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Technical debt and agile software development practices and processes: An industry practitioner survey

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arXiv 2021年

作者： Holvitie, Johannes Licorish, Sherlock A. Spínola, Rodrigo O. Hyrynsalmi, Sami MacDonell, Stephen G. Mendes, Thiago S. Buchan, Jim Leppänen, Ville Turku Centre for Computer Science Software Development Laboratory Turku Finland University of Turku Department of Information Technology Turku Finland University of Otago Department of Information Science Otago Dunedin New Zealand Salvador University Graduate Program in Systems and Computer Bahia Salvador Brazil Federal University of Bahia Fraunhofer Project Center for Software and System Engineering Salvador Brazil Tampere University of Technology Pori Campus Pori Finland Federal Institute of Bahia Information Technology Department Bahia Santo Amaro Brazil Auckland University of Technology School of Engineering Computer and Mathematical Sciences Auckland New Zealand

Context: Contemporary software development is typically conducted in dynamic, resource-scarce environments that are prone to the accumulation of technical debt. While this general phenomenon is acknowledged, what remains unknown is how technical debt specifically manifests in and affects software processes, and how the software development techniques employed accommodate or mitigate the presence of this debt. Objectives: We sought to draw on practitioner insights and experiences in order to classify the effects of agile method use on technical debt management, given the popularity and perceived success of agile methods. We explore the breadth of practitioners' knowledge about technical debt;how technical debt is manifested across the software process;and the perceived effects of common agile software development practices and processes on technical debt. In doing so, we address a research gap in technical debt knowledge and provide novel and actionable managerial recommendations. Method: We designed, tested and executed a multi-national survey questionnaire to address our objectives, receiving 184 responses from practitioners in Brazil, Finland, and New Zealand. Results: Our findings indicate that: 1) Practitioners are aware of technical debt, although, there was under utilization of the concept, 2) Technical debt commonly resides in legacy systems, however, concrete instances of technical debt are hard to conceptualize which makes it problematic to manage, 3) Queried agile practices and processes help to reduce technical debt;in particular, techniques that verify and maintain the structure and clarity of implemented artifacts (e.g., Coding standards and Refactoring) positively affect technical debt management. Conclusions: The fact that technical debt instances tend to have characteristics in common means that a systematic approach to its management is feasible. However, notwithstanding the positive effects of some agile practices on technical debt management, comp

关键词： Legacy systems

*** as digital platform for vegetation analysis and estimation of carbon stock in KEHATI aqua park

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AIP Conference Proceedings 2024年第1期3026卷

作者： Nanda Satya Nugraha Dian Pratama Putra Mohammad Prasanto Bimantio Amallia Ferhat Rama Zakaria Rudi Nirwantono Teddy Suparyanto Bens Pardamean Faculty of Forestry Institute of Agriculture STIPER Yogyakarta Indonesia 55282 Faculty of Agriculture Institute of Agriculture STIPER Yogyakarta Indonesia 55282 Faculty of Agricultural Technology Institute of Agriculture STIPER Yogyakarta Indonesia 55282 PT. Tirta Investama Pabrik Klaten Klaten Central Java Indonesia 57474 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 1148 Biotechnology Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

KEHATI AQUA Park is one of the green areas managed by PT. Tirta Investama Klaten (Klaten Factory). This area is located in Wangen and Ponggok Villages, Polanharjo District, Klaten Regency, Central Java, and is an integral part of the company’s seriousness in carbon reduction movement. When maintenance of the area is important for the sustainability of the park, there is however no data on the trees inventory in the area. Therefore, this study aims to invent the trees at KEHATI AQUA Park and evaluate the potential of the area to become a carbon sink using *** application. This study was conducted at the KEHATI AQUA Park. The census method was performed to collect tree data, and the result was recorded in *** application. The carbon stock calculation was estimated using the application according to the tree data submitted in the application. The study included a total of 1048 plantation spots in 51 tree species. From those numbers, about 738 trees existed, and the remaining spots were blank spaces. Based on the condition of the trees, those were 660 good trees, 17 dry trees, and 61 under pest infection. The carbon stock estimation at KEHATI AQUA Park Klaten in the next five years (2026) is around 40 tons of carbon. Therefore, it can be concluded that the park is valuable as an area to preserve biodiversity and as a carbon sink.

