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Lapinskas, Remigijus. "sites.google.com/view/Lapinskas – Mathematical readings." Lietuvos matematikos rinkinys 64 (November 20, 2023): 48–49. http://dx.doi.org/10.15388/lmd.2023.33595.
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This article is about the author's online book "Mathematical Readings" [2]. The book presents the high school math course in a slightly different way than conventional textbooks, the work focuses less on routine problems and tries to examine mathematical concepts in a broader context. The book makes frequent use of mobile math apps and the R program, and links to online sources are often provided. The text may be useful for self-study and math circles.
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De Fino, Melissa. "COOPERATIVE CATALOGING RULES http://sites.google.com/site/opencatalogingrules/." Technical Services Quarterly 27, no. 3 (May 28, 2010): 317–18. http://dx.doi.org/10.1080/07317131003769433.
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Bongiorno, Enea G., Alessandra Micheletti, Giovanni Naldi, and Davide La Torre. "SHAPE AND SIZE IN MEDICINE, BIOTECHNOLOGY, MATERIALS SCIENCE AND SOCIAL SCIENCES." Image Analysis & Stereology 30, no. 3 (November 1, 2011): 133. http://dx.doi.org/10.5566/ias.v30.p133-134.
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This special issue gathers together papers presented during the workshop Shape and Size in Medicine, Biotechnology, Materials Science and Social Sciences, Milano, Italy, 16-17 February 2011, https://sites.google.com/site/shapemilan/home
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Bibee, Abigail. "Resource Description and Access Happy Fun Time Companion http://sites.google.com/site/codlinandshort/." Technical Services Quarterly 28, no. 3 (May 19, 2011): 367–68. http://dx.doi.org/10.1080/07317131.2011.574549.
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Putri, Evi Ananda, Yulia Linguistika, and Siti Mas'ula. "PENGEMBANGAN MEDIA KARTU SOAL MATEMATIKA BERBASIS GOOGLE SITES MATERI KPK DAN FPB PADA SISWA KELAS IV SEKOLAH DASAR." Sekolah Dasar: Kajian Teori dan Praktik Pendidikan 31, no. 2 (November 30, 2022): 87. http://dx.doi.org/10.17977/um009v31i22022p087.
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This development research aims to produce question card media based on google sites material for LCM and GCF grade IV Elementary Schools that are valid and interesting for students. The research model uses the ADDIE model with five stages of development including: (1) analysis, (2) design, (3) development, (4) implementation, and (5) evaluation. The product is a website link (https://sites.google.com/view/media-mathion-card/page-muka) which is online. Based on the validation results, the percentage of material experts is 85 percent (valid), the percentage of media experts is 96.67 percent (very valid), the percentage of teachers is 91.67 percent (very valid), and the student attractiveness test results are 93 percent (very good). So it was concluded that the mathion card media product was valid according to the experts and interesting for fourth grade students.Penelitian pengembangan ini bertujuan untuk menghasilkan media kartu soal berbasis google sites materi KPK dan FPB kelas IV Sekolah Dasar yang valid dan menarik bagi siswa. Model penelitian menggunakan model ADDIE dengan lima tahap pengembangan meliputi: (1) analisis, (2) desain, (3) pengembangan, (4) implementasi, dan (5) evaluasi. Produk berupa link website (https://sites.google.com/view/media-mathion-card/halaman-muka) yang secara online. Berdasarkan hasil validasi, persentase ahli materi 85 persen (valid), persentase ahli media 96,67 persen (sangat valid), persentase guru 91,67 persen (sangat valid), dan hasil uji kemenarikan siswa sebesar 93 persen (sangat baik). Sehingga disimpulkan bahwa produk media mathion card valid menurut para ahli serta menarik bagi siswa kelas IV.
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Sitarz, Sebastian, and Krzysztof Botor. "MOLPTOL - a software package for sensitivityanalysis in MOLP." Multiple Criteria Decision Making 16 (2021): 140–52. http://dx.doi.org/10.22367/mcdm.2021.16.08.
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The paper introduces a new software package, MOLPTOL, for sensitivity analysis in multi-objective linear programming. In this application, which is available for free of charge on the web page (https:// sites.google.com/view/molptol), the tolerance approach as a measure of sensitivity is used. The motivation for creating MOLPTOL is the lack of such tools to date. MOLPTOL is novel for multi-criteria decision-making methods based on sensitivity analysis. The paper presents some new computational methods for obtaining the supremal tolerances as well. Keywords: multi-objective linear programming, sensitivity analysis, computer software.
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Pont, Frédéric, Marie Tosolini, and Jean J. Fournié. "Single-Cell Signature Explorer for comprehensive visualization of single cell signatures across scRNA-seq datasets." Nucleic Acids Research 47, no. 21 (July 11, 2019): e133-e133. http://dx.doi.org/10.1093/nar/gkz601.
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Abstract The momentum of scRNA-seq datasets prompts for simple and powerful tools exploring their meaningful signatures. Here we present Single-Cell_Signature_Explorer (https://sites.google.com/site/fredsoftwares/products/single-cell-signature-explorer), the first method for qualitative and high-throughput scoring of any gene set-based signature at the single cell level and its visualization using t-SNE or UMAP. By scanning datasets for single or combined signatures, it rapidly maps any multi-gene feature, exemplified here with signatures of cell lineages, biological hallmarks and metabolic pathways in large scRNAseq datasets of human PBMC, melanoma, lung cancer and adult testis.
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Alami, Z., L. Idelkheir, I. Zine-Eddine, El Atiqi, Y. Lmaalla, O. Aitbelassel, Laamrani a, and Y. Benchamkha. "PORTE FOLIO DES COMPETENCES PRATIQUES DU RESIDENT EN CHIRURGIE PLASTIQUE AU MAROC." International Journal of Advanced Research 12, no. 03 (March 31, 2024): 556–90. http://dx.doi.org/10.21474/ijar01/18427.
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In Morocco, plastic surgery is a comprehensive specialty that encompasses various domains. The training is lengthy and rigorous, involving residents in a extensive curriculum with both theoretical education and practical hospital training. The study aims to assess residents skills, define mastered procedures, and collect feedback to enhance the quality of education.A secondary objective is to create a portfolio using digital support: https://sites.google.com/view/comptencespratiqueduresident/accueil. To enable residents to track their progress and make informed decisions about their career in plastic surgery. We hope this educational tool will find its rightful place in the training of plastic surgery residents.
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Ghosh, Saptarshi, Kripabandhu Ghosh, Debasis Ganguly, Arnab Bhattacharya, Partha Pratim Chakrabarti, Shouvik Guha, Arindam Pal, et al. "Report on the 2nd Symposium on Artificial Intelligence and Law (SAIL) 2022." ACM SIGIR Forum 56, no. 1 (June 2022): 1–7. http://dx.doi.org/10.1145/3582524.3582538.
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This report describes the 2 nd edition of the Symposium on Artificial Intelligence and Law (SAIL) organized as a virtual event during June 6--9, 2022. The aim of SAIL is to bring together experts from the industry and the academia to discuss the scope and future of AI as applied to the legal domain. The symposium is also meant to foster collaborations between researchers of the following communities: Law, Artificial Intelligence, Data Mining, Information Retrieval, and Natural Language Processing. Eminent researchers working on AI and Law in both the academia and the industry were invited to deliver talks at this symposium. Date: 6--9 June, 2022. Website: https://sites.google.com/view/sail-2022/.
