effects of PV sources with less than 1% error. Furthermore, a compact DW-ANN-based Verilog-A model has been developed that captures the dc as well as transient behavior accurately for circuit-level analysis. CFET-based circuits such as inverter, 6T-static random access memory (SRAM), and ring oscillator (RO) are characterized and implemented using DW-ANN-based CM. The overall average error of the model is reported as less than 2%. Therefore, the proposed device and circuit modeling approach provides a feasible solution for the rapid compact modeling of new emerging devices with good convergence and high accuracy. © 1963-2012 IEEE.

关键词： Neural networks

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Enhancing safety with an AI-empowered assessment and monitoring system for BSL-3 facilities

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Heliyon 2025年第1期11卷 e40855页

作者： Fan, Yi-Ling Hsu, Ching-Han Wu, Ju-Yu Tsai, Ying-Ying Chen, Wei J. Lee, Min-Shi Hsu, Fang-Rong Liao, Lun-De Institute of Biomedical Engineering and Nanomedicine National Health Research Institutes 35 Keyan Road Miaoli County Zhunan Town 350 Taiwan Department of Biomedical Engineering & Environmental Sciences National Tsing-Hua University Hsinchu Taiwan Doctoral Program in Tissue Engineering and Regenerative Medicine National Chung Hsing University Taichung Taiwan Center for Neuropsychiatric Research National Health Research Institutes 35 Keyan Road Miaoli County Zhunan Town 350 Taiwan National Institute of Infectious Diseases and Vaccinology National Health Research Institutes 35 Keyan Road Miaoli County Zhunan Town 350 Taiwan Department of Information Engineering and Computer Science Feng Chia University Taichung 407 Taiwan

Introduction: The COVID-19 pandemic has created an urgent demand for research, which has spurred the development of enhanced biosafety protocols in biosafety level (BSL)-3 laboratories to safeguard against the risks associated with handling highly contagious pathogens. Laboratory management failures can pose significant hazards. Methods: An external system captured images of personnel entering a laboratory, which were then analyzed by an AI-based system to verify their compliance with personal protective equipment (PPE) regulations, thereby introducing an additional layer of protection. A deep learning model was trained to detect the presence of essential PPE items, such as clothing, masks, hoods, double-layer gloves, shoe covers, and respirators, ensuring adherence to World Health Organization (WHO) standards. The internal laboratory management system used a deep learning model to delineate alert zones and monitor compliance with the imposed safety protocols. Results: The external detection system was trained on a dataset consisting of 4112 images divided into 15 PPE compliance classes. The model achieved an accuracy of 97.52 % and a recall of 97.03 %. The identification results were presented in real time via a visual interface and simultaneously stored on the administrator's dashboard for future reference. We trained the internal management system on 3347 images, achieving 90 % accuracy and 85 % recall. The results were transmitted in JSON format to the internal monitoring system, which triggered alerts in response to violations of safe practices or alert zones. Real-time notifications were sent to the administrators when the safety thresholds were met. Conclusion: The BSL-3 laboratory monitoring system significantly reduces the risk of exposure to pathogens for personnel during laboratory operations. By ensuring the correct use of PPE and enhancing adherence to the imposed safety protocols, this system contributes to maintaining the integrity of BSL-3 facilities

关键词： Bioengineering Biomedical instrumentation Biomedical laboratory safety Biosafety level-3 laboratory

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Uncovering response biases in recommendation 28

Uncovering response biases in recommendation

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28th AAAI Conference on Artificial Intelligence, AAAI 2014

作者： Park, Kyung-Wha Kim, Byoung-Hee Park, Tae-Suh Zhang, Byoung-Tak Department of Computer Science and Engineering 'Brain Science Program Seoul National University Seoul151-742 Korea Republic of

ISBN: (纸本)9781577356714

An user-specific tendency of biased movie rating is investigated, leading six identified types of rating pattern in a massive movie rating dataset. Based on the observed bias assumption, we propose a rescaling method of preferential scores by considering the rating types. Experimental results show significant enhancement for movie recommendation systems. © Copyright 2014, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Motion pictures

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Into 3D-Reconstructed Apparel over Virtual Try-On with Virtual Reality

Into 3D-Reconstructed Apparel over Virtual Try-On with Virtu...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Doungtap, Surasachai Petchhan, Jirayu Phanichraksaphong, Varinya Wang, Jenq-Haur International Graduate Program of Electrical Engineering and Computer Science Taiwan National Taiwan University of Science & Technology Dept. of Electrical Engineering Taiwan National Taipei University of Technology Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9798350324174

Virtualization technologies are still growing bigger and faster. Despite the greatness of its advancement, the costume industry is still very accessible when it comes to real trials. Off-the-shelf stuff are inadequate details for the desired individual to assess its in-depth utility for each garment trying on for a second, including custom stuff are much harder to try out right away. To this end, 2D image-based 3D reconstruction inclusive of touchable-virtualized space is accessible easier to stuff details for mans' decision making in purchasing. We establish the overall end-to-end pipeline from reconstruction until visualization for one instance to be triable on its stuff for a moment. As an expectation, our proposed approach can bring objects into the experimental area and use them immediately without any obstacle. © 2023 IEEE.

关键词： Virtual reality

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