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Landau Polaritons in a Full-Dielectric Three-Dimensional Photonic-Crystal Cavity

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Landau Polaritons in a Full-Dielectric Three-Dimensional Pho...

Conference on Lasers and Electro-Optics (CLEO)

作者： Fuyang Tay Ali Mojibpour Shuang Liang Andrey Baydin Arash Ahmadivand Nicolas Marquez Peraca Hongjing Xu Geoff C. Gardner Michael J. Manfra David Hagenmüller Junichiro Kono Department of Electrical and Computer Engineering Rice University Houston Texas USA Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston Texas USA Department of Physics and Astronomy Purdue University West Lafayette IN USA Birck Nanotechnology Center Purdue University West Lafayette IN USA Smalley-Curl Institute Rice University Houston Texas USA Department of Physics and Astronomy Rice University Houston Texas USA Microsoft Quantum Purdue Purdue University West Lafayette IN USA School of Electrical and Computer Engineering Purdue University West Lafayette IN USA School of Materials Engineering Purdue University West Lafayette IN USA ISIS (UMR 7006) Université de Strasbourg and CNRS Strasbourg France Department of Materials Science and Nano Engineering Rice University Houston Texas USA

We fabricated a full-dielectric three-dimensional photonic-crystal cavity containing an ultrahigh-mobility two-dimensional electron gas. By applying a strong perpendicular magnetic field, we created Landau polaritons ... 详细信息

ISBN: (数字)9781957171050

ISBN: (纸本)9781665466660

关键词： Couplings HEMTs Laser modes Polaritons Magnetic fields Gas lasers MODFETs

Multimodal deep learning framework for image popularity prediction on social media

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arXiv 2021年

作者： Abousaleh, Fatma S. Cheng, Wen-Huang Yu, Neng-Hao Tsao, Yu Social Networks and Human-Centered Computing Program Taiwan International Graduate Program Institute of Information Science Research Center for Information Technology Innovation Academia Sinica Taipei11529 Taiwan Department of Computer Science National Chengchi University Taipei11605 Taiwan The Institute of Electronics Department of Electronics Engineering National Chiao Tung University Hsinchu30010 Taiwan The College of Design Department of Design National Taiwan University of Science and Technology Taipei10607 Taiwan The Research Center for Information Technology Innovation Academia Sinica Taipei11529 Taiwan

Billions of photos are uploaded to the web daily through various types of social networks. Some of these images receive millions of views and become popular, whereas others remain completely unnoticed. This raises the problem of predicting image popularity on social media. The popularity of an image can be affected by several factors, such as visual content, aesthetic quality, user, post metadata, and time. Thus, considering all these factors is essential for accurately predicting image popularity. In addition, the efficiency of the predictive model also plays a crucial role. In this study, motivated by multimodal learning, which uses information from various modalities, and the current success of convolutional neural networks (CNNs) in various fields, we propose a deep learning model, called visual-social convolutional neural network (VSCNN), which predicts the popularity of a posted image by incorporating various types of visual and social features into a unified network model. VSCNN first learns to extract high-level representations from the input visual and social features by utilizing two individual CNNs. The outputs of these two networks are then fused into a joint network to estimate the popularity score in the output layer. We assess the performance of the proposed method by conducting extensive experiments on a dataset of approximately 432K images posted on Flickr. The simulation results demonstrate that the proposed VSCNN model significantly outperforms state-of-the-art models, with a relative improvement of greater than 2.33%, 7.59%, and 14.16% in terms of Spearman’s Rho, mean absolute error, and mean squared error, respectively. Copyright © 2021, The Authors. All rights reserved.

关键词： Social networking (online)

Magnetically Tuned Continuous Transition from Weak to Strong Coupling in Terahertz Magnon Polaritons

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arXiv 2022年

作者： Baydin, Andrey Hayashida, Kenji Makihara, Takuma Tay, Fuyang Ma, Xiaoxuan Ren, Wei Ma, Guohong Noe, G. Timothy Katayama, Ikufumi Takeda, Jun Nojiri, Hiroyuki Cao, Shixun Bamba, Motoaki Kono, Junichiro Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States The Smalley-Curl Institute Rice University HoustonTX77005 United States Division of Applied Physics Graduate School of Engineering Hokkaido University Hokkaido Sapporo060-8628 Japan Department of Physics and Astronomy Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Department of Physics International Center of Quantum and Molecular Structures Materials Genome Institute Shanghai University Shanghai200444 China Department of Physics Graduate School of Engineering Science Yokohama National University Yokohama240-8501 Japan Institute for Materials Research Tohoku University Sendai980-8577 Japan The Hakubi Center for Advanced Research Kyoto University Kyoto606-8502 Japan Department of Physics I Kyoto University Kyoto606-8502 Japan PRESTO Japan Science and Technology Agency Kawaguchi332-0012 Japan Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States