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Danese, Anthony. "A Gauss’s Law Computer Simulation in GlowScript." Physics Teacher 60, no. 5 (May 2022): 385–87. http://dx.doi.org/10.1119/10.0010396.
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In this paper I describe an interactive Gauss’s law computer simulation using the GlowScript programming environment. The simulation calculates a point charge’s electric field at locations on the surface of a Gaussian cube and displays the electric field in GlowScript’s 3D graphics window. The point charge can be moved, and the electric field visualization will update dynamically. Students can use the simulation controls to record the electric field strength and direction, and then copy and paste the data into a spreadsheet in order to calculate the electric flux through the cube. The simulation can be used as part of a quantitative virtual laboratory to develop a student’s intuition for electric flux and Gauss’s law. The simulation can be accessed at https://sites.google.com/view/gauss/home .
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Law, Wan Ching, Rachel McClanahan, and Penny C. Weismuller. "Depression Screening in the School Setting: Identification of the Depressed Adolescent." NASN School Nurse 32, no. 6 (October 17, 2017): 364–70. http://dx.doi.org/10.1177/1942602x17726095.
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Adolescent depression is a silent epidemic in this country. Untreated depression has detrimental effects on physical health, psychosocial well-being, and academic productivity. It is important for school nurses to be able to recognize depression and refer students promptly for treatment. This article and its associated learning module will provide school nurses with updated information on adolescent depression, discuss barriers in depression screening, use of the PHQ-9 (Patient Health Questionaire-9 Item) as an evidence-based depression screening tool in the educational setting, and the important role of school nurses in depression screening. It is anticipated that by increasing awareness and knowledge about adolescent depression and providing training in the use of an evidence-based screening tool, school nurses will have greater confidence in identifying and referring students in need. (A free online depression screening education module developed by the lead author is available at https://sites.google.com/view/depressionscreeningtraining .)
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Matsubara, Teppei, Tomoshiro Ochiai, Morihiro Hayashida, Tatsuya Akutsu, and Jose C. Nacher. "Convolutional neural network approach to lung cancer classification integrating protein interaction network and gene expression profiles." Journal of Bioinformatics and Computational Biology 17, no. 03 (June 2019): 1940007. http://dx.doi.org/10.1142/s0219720019400079.
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Deep learning technologies are permeating every field from image and speech recognition to computational and systems biology. However, the application of convolutional neural networks (CCNs) to “omics” data poses some difficulties, such as the processing of complex networks structures as well as its integration with transcriptome data. Here, we propose a CNN approach that combines spectral clustering information processing to classify lung cancer. The developed spectral-convolutional neural network based method achieves success in integrating protein interaction network data and gene expression profiles to classify lung cancer. The performed computational experiments suggest that in terms of accuracy the predictive performance of our proposed method was better than those of other machine learning methods such as SVM or Random Forest. Moreover, the computational results also indicate that the underlying protein network structure assists to enhance the predictions. Data and CNN code can be downloaded from the link: https://sites.google.com/site/nacherlab/analysis
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Son, Sanghyun, Yi-Ling Qiao, Jason Sewall, and Ming C. Lin. "Differentiable Hybrid Traffic Simulation." ACM Transactions on Graphics 41, no. 6 (November 30, 2022): 1–10. http://dx.doi.org/10.1145/3550454.3555492.
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We introduce a novel differentiable hybrid traffic simulator , which simulates traffic using a hybrid model of both macroscopic and microscopic models and can be directly integrated into a neural network for traffic control and flow optimization. This is the first differentiable traffic simulator for macroscopic and hybrid models that can compute gradients for traffic states across time steps and inhomogeneous lanes. To compute the gradient flow between two types of traffic models in a hybrid framework, we present a novel intermediate conversion component that bridges the lanes in a differentiable manner as well. We also show that we can use analytical gradients to accelerate the overall process and enhance scalability. Thanks to these gradients, our simulator can provide more efficient and scalable solutions for complex learning and control problems posed in traffic engineering than other existing algorithms. Refer to https://sites.google.com/umd.edu/diff-hybrid-traffic-sim for our project.
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Yarats, Denis, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau, and Rob Fergus. "Improving Sample Efficiency in Model-Free Reinforcement Learning from Images." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 12 (May 18, 2021): 10674–81. http://dx.doi.org/10.1609/aaai.v35i12.17276.
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Training an agent to solve control tasks directly from high-dimensional images with model-free reinforcement learning (RL) has proven difficult. A promising approach is to learn a latent representation together with the control policy. However, fitting a high-capacity encoder using a scarce reward signal is sample inefficient and leads to poor performance. Prior work has shown that auxiliary losses, such as image reconstruction, can aid efficient representation learning. However, incorporating reconstruction loss into an off-policy learning algorithm often leads to training instability. We explore the underlying reasons and identify variational autoencoders, used by previous investigations, as the cause of the divergence. Following these findings, we propose effective techniques to improve training stability. This results in a simple approach capable of matching state-of-the-art model-free and model-based algorithms on MuJoCo control tasks. Furthermore, our approach demonstrates robustness to observational noise, surpassing existing approaches in this setting. Code, results, and videos are anonymously available at https://sites.google.com/view/sac-ae/home.
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Yeh, Jia-Fong, Chi-Ming Chung, Hung-Ting Su, Yi-Ting Chen, and Winston H. Hsu. "Stage Conscious Attention Network (SCAN): A Demonstration-Conditioned Policy for Few-Shot Imitation." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 8 (June 28, 2022): 8866–73. http://dx.doi.org/10.1609/aaai.v36i8.20868.
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In few-shot imitation learning (FSIL), using behavioral cloning (BC) to solve unseen tasks with few expert demonstrations becomes a popular research direction. The following capabilities are essential in robotics applications: (1) Behaving in compound tasks that contain multiple stages. (2) Retrieving knowledge from few length-variant and misalignment demonstrations. (3) Learning from an expert different from the agent. No previous work can achieve these abilities at the same time. In this work, we conduct FSIL problem under the union of above settings and introduce a novel stage conscious attention network (SCAN) to retrieve knowledge from few demonstrations simultaneously. SCAN uses an attention module to identify each stage in length-variant demonstrations. Moreover, it is designed under demonstration-conditioned policy that learns the relationship between experts and agents. Experiment results show that SCAN can perform in complicated compound tasks without fine-tuning and provide the explainable visualization. Project page is at https://sites.google.com/view/scan-aaai2022.
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Isacchini, Giulio, Carlos Olivares, Armita Nourmohammad, Aleksandra M. Walczak, and Thierry Mora. "SOS: online probability estimation and generation of T-and B-cell receptors." Bioinformatics 36, no. 16 (June 17, 2020): 4510–12. http://dx.doi.org/10.1093/bioinformatics/btaa574.
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Abstract Summary Recent advances in modelling VDJ recombination and subsequent selection of T- and B-cell receptors provide useful tools to analyse and compare immune repertoires across time, individuals and tissues. A suite of tools—IGoR, OLGA and SONIA—have been publicly released to the community that allow for the inference of generative and selection models from high-throughput sequencing data. However, using these tools requires some scripting or command-line skills and familiarity with complex datasets. As a result, the application of the above models has not been available to a broad audience. In this application note, we fill this gap by presenting Simple OLGA & SONIA (SOS), a web-based interface where users with no coding skills can compute the generation and post-selection probabilities of their sequences, as well as generate batches of synthetic sequences. The application also functions on mobile phones. Availability and implementation SOS is freely available to use at sites.google.com/view/statbiophysens/sos with source code at github.com/statbiophys/sos.
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Pezatti, Erotilde Goreti, and Ana Carolina Teixeira Peres. "Os vários usos de "mesmo" no português brasieiro dos séculos XVIII, XIX e XX." Revista do GEL 19, no. 3 (August 2, 2023): 249–71. http://dx.doi.org/10.21165/gel.v19i3.3441.
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Este estudo investiga o uso de mesmo no português brasileiro, nos séculos XVIII, XIX e XX. A proposta consiste em verificar, na história recente do português, a persistência ou não da multifuncionalidade desse item. Para tanto, toma como universo de pesquisa cartas particulares e cartas oficiais extraídas do córpus do Projeto para a História do Português Brasileiro (https://sites.google.com/site/corporaphpb), e, como suporte teórico, a Gramática Discursivo-Funcional, desenvolvida por Hengeveld e Mackenzie (2008). Os resultados mostram que os cinco diferentes usos (operador de ênfase, função pragmática Contraste, operador de identidade idêntica, núcleo anafórico e modificador de propriedade configuracional), detectados por Peres (2020), já existiam desde o século XVIII e permaneceram no decorrer dos séculos XIX e XX. Além disso, não houve alteração substancial nos usos de mesmo e não sofreram alteração na forma de codificação no decorrer dos três séculos. O que este estudo revela é que alguns usos estão em decréscimo e outros em ascendência, apontando para um processo de gramaticalização.
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Tran, Huyen T. T., Nam Pham Ngoc, Tobias Hoßfeld, Michael Seufert, and Truong Cong Thang. "Cumulative Quality Modeling for HTTP Adaptive Streaming." ACM Transactions on Multimedia Computing, Communications, and Applications 17, no. 1 (April 16, 2021): 1–24. http://dx.doi.org/10.1145/3423421.
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HTTP Adaptive Streaming has become the de facto choice for multimedia delivery. However, the quality of adaptive video streaming may fluctuate strongly during a session due to throughput fluctuations. So, it is important to evaluate the quality of a streaming session over time. In this article, we propose a model to estimate the cumulative quality for HTTP Adaptive Streaming. In the model, a sliding window of video segments is employed as the basic building block. Through statistical analysis using a subjective dataset, we identify four important components of the cumulative quality model, namely the minimum window quality, the last window quality, the maximum window quality, and the average window quality. Experiment results show that the proposed model achieves high prediction performance and outperforms related quality models. In addition, another advantage of the proposed model is its simplicity and effectiveness for deployment in real-time estimation. Our subjective dataset as well as the source code of the proposed model have been made publicly available at https://sites.google.com/site/huyenthithanhtran1191/cqmdatabase .
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DIMA, CINDY CITYA. "Rancangan Konten Desa Wisata Kampoeng Dolanan Eyang R. Tjokrowihardjo pada Media Google Sites untuk Walitelon Utara Temanggung." Media Wisata 20, no. 1 (January 24, 2022): 71–77. http://dx.doi.org/10.36276/mws.v20i1.130.
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Design of tourism village content of Kampoeng Dolanan Eyang R. Tjokrowihardjo on google sites media for the north walitelon of Temanggung. The use of Google Sites can increase Pokdarwis competence and general public visits as digital literacy readers. Specific targets to be achieved are orderly administration for Pokdarwis workshops and at the same time as promotional media with google sites for the general public. The method used is a qualitative descriptive (phenomenon) because the Covid 19 pandemic phenomenon is still a scourge for tourism, especially tourist villages. This study uses data triangulation for data collection from the master trainer from the Ministry of Tourism and Creative Economy of the Republic of Indonesia during a visitation assessment of assistants from universities in the tourist village of Walitelon Utara, Temanggung in November 2020, observation of tourism village content on google sites, as well as surveys of potential users. This page and with data analysis techniques, namely editing in addition to the media, the content is also in line with the assistance of the Higher Education. The author gives the name "Desa Wisata Walitelon Utara" sites.google.com
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Tang, M. J., R. A. Cox, and M. Kalberer. "Compilation and evaluation of gas phase diffusion coefficients of reactive trace gases in the atmosphere: volume 1. Inorganic compounds." Atmospheric Chemistry and Physics 14, no. 17 (September 8, 2014): 9233–47. http://dx.doi.org/10.5194/acp-14-9233-2014.
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Abstract. Diffusion of gas molecules to the surface is the first step for all gas–surface reactions. Gas phase diffusion can influence and sometimes even limit the overall rates of these reactions; however, there is no database of the gas phase diffusion coefficients of atmospheric reactive trace gases. Here we compile and evaluate, for the first time, the diffusivities (pressure-independent diffusion coefficients) of atmospheric inorganic reactive trace gases reported in the literature. The measured diffusivities are then compared with estimated values using a semi-empirical method developed by Fuller et al. (1966). The diffusivities estimated using Fuller's method are typically found to be in good agreement with the measured values within ±30%, and therefore Fuller's method can be used to estimate the diffusivities of trace gases for which experimental data are not available. The two experimental methods used in the atmospheric chemistry community to measure the gas phase diffusion coefficients are also discussed. A different version of this compilation/evaluation, which will be updated when new data become available, is uploaded online (https://sites.google.com/site/mingjintang/home/diffusion).
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Fan, Wan-Cyuan, Cheng-Fu Yang, Chiao-An Yang, and Yu-Chiang Frank Wang. "Target-Free Text-Guided Image Manipulation." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 1 (June 26, 2023): 588–96. http://dx.doi.org/10.1609/aaai.v37i1.25134.
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We tackle the problem of target-free text-guided image manipulation, which requires one to modify the input reference image based on the given text instruction, while no ground truth target image is observed during training. To address this challenging task, we propose a Cyclic-Manipulation GAN (cManiGAN) in this paper, which is able to realize where and how to edit the image regions of interest. Specifically, the image editor in cManiGAN learns to identify and complete the input image, while cross-modal interpreter and reasoner are deployed to verify the semantic correctness of the output image based on the input instruction. While the former utilizes factual/counterfactual description learning for authenticating the image semantics, the latter predicts the "undo" instruction and provides pixel-level supervision for the training of cManiGAN. With the above operational cycle-consistency, our cManiGAN can be trained in the above weakly supervised setting. We conduct extensive experiments on the datasets of CLEVR and COCO datasets, and the effectiveness and generalizability of our proposed method can be successfully verified. Project page: sites.google.com/view/wancyuanfan/projects/cmanigan.
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Li, Jing, Jing Xu, Fangwei Zhong, Xiangyu Kong, Yu Qiao, and Yizhou Wang. "Pose-Assisted Multi-Camera Collaboration for Active Object Tracking." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 01 (April 3, 2020): 759–66. http://dx.doi.org/10.1609/aaai.v34i01.5419.
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Active Object Tracking (AOT) is crucial to many vision-based applications, e.g., mobile robot, intelligent surveillance. However, there are a number of challenges when deploying active tracking in complex scenarios, e.g., target is frequently occluded by obstacles. In this paper, we extend the single-camera AOT to a multi-camera setting, where cameras tracking a target in a collaborative fashion. To achieve effective collaboration among cameras, we propose a novel Pose-Assisted Multi-Camera Collaboration System, which enables a camera to cooperate with the others by sharing camera poses for active object tracking. In the system, each camera is equipped with two controllers and a switcher: The vision-based controller tracks targets based on observed images. The pose-based controller moves the camera in accordance to the poses of the other cameras. At each step, the switcher decides which action to take from the two controllers according to the visibility of the target. The experimental results demonstrate that our system outperforms all the baselines and is capable of generalizing to unseen environments. The code and demo videos are available on our website https://sites.google.com/view/pose-assisted-collaboration.