Depending on the relative rates of coupling and dissipation, a light-matter coupled system is either in the weak- or strong-coupling regime. Here, we present a unique system where the coupling rate continuously increases with an externally applied magnetic field while the dissipation rate remains constant, allowing us to monitor a weak-to-strong coupling transition as a function of magnetic field. We observed a Rabi splitting of a terahertz magnon mode in yttrium orthoferrite above a threshold magnetic field of ∼14 T. Based on a microscopic theoretical model, we show that with increasing magnetic field the magnons transition into magnon polaritons through an exceptional point, which will open up new opportunities for in situ control of non-Hermitian systems. Copyright © 2022, The Authors. All rights reserved.

关键词： Polariton

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Sharma et al. Reply:

Physical Review Letters 2022年第21期128卷 219602-219602页

作者： Keshav Sharma Nathalia L. Costa Yoong Ahm Kim Hiroyuki Muramatsu Newton M. Barbosa Neto Luiz G. P. Martins Jing Kong Alexandre Rocha Paschoal Paulo T. Araujo Department of Physics and Astronomy University of Alabama Tuscaloosa 35487 Alabama USA Department of Physics Federal University of Ceara Fortaleza 60455-760 Ceara Brazil Department of Polymer Engineering School of Polymer Science and Engineering and Alan G. MacDiarmid Energy Research Institute Chonnam National University 77 Yongbong-ro Buk-gu Gwangju 61186 Republic of Korea Research Institute for Supra-Materials Shinshu University 4-17-1 Wakasato 380-8553 Nagano Japan Institute of Natural Sciences Graduate Program in Physics Federal University of Para Belem 66075-110 Brazil Department of Physics Massachusetts Institute of Technology Cambridge 02139 Massachusetts USA Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge 02139 Massachusetts USA

An artificial intelligence method for vessel detection in images of cardiac catheterization

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Informatics in Medicine Unlocked 2023年 39卷

作者： Chien, Ting-Ying Ting, Hsien-Wei Li, Hao-Wei Chang, Hsiao-Huang Department of Computer Science and Engineering Yuan Ze University 320 Taoyuan City Taiwan Graduate Program in Biomedical Informatics Yuan Ze University 320 Taoyuan City Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University 320 Taoyuan City Taiwan Department of Neurosurgery Taipei Hospital Ministry of Health and Welfare 242 New Taipei City Taiwan Division of Cardiovascular Surgery Department of Surgery Taipei Veterans General Hospital Taipei 11217 Taiwan Department of Surgery School of Medicine College of Medicine Taipei Medical University Taipei 11031 Taiwan

Coronary artery disease (CAD) is one of the top ten leading causes of death in countries worldwide. There are several methods used by physicians to diagnose CAD. One common method is the use of X-ray angiogram (XRA) images. When employing a computer-aided automatic analysis method to locate blood vessels in XRA images, problems such as complex background noise, low contrast, and difficulty in separating blood vessels from the background are encountered, especially for blood vessels with a low contrast to the background noise. In this study, we used various image preprocessing methods to highlight blood vessels from complex backgrounds and different types of blood vessel, followed by the employment of four superpixel segmentation methods to partition an image into multiple segments, and finally the utilization of Weighted Voting to determine the best superpixel algorithm. A genetic algorithm was used to identify the best weights by which to determine the locations of blood vessels in images of cardiac catheterization. Our proposed method achieved an average F1-score of 73.4% in the analysis of five patients, which was better than the other superpixel algorithms tested. The results of this research will be helpful for future SYNTAX score analysis. © 2023

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Scalable Metagrating for Efficient Ultrasonic Focusing

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Physical Review Applied 2021年第6期16卷 064014-064014页