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Andleeb, Saiqa, Wajid Arshad Abbasi, Rozina Ghulam Mustafa, Ghafoor ul Islam, Anum Naseer, Irsa Shafique, Asma Parween, et al. "ESIDE: A computationally intelligent method to identify earthworm species (E. fetida) from digital images: Application in taxonomy." PLOS ONE 16, no. 9 (September 16, 2021): e0255674. http://dx.doi.org/10.1371/journal.pone.0255674.
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Earthworms (Crassiclitellata) being ecosystem engineers significantly affect the physical, chemical, and biological properties of the soil by recycling organic material, increasing nutrient availability, and improving soil structure. The efficiency of earthworms in ecology varies along with species. Therefore, the role of taxonomy in earthworm study is significant. The taxonomy of earthworms cannot reliably be established through morphological characteristics because the small and simple body plan of the earthworm does not have anatomical complex and highly specialized structures. Recently, molecular techniques have been adopted to accurately classify the earthworm species but these techniques are time-consuming and costly. To combat this issue, in this study, we propose a machine learning-based earthworm species identification model that uses digital images of earthworms. We performed a stringent performance evaluation not only through 10-fold cross-validation and on an external validation dataset but also in real settings by involving an experienced taxonomist. In all the evaluation settings, our proposed model has given state-of-the-art performance and justified its use to aid earthworm taxonomy studies. We made this model openly accessible through a cloud-based webserver and python code available at https://sites.google.com/view/wajidarshad/software and https://github.com/wajidarshad/ESIDE.
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Ciung, Margaretha Vonita, Istiqomah Istiqomah, and Irham Taufiq. "Pengembangan Media Pembelajaran Matematika Berbasis Google Sites pada Materi Deret Aritmatika." CIRCLE : Jurnal Pendidikan Matematika 2, no. 01 (March 22, 2022): 41–50. http://dx.doi.org/10.28918/circle.v2i01.5100.
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Penelitian ini bertujuan untuk mengembangkan media pembelajaran berbasis google sites pada mata pelajaran matematika materi deret aritmatika untuk siswa SMA dan mengetahui kelayakan media berbasis google sites yang dikembangkan. Penelitian ini menggunakan metode R&D dengan model ADDIE yaitu Analysis, Design, Development, Implementation, and evaluation. Subjek penelitian ini adalah 27 siswa kelas XI di SMA Piri 1 Yogyakarta. Teknik pengumpulan data menggunakan angket validasi ahli dan angket respon siswa dengan melakukan uji coba lapangan terbatas. Teknik analisis data berupa analisis deskriptif kualitatif dan kuantitatif. Hasil penelitian adalah media pembelajaran matematika berbasis google sites materi deret aritmetika dengan alamat https://sites.google.com/view/deretaritmatika/home-math. Pengujian kelayakan menunjukkan media pembelajaran layak digunakan. Hal ini dibuktikan dengan hasil validasi ahli media memperoleh skor rata-rata 4,1 dengan kategori baik, sedangkan hasil validasi ahli materi memperoleh skor rata-rata 4,3 dengan kategori sangat baik dan hasil respon peserta didik memperoleh skor rata-rata 3,7 dengan kategori baik. Oleh karena itu, penelitian ini layak digunakan dengan menggunakan uji coba lapangan terbatas dan disarankan untuk melanjutkan penelitian pada uji coba lapangan utama dan memperluas penelitian dengan materi lainnya sehingga penggunaan google sites sebagai media pembelajaran semakin luas.
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Trippas, Johanne, David Maxwel, Abdulaziz Alqatan, Miriam Boom, Catherine Chavula, Anita Crescenzi, Luis-Daniel Ibáñez, et al. "Report on the 1st Early Career Researchers' Roundtable for Information Access Research (ECRs4IR 2022) at CHIIR 2022." ACM SIGIR Forum 56, no. 1 (June 2022): 1–10. http://dx.doi.org/10.1145/3582524.3582533.
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The First Early Career Researchers Roundtable for Information Access Research Workshop , in conjunction with the Seventh ACM Conference on Human Information Interaction and Retrieval (CHIIR) 2022, looked into the future of research, collaborations, and self-development to ask the following. Where are the opportunities for researchers in a (post-)pandemic environment, especially for Early Career Researchers (ECRs)? What do we need to do to get there? Which practical implementations can the broader CHIIR community support? The workshop started with an invited talk. Instead of conventional paper presentations, the attendees discussed the lessons learned from working in a pandemic. This report, co-authored by the workshop's organisers and its participants, summarises the discussion. This report aims to provide the broader CHIIR community with feedback on the workshop and foster ideas raised by ECRs to support ECRs. Two primary outcomes are (i) ECRs are often enthusiastic about taking on roles within a community, but formal validation and recognition are needed for their efforts and (ii) that the role of a conference needs to be reevaluated optimising the benefits of attending the event. Date: 14 March 2022. Website: https://sites.google.com/view/ecrs4ir/home.
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DeFazio, David, Yohei Hayamizu, and Shiqi Zhang. "Learning Quadruped Locomotion Policies Using Logical Rules." Proceedings of the International Conference on Automated Planning and Scheduling 34 (May 30, 2024): 142–50. http://dx.doi.org/10.1609/icaps.v34i1.31470.
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Quadruped animals are capable of exhibiting a diverse range of locomotion gaits. While progress has been made in demonstrating such gaits on robots, current methods rely on motion priors, dynamics models, or other forms of extensive manual efforts. People can use natural language to describe dance moves. Could one use a formal language to specify quadruped gaits? To this end, we aim to enable easy gait specification and efficient policy learning. Leveraging Reward Machines (RMs) for high-level gait specification over foot contacts, our approach is called RM-based Locomotion Learning (RMLL), and supports adjusting gait frequency at execution time. Gait specification is enabled through the use of a few logical rules per gait (e.g., alternate between moving front feet and back feet) and does not require labor-intensive motion priors. Experimental results in simulation highlight the diversity of learned gaits (including two novel gaits), their energy consumption and stability across different terrains, and the superior sample-efficiency when compared to baselines. We also demonstrate these learned policies with a real quadruped robot. Video and supplementary materials: https://sites.google.com/view/rm-locomotion-learning/home
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Narang, Yashraj S., Balakumar Sundaralingam, Karl Van Wyk, Arsalan Mousavian, and Dieter Fox. "Interpreting and predicting tactile signals for the SynTouch BioTac." International Journal of Robotics Research 40, no. 12-14 (November 26, 2021): 1467–87. http://dx.doi.org/10.1177/02783649211047634.
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In the human hand, high-density contact information provided by afferent neurons is essential for many human grasping and manipulation capabilities. In contrast, robotic tactile sensors, including the state-of-the-art SynTouch BioTac, are typically used to provide low-density contact information, such as contact location, center of pressure, and net force. Although useful, these data do not convey or leverage the rich information content that some tactile sensors naturally measure. This research extends robotic tactile sensing beyond reduced-order models through (1) the automated creation of a precise experimental tactile dataset for the BioTac over a diverse range of physical interactions, (2) a 3D finite-element (FE) model of the BioTac, which complements the experimental dataset with high-density, distributed contact data, (3) neural-network-based mappings from raw BioTac signals to not only low-dimensional experimental data, but also high-density FE deformation fields, and (4) mappings from the FE deformation fields to the raw signals themselves. The high-density data streams can provide a far greater quantity of interpretable information for grasping and manipulation algorithms than previously accessible. Datasets, CAD files for the experimental testbed, FE model files, and videos are available at https://sites.google.com/nvidia.com/tactiledata .
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Piscopo, Alessandro, Oana Inel, Sanne Vrijenhoek, Martijn Millecamp, and Krisztian Balog. "Report on the 1st Workshop on Measuring the Quality of Explanations in Recommender Systems (QUARE 2022) at SIGIR 2022." ACM SIGIR Forum 56, no. 2 (December 2022): 1–16. http://dx.doi.org/10.1145/3582900.3582915.
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Explainable recommenders are systems that explain why an item is recommended, in addition to suggesting relevant items to the users of the system. Although explanations are known to be able to significantly affect a user's decision-making process, significant gaps remain concerning methodologies to evaluate them. This hinders cross-comparison between explainable recommendation approaches and is one of the issues hampering the widespread adoption of explanations in industry settings. The goal of QUARE '22 was to promote discussion upon future research and practice directions around evaluation methodologies for explanations in recommender systems. To that end, we brought together researchers and practitioners from academia and industry in a half-day event, co-located with SIGIR 2022. The workshop's program included two keynote talks, three sessions of technical paper presentations in the form of lightning talks followed by panel discussions, and a final plenary discussion session. Although the area of explanations for recommender systems is still in its early stages, QUARE saw the participation of researchers and practitioners from several fields, laying the groundwork for the creation of a community around this topic and indicating promising directions for future research and development. Date: 15 July, 2022. Website: https://sites.google.com/view/quare-2022/home.
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Zhang, Linrui, Qin Zhang, Li Shen, Bo Yuan, Xueqian Wang, and Dacheng Tao. "Evaluating Model-Free Reinforcement Learning toward Safety-Critical Tasks." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 12 (June 26, 2023): 15313–21. http://dx.doi.org/10.1609/aaai.v37i12.26786.
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Safety comes first in many real-world applications involving autonomous agents. Despite a large number of reinforcement learning (RL) methods focusing on safety-critical tasks, there is still a lack of high-quality evaluation of those algorithms that adheres to safety constraints at each decision step under complex and unknown dynamics. In this paper, we revisit prior work in this scope from the perspective of state-wise safe RL and categorize them as projection-based, recovery-based, and optimization-based approaches, respectively. Furthermore, we propose Unrolling Safety Layer (USL), a joint method that combines safety optimization and safety projection. This novel technique explicitly enforces hard constraints via the deep unrolling architecture and enjoys structural advantages in navigating the trade-off between reward improvement and constraint satisfaction. To facilitate further research in this area, we reproduce related algorithms in a unified pipeline and incorporate them into SafeRL-Kit, a toolkit that provides off-the-shelf interfaces and evaluation utilities for safety-critical tasks. We then perform a comparative study of the involved algorithms on six benchmarks ranging from robotic control to autonomous driving. The empirical results provide an insight into their applicability and robustness in learning zero-cost-return policies without task-dependent handcrafting. The project page is available at https://sites.google.com/view/saferlkit.
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Alhinti, Lubna, Stuart Cunningham, and Heidi Christensen. "The Dysarthric Expressed Emotional Database (DEED): An audio-visual database in British English." PLOS ONE 18, no. 8 (August 7, 2023): e0287971. http://dx.doi.org/10.1371/journal.pone.0287971.
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The Dysarthric Expressed Emotional Database (DEED) is a novel, parallel multimodal (audio-visual) database of dysarthric and typical emotional speech in British English which is a first of its kind. It is an induced (elicited) emotional database that includes speech recorded in the six basic emotions: “happiness”, “sadness”, “anger”, “surprise”, “fear”, and “disgust”. A “neutral” state has also been recorded as a baseline condition. The dysarthric speech part includes recordings from 4 speakers: one female speaker with dysarthria due to cerebral palsy and 3 speakers with dysarthria due to Parkinson’s disease (2 female and 1 male). The typical speech part includes recordings from 21 typical speakers (9 female and 12 male). This paper describes the collection of the database, covering its design, development, technical information related to the data capture, and description of the data files and presents the validation methodology. The database was validated subjectively (human performance) and objectively (automatic recognition). The achieved results demonstrated that this database will be a valuable resource for understanding emotion communication by people with dysarthria and useful in the research field of dysarthric emotion classification. The database is freely available for research purposes under a Creative Commons licence at: https://sites.google.com/sheffield.ac.uk/deed
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Chen, Jiayu, Zelai Xu, Yunfei Li, Chao Yu, Jiaming Song, Huazhong Yang, Fei Fang, Yu Wang, and Yi Wu. "Accelerate Multi-Agent Reinforcement Learning in Zero-Sum Games with Subgame Curriculum Learning." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 10 (March 24, 2024): 11320–28. http://dx.doi.org/10.1609/aaai.v38i10.29011.
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Learning Nash equilibrium (NE) in complex zero-sum games with multi-agent reinforcement learning (MARL) can be extremely computationally expensive. Curriculum learning is an effective way to accelerate learning, but an under-explored dimension for generating a curriculum is the difficulty-to-learn of the subgames –games induced by starting from a specific state. In this work, we present a novel subgame curriculum learning framework for zero-sum games. It adopts an adaptive initial state distribution by resetting agents to some previously visited states where they can quickly learn to improve performance. Building upon this framework, we derive a subgame selection metric that approximates the squared distance to NE values and further adopt a particle-based state sampler for subgame generation. Integrating these techniques leads to our new algorithm, Subgame Automatic Curriculum Learning (SACL), which is a realization of the subgame curriculum learning framework. SACL can be combined with any MARL algorithm such as MAPPO. Experiments in the particle-world environment and Google Research Football environment show SACL produces much stronger policies than baselines. In the challenging hide-and-seek quadrant environment, SACL produces all four emergent stages and uses only half the samples of MAPPO with self-play. The project website is at https://sites.google.com/view/sacl-neurips.
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Aini, Windra, Darmayasa Darmayasa, Ruth Rinda, Ahmad Tarmizi Abdul Karim, Agus Sugiarto, Andri Estining Sejati, and Masri Ridwan. "Website learning media to enhance planning tour packages competencies: A case study from Makassar Tourism Polytechnic, Indonesia." Jurnal Pendidikan Geografi: Kajian, Teori, dan Praktek dalam Bidang Pendidikan dan Ilmu Geografi 29, no. 1 (January 30, 2024): 43. http://dx.doi.org/10.17977/um017v29i12024p43-59.
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This research aims to develop website-based learning media on tourism package planning competency and report its feasibility. In particular, this study aims to address the challenges posed by the COVID-19 pandemic, which has made it difficult to conduct field trips or study tours, a crucial component of the travel business study program at Politeknik Pariwisata Makassar. The research addopted a research and development (R&D) approach with the ADDIE model, as well as involving the material experts and media experts in the media assessments. Learning media trials were conducted in small groups comprising ten students and in large groups with 30 students. The learning media development resulted in a website hosted on the Google Site at https://sites.google.com/view/membuat-paket-wisata/halaman-muka. The expert assessment of the media's learning content and teaching process obtained an average score of 4.56 in the very good category. Meanwhile, the assessment of media experts on appearance and programming obtained an average score of 4.41 in the very good category. Similarly, the product trials involving students also culminate in an average score of 4.45 in the excellent category. In general, the results of the assessment and trials concluded that website-based learning media is feasible to be adopted in the competence of planning tour packages.