作者： Yan Kei Chiang Li Quan Yugui Peng Shahrokh Sepehrirahnama Sebastian Oberst Andrea Alù David A. Powell School of Engineering and Information Technology University of New South Wales Canberra ACT 2610 Australia Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 USA Photonics Initiative Advanced Science Research Center City University of New York New York New York 10031 USA Centre for Audio Acoustics and Vibration University of Technology Sydney Broadway NSW 2007 Australia Physics Program Graduate Center City University of New York New York New York 10016 USA

Acoustic metalenses have been pursued over the past decades due to their pivotal role in a wide variety of applications. Recent research efforts have demonstrated that, at ultrasonic regimes, acoustic levitation can be realized with standing waves, which are created by the interference between incoming and reflected focused waves. However, the conventional gradient-metasurface approach to focus ultrasonic waves is complex, leading to poor scalability. In this work, we propose a design principle for ultrasonic metalenses, based on metagratings—arrays of discrete scatters with coarser features than gradient metasurfaces. We achieve beam focusing by locally controlling the excitation of a single diffraction order with the use of metagratings, with geometry adiabatically varying over the lens aperture. We show that our metalens can effectively focus impinging ultrasonic waves to a focal point with a full width at half maximum of 0.364 of the wavelength. The focusing performance of the metalens is demonstrated experimentally, validating our proposed approach. This metagrating approach to focusing can be adopted for different operating frequencies by scaling the size of the structure, which has coarse features suitable for high-frequency designs, with potential applications ranging from biomedical science to nondestructive testing.

关键词： Acoustic measurements Acoustic metamaterials Acoustic modeling Acoustic wave phenomena Beam optics Ultrasonics Bloch-Floquet theorem Ultrasound techniques

Multimodal Whole Slide Foundation Model for Pathology

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arXiv 2024年

作者： Ding, Tong Wagner, Sophia J. Song, Andrew H. Chen, Richard J. Lu, Ming Y. Zhang, Andrew Vaidya, Anurag J. Jaume, Guillaume Shaban, Muhammad Kim, Ahrong Williamson, Drew F.K. Chen, Bowen Almagro-Perez, Cristina Doucet, Paul Sahai, Sharifa Chen, Chengkuan Komura, Daisuke Kawabe, Akihiro Ishikawa, Shumpei Gerber, Georg Peng, Tingying Le, Long Phi Mahmood, Faisal Department of Pathology Mass General Brigham Harvard Medical School BostonMA United States Data Science Program Dana-Farber Cancer Institute BostonMA United States Cancer Program Broad Institute of Harvard and MIT CambridgeMA United States John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA United States Helmholtz Munich German Research Center for Environment and Health Munich Germany School of Computation Information and Technology Technical University of Munich Munich Germany Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States Harvard-MIT Division of Health Sciences and Technology Massachusetts Institute of Technology CambridgeMA United States Department of Pathology Pusan National University Busan Korea Republic of Department of Pathology and Laboratory Medicine Emory University School of Medicine AtlantaGA United States Harvard Data Science Initiative Harvard University CambridgeMA United States Department of Systems Biology Harvard Medical School BostonMA United States Department of Preventive Medicine Graduate School of Medicine The University of Tokyo Tokyo Japan Division of Pathology National Cancer Center Exploratory Oncology Research & Clinical Trial Center Chiba Japan

The field of computational pathology has been transformed with recent advances in foundation models that encode histopathology region-of-interests (ROIs) into versatile and transferable feature representations via self-supervised learning (SSL). However, translating these advancements to address complex clinical challenges at the patient and slide level remains constrained by limited clinical data in disease-specific cohorts, especially for rare clinical conditions. We propose TITAN, a multimodal whole slide foundation model pretrained using 335,645 WSIs via visual self-supervised learning and vision-language alignment with corresponding pathology reports and 423,122 synthetic captions generated from a multimodal generative AI copilot for pathology. Without any finetuning or requiring clinical labels, TITAN can extract general-purpose slide representations and generate pathology reports that generalize to resource-limited clinical scenarios such as rare disease retrieval and cancer prognosis. We evaluate TITAN on diverse clinical tasks and find that TITAN outperforms both ROI and slide foundation models across machine learning settings such as linear probing, few-shot and zero-shot classification, rare cancer retrieval and cross-modal retrieval, and pathology report generation. The model is publicly accessible at https://***/mahmoodlab/TITAN © 2024, CC BY-NC-ND.

关键词： Self-supervised learning