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Hsu, Kai-Chieh, Allen Z. Ren, Duy P. Nguyen, Anirudha Majumdar, and Jaime F. Fisac. "Sim-to-Lab-to-Real: Safe Reinforcement Learning with Shielding and Generalization Guarantees (Abstract Reprint)." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 20 (March 24, 2024): 22699. http://dx.doi.org/10.1609/aaai.v38i20.30599.
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Safety is a critical component of autonomous systems and remains a challenge for learning-based policies to be utilized in the real world. In particular, policies learned using reinforcement learning often fail to generalize to novel environments due to unsafe behavior. In this paper, we propose Sim-to-Lab-to-Real to bridge the reality gap with a probabilistically guaranteed safety-aware policy distribution. To improve safety, we apply a dual policy setup where a performance policy is trained using the cumulative task reward and a backup (safety) policy is trained by solving the Safety Bellman Equation based on Hamilton-Jacobi (HJ) reachability analysis. In Sim-to-Lab transfer, we apply a supervisory control scheme to shield unsafe actions during exploration; in Lab-to-Real transfer, we leverage the Probably Approximately Correct (PAC)-Bayes framework to provide lower bounds on the expected performance and safety of policies in unseen environments. Additionally, inheriting from the HJ reachability analysis, the bound accounts for the expectation over the worst-case safety in each environment. We empirically study the proposed framework for ego-vision navigation in two types of indoor environments with varying degrees of photorealism. We also demonstrate strong generalization performance through hardware experiments in real indoor spaces with a quadrupedal robot. See https://sites.google.com/princeton.edu/sim-to-lab-to-real for supplementary material.
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Yue, Lori Qingyuan, Jiexin Zheng, and Kaixian Mao. "Firms’ Rhetorical Nationalism: Theory, Measurement, and Evidence from a Computational Analysis of Chinese Public Firms." Management and Organization Review 20, no. 2 (April 2024): 161–203. http://dx.doi.org/10.1017/mor.2024.6.
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AbstractIn this article, we develop a computational measure of firm-level rhetorical nationalism. We first review the literature and develop a four-dimensional theoretical framework of nationalism relevant to firms: national pride, anti-foreign, dominant agenda (national revival), and corporate role. We then use machine-learning-based text analysis of over 41,000 annual reports of Chinese public firms from 2000 to 2020 and identify a dictionary of words for each dimension. Using a weighted ratio of nationalism-related words, we describe the overall picture of Chinese public firms’ rhetorical nationalism and provide the first empirical evidence regarding rising rhetorical nationalism among Chinese firms. Firms’ demonstration of rhetorical nationalism is related to both strategic and socialization factors; firms that are state-owned enterprises, older, larger, more profitable, consumer-facing, with more individual investors, and lower sales from overseas demonstrate a higher level of nationalism. Firms that demonstrate more rhetorical nationalism also have a better future financial return. Our study provides a theoretical framework for the organizational study of nationalism and a new measure for firms’ rhetorical nationalism, and demonstrates that rising rhetorical nationalism among Chinese firms is more strongly driven by firms’ motivations to appeal to domestic investors and consumers than to obtain government subsidies. Our dataset is publicly available at: https://sites.google.com/view/firms-rhetorical-nationalism
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Song, Yuhang, Andrzej Wojcicki, Thomas Lukasiewicz, Jianyi Wang, Abi Aryan, Zhenghua Xu, Mai Xu, Zihan Ding, and Lianlong Wu. "Arena: A General Evaluation Platform and Building Toolkit for Multi-Agent Intelligence." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (April 3, 2020): 7253–60. http://dx.doi.org/10.1609/aaai.v34i05.6216.
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Learning agents that are not only capable of taking tests, but also innovating is becoming a hot topic in AI. One of the most promising paths towards this vision is multi-agent learning, where agents act as the environment for each other, and improving each agent means proposing new problems for others. However, existing evaluation platforms are either not compatible with multi-agent settings, or limited to a specific game. That is, there is not yet a general evaluation platform for research on multi-agent intelligence. To this end, we introduce Arena, a general evaluation platform for multi-agent intelligence with 35 games of diverse logics and representations. Furthermore, multi-agent intelligence is still at the stage where many problems remain unexplored. Therefore, we provide a building toolkit for researchers to easily invent and build novel multi-agent problems from the provided game set based on a GUI-configurable social tree and five basic multi-agent reward schemes. Finally, we provide Python implementations of five state-of-the-art deep multi-agent reinforcement learning baselines. Along with the baseline implementations, we release a set of 100 best agents/teams that we can train with different training schemes for each game, as the base for evaluating agents with population performance. As such, the research community can perform comparisons under a stable and uniform standard. All the implementations and accompanied tutorials have been open-sourced for the community at https://sites.google.com/view/arena-unity/.
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Casser, Vincent, Soeren Pirk, Reza Mahjourian, and Anelia Angelova. "Depth Prediction without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 8001–8. http://dx.doi.org/10.1609/aaai.v33i01.33018001.
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Learning to predict scene depth from RGB inputs is a challenging task both for indoor and outdoor robot navigation. In this work we address unsupervised learning of scene depth and robot ego-motion where supervision is provided by monocular videos, as cameras are the cheapest, least restrictive and most ubiquitous sensor for robotics.
Previous work in unsupervised image-to-depth learning has established strong baselines in the domain. We propose a novel approach which produces higher quality results, is able to model moving objects and is shown to transfer across data domains, e.g. from outdoors to indoor scenes. The main idea is to introduce geometric structure in the learning process, by modeling the scene and the individual objects; camera ego-motion and object motions are learned from monocular videos as input. Furthermore an online refinement method is introduced to adapt learning on the fly to unknown domains.
The proposed approach outperforms all state-of-the-art approaches, including those that handle motion e.g. through learned flow. Our results are comparable in quality to the ones which used stereo as supervision and significantly improve depth prediction on scenes and datasets which contain a lot of object motion. The approach is of practical relevance, as it allows transfer across environments, by transferring models trained on data collected for robot navigation in urban scenes to indoor navigation settings. The code associated with this paper can be found at https://sites.google.com/view/struct2depth.
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Bian, Yuanyuan, Chong He, Jie Hou, Jianlin Cheng, and Jing Qiu. "PairedFB: a full hierarchical Bayesian model for paired RNA-seq data with heterogeneous treatment effects." Bioinformatics 35, no. 5 (August 23, 2018): 787–97. http://dx.doi.org/10.1093/bioinformatics/bty731.
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Abstract Motivation Several methods have been proposed for the paired RNA-seq analysis. However, many of them do not consider the heterogeneity in treatment effect among pairs that can naturally arise in real data. In addition, it has been reported in literature that the false discovery rate (FDR) control of some popular methods has been problematic. In this paper, we present a full hierarchical Bayesian model for the paired RNA-seq count data that accounts for variation of treatment effects among pairs and controls the FDR through the posterior expected FDR. Results Our simulation studies show that most competing methods can have highly inflated FDR for small to moderate sample sizes while PairedFB is able to control FDR close to the nominal levels. Furthermore, PairedFB has overall better performance in ranking true differentially expressed genes (DEGs) on the top than others, especially when the sample size gets bigger or when the heterogeneity level of treatment effects is high. In addition, PairedFB can be applied to identify the biologically significant DEGs with controlled FDR. The real data analysis also indicates PairedFB tends to find more biologically relevant genes even when the sample size is small. PairedFB is also shown to be robust with respect to the model misspecification in terms of its relative performance compared to others. Availability and implementation Software to implement this method (PairedFB) can be downloaded at: https://sites.google.com/a/udel.edu/qiujing/publication. Supplementary information Supplementary data are available at Bioinformatics online.
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Kim, Daehan, Minseok Seo, Kwanyong Park, Inkyu Shin, Sanghyun Woo, In So Kweon, and Dong-Geol Choi. "Bidirectional Domain Mixup for Domain Adaptive Semantic Segmentation." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 1 (June 26, 2023): 1114–23. http://dx.doi.org/10.1609/aaai.v37i1.25193.
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Mixup provides interpolated training samples and allows the model to obtain smoother decision boundaries for better generalization. The idea can be naturally applied to the domain adaptation task, where we can mix the source and target samples to obtain domain-mixed samples for better adaptation. However, the extension of the idea from classification to segmentation (i.e., structured output) is nontrivial. This paper systematically studies the impact of mixup under the domain adaptive semantic segmentation task and presents a simple yet effective mixup strategy called Bidirectional Domain Mixup (BDM). In specific, we achieve domain mixup in two-step: cut and paste. Given the warm-up model trained from any adaptation techniques, we forward the source and target samples and perform a simple threshold-based cut out of the unconfident regions (cut). After then, we fill-in the dropped regions with the other domain region patches (paste). In doing so, we jointly consider class distribution, spatial structure, and pseudo label confidence. Based on our analysis, we found that BDM leaves domain transferable regions by cutting, balances the dataset-level class distribution while preserving natural scene context by pasting. We coupled our proposal with various state-of-the-art adaptation models and observe significant improvement consistently. We also provide extensive ablation experiments to empirically verify our main components of the framework. Visit our project page with the code at https://sites.google.com/view/bidirectional-domain-mixup
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Micev, Kire, Jan Steiner, Asude Aydin, Jörg Rieckermann, and Tobi Delbruck. "Measuring diameters and velocities of artificial raindrops with a neuromorphic event camera." Atmospheric Measurement Techniques 17, no. 1 (January 18, 2024): 335–57. http://dx.doi.org/10.5194/amt-17-335-2024.
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Abstract. Hydrometers that measure size and velocity distributions of precipitation are needed for research and corrections of rainfall estimates from weather radars and microwave links. Existing optical disdrometers measure droplet size distributions, but underestimate small raindrops and are impractical for widespread always-on IoT deployment. We study the feasibility of measuring droplet size and velocity using a neuromorphic event camera. These dynamic vision sensors asynchronously output a sparse stream of pixel brightness changes. Droplets falling through the plane of focus of a steeply down-looking camera create events generated by the motion of the droplet across the field of view. Droplet size and speed are inferred from the hourglass-shaped stream of events. Using an improved hard disk arm actuator to reliably generate artificial raindrops with a range of small sizes, our experiments show maximum errors of 7 % (mean absolute percentage error) for droplet sizes from 0.3 to 2.5 mm and speeds from 1.3 to 8.0 m s−1. Measurements with the same setup from a commercial PARSIVEL disdrometer show similar results. Both devices slightly overestimate the small droplet volume with a volume overestimation of 25 % from the event camera measurements and 50 % from the PARSIVEL instrument. Each droplet requires processing of 5000 to 50 000 brightness change events, potentially enabling low-power always-on disdrometers that consume power proportional to the rainfall rate. Data and code are available at the paper website https://sites.google.com/view/dvs-disdrometer/home (Micev et al., 2023).
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Abbasi, Wajid Arshad, Syed Ali Abbas, and Saiqa Andleeb. "PANDA: Predicting the change in proteins binding affinity upon mutations by finding a signal in primary structures." Journal of Bioinformatics and Computational Biology 19, no. 04 (June 11, 2021): 2150015. http://dx.doi.org/10.1142/s0219720021500153.
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Accurately determining a change in protein binding affinity upon mutations is important to find novel therapeutics and to assist mutagenesis studies. Determination of change in binding affinity upon mutations requires sophisticated, expensive, and time-consuming wet-lab experiments that can be supported with computational methods. Most of the available computational prediction techniques depend upon protein structures that bound their applicability to only protein complexes with recognized 3D structures. In this work, we explore the sequence-based prediction of change in protein binding affinity upon mutation and question the effectiveness of [Formula: see text]-fold cross-validation (CV) across mutations adopted in previous studies to assess the generalization ability of such predictors with no known mutation during training. We have used protein sequence information instead of protein structures along with machine learning techniques to accurately predict the change in protein binding affinity upon mutation. Our proposed sequence-based novel change in protein binding affinity predictor called PANDA performs comparably to the existing methods gauged through an appropriate CV scheme and an external independent test dataset. On an external test dataset, our proposed method gives a maximum Pearson correlation coefficient of 0.52 in comparison to the state-of-the-art existing protein structure-based method called MutaBind which gives a maximum Pearson correlation coefficient of 0.59. Our proposed protein sequence-based method, to predict a change in binding affinity upon mutations, has wide applicability and comparable performance in comparison to existing protein structure-based methods. We made PANDA easily accessible through a cloud-based webserver and python code available at https://sites.google.com/view/wajidarshad/software and https://github.com/wajidarshad/panda , respectively.
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De Smedt, Sofie, Ann Bogaerts, Quentin Groom, and Henry Engledow. "Botanicalcollections.be: The New Virtual Herbarium of Meise Botanic Garden (BR)." Biodiversity Information Science and Standards 2 (June 13, 2018): e26140. http://dx.doi.org/10.3897/biss.2.26140.
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The botanicalcollections.be website (http://www.botanicalcollections.be) is the culmination of the three year Digitale Ontsluiting Erfgoedcollecties (DOE!) project. Over this period we have digitally imaged 1.2 million African and Belgian herbarium specimens and much of their label data. All these data are freely available on our new virtual herbarium www.botanicalcollections.be. For this we have to thank a generous grant from the Flemish Government. The site was officially launched on the 23rd March, 2018, at the Fourth Annual Meeting of Plant Ecology and Evolution held at Bouchout Castle in Meise Botanic Garden (https://sites.google.com/plantentuinmeise.be/ampee4/). Before developing the website we conducted a user requirements analysis (Vissers et al. 2017. These requirements formed the basis for development from initial design to the finished product. Lots of features were incorporated to make the site as user-friendly and usable as possible; persistent URIs, zoomable and downloadable images and access to data. Each specimen can be annotated and is available in a machine readable format. The goal of the botanicalcollections.be website is not only to make digitized specimens from the Botanic Garden available, but also to centralize and display the herbarium specimens from other Belgian herbaria. A cooperation agreement will make collaboration easy and transparent. The benefits to herbaria of participating in this virtual herbarium include greater publicity, the ability to show how their specimens contribute to overall knowledge, and a mechanism for identifying where to focus future collecting efforts, all of which help validate their worth to institutional administrators. In addition, such cooperation helps build professional relationships who, because of disparate interests and obligations, might not normally connect with each other.
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Кононец, Н. В. "РОЛЬ ІНФОРМАЦІЙНО-ОСВІТНЬОГО СЕРЕДОВИЩА ЗАКЛАДУ ВИЩОЇ ОСВІТИ ПРИ РЕСУРСНО-ОРІЄНТОВАНОМУ НАВЧАННІ СТУДЕНТІВ У ВИЩІЙ ШКОЛІ." Засоби навчальної та науково-дослідної роботи, no. 51 (2018): 31–45. http://dx.doi.org/10.34142/2312-1548.2018.51.03.
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У статті автор розкриває роль інформаційно-освітнього середовища закладу вищої освіти при ресурсно-орієнтованому навчанні студентів у вищій школі. Інформаційно-освітнє середовище закладу вищої освіти як дидактична основа ресурсно-орієнтованого навчання студентів у вищій школі представлене як педагогічна система, що об’єднує в собі інформаційні освітні ресурси, комп’ютерні засоби навчання, засоби управління навчальним процесом, педагогічні прийоми, методи і технології, направлені на формування інтелектуально-розвиненої соціально-значущої творчої особистості, що володіє необхідним рівнем професійних знань, умінь і навичок для ефективного функціонування в інформаційному суспільстві. Компонентами інформаційно-освітнього середовища закладу вищої освіти є суб’єктно-ресурсний, матеріально-технічний, дидактичний, технологічний компоненти та веб-система закладу вищої освіти. Суб’єктно-ресурсний компонент визначає користувачів, розробників та учасників середовища, консолідує ресурси закладу вищої освіти для створення та розвитку середовища: кадрові, матеріально-технічні, навчально-методичні, фінансові та інформаційні ресурси. Матеріально-технічний компонент містить аудиторії, лабораторії, спеціальні кабінети, бібліотека закладу вищої освіти як комплексний медіацентр, що забезпечує доступ до інформації, комп’ютерна техніка, мультимедійні пристрої, комп’ютерні мережі тощо. Дидактичний компонент містить форми, методи та засоби навчання студентів, які, разом з традиційними, реалізуються за допомогою програмно-технічних і телекомунікаційних засобів (дистанційне, змішане, мобільне навчання). Технологічний компонент забезпечує доступ до навчальної інформації завдяки сучасним інтернет-технологіям, можливості розробки електронних освітніх ресурсів, організацію технологій взаємодії (інтерактивної, мобільної, візуальної). Веб-система закладу вищої освіти як компонент його інформаційно-освітнього середовища є об’єднуючим для усіх чотирьох компонентів – сукупність веб-сайтів, об’єднаних офіційним веб-сайтом. Розглянуто важливі складові інформаційно-освітнього середовища ВНЗ Укоопспілки «Полтавський університет економіки і торгівлі»: Головний центр дистанційного навчання, віртуальне навчальне середовище Інституту економіки, управління та інформаційних технологій, електронні навчально-методичні комплекси дисциплін, створені у вигляді дистанційних курсів за допомогою сервісу https://sites.google.com/.
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Wright, Kath, Julie Glanville, and Carol Lefebvre. "VP195 Using The ISSG Search Filter Resource In Health Technology Assessment." International Journal of Technology Assessment in Health Care 33, S1 (2017): 240. http://dx.doi.org/10.1017/s0266462317004226.
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INTRODUCTION:Information specialists and others searching for Health Technology Assessments (HTAs) can use the ISSG Search Filter resource (SFR) to identify filters to incorporate into search strategies. This can save time and effort when designing searches and create more efficient searches that retrieve fewer and possibly more relevant database records (link available here: https://sites.google.com/a/york.ac.uk/issg-search-filters-resource/home).What are search filters? Search filters are collections of search terms designed to retrieve selections of records from bibliographic databases. Some filters are designed to retrieve records of specific study designs such as randomized controlled trials (RCTs) or systematic reviews; others aim to retrieve records relating to other features or topics such as the age or gender of study participants.Search filters may be designed to be sensitive, precise or balanced between sensitivity and precision.METHODS:When would you use a search filter in HTA? Search filters can be added to search strategies to limit to specific study types, for example, RCTs, mixed methods studies, systematic reviews. They can also be used when searching for other aspects of HTA such as patient views or specific age groups.The ISSG SFR includes sections listing search filters to help identify adverse effects, aetiology, economic evaluations, health state utility values, public views, and quality of life.RESULTS:How are filters used? A search filter is often used in combination with a topic search to restrict the search results to a specific type of record, for example, records reporting health state utility values or records of randomized controlled trials.CONCLUSIONS:Further guidance on the use of search filters can be found in the SuRe Info Search Filters chapter.
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Li, Yang, Shao Zhang, Jichen Sun, Wenhao Zhang, Yali Du, Ying Wen, Xinbing Wang, and Wei Pan. "Tackling Cooperative Incompatibility for Zero-Shot Human-AI Coordination." Journal of Artificial Intelligence Research 80 (July 23, 2024): 1139–85. http://dx.doi.org/10.1613/jair.1.15884.
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Securing coordination between AI agent and teammates (human players or AI agents) in contexts involving unfamiliar humans continues to pose a significant challenge in Zero-Shot Coordination. The issue of cooperative incompatibility becomes particularly prominent when an AI agent is unsuccessful in synchronizing with certain previously unknown partners. Traditional algorithms have aimed to collaborate with partners by optimizing fixed objectives within a population, fostering diversity in strategies and behaviors. However, these techniques may lead to learning loss and an inability to cooperate with specific strategies within the population, a phenomenon named cooperative incompatibility in learning. In order to solve cooperative incompatibility in learning and effectively address the problem in the context of ZSC, we introduce the Cooperative Open-ended LEarning (COLE) framework, which formulates open-ended objectives in cooperative games with two players using perspectives of graph theory to evaluate and pinpoint the cooperative capacity of each strategy. We present two practical algorithms, specifically COLESV and COLER, which incorporate insights from game theory and graph theory. We also show that COLE could effectively overcome the cooperative incompatibility from theoretical and empirical analysis. Subsequently, we created an online Overcooked human-AI experiment platform, the COLE platform, which enables easy customization of questionnaires, model weights, and other aspects. Utilizing the COLE platform, we enlist 130 participants for human experiments. Our findings reveal a preference for our approach over state-of-the-art methods using a variety of subjective metrics. Moreover, objective experimental outcomes in the Overcooked game environment indicate that our method surpasses existing ones when coordinating with previously unencountered AI agents and the human proxy model. Our code and demo are publicly available at https://sites.google.com/view/cole-2023.
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Magro, Bianca, Valentina Zuccaro, Luca Novelli, Lorenzo Zileri, Ciro Celsa, Federico Raimondi, Mauro Gori, et al. "Predicting in-hospital mortality from Coronavirus Disease 2019: A simple validated app for clinical use." PLOS ONE 16, no. 1 (January 14, 2021): e0245281. http://dx.doi.org/10.1371/journal.pone.0245281.
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Backgrounds Validated tools for predicting individual in-hospital mortality of COVID-19 are lacking. We aimed to develop and to validate a simple clinical prediction rule for early identification of in-hospital mortality of patients with COVID-19. Methods and findings We enrolled 2191 consecutive hospitalized patients with COVID-19 from three Italian dedicated units (derivation cohort: 1810 consecutive patients from Bergamo and Pavia units; validation cohort: 381 consecutive patients from Rome unit). The outcome was in-hospital mortality. Fine and Gray competing risks multivariate model (with discharge as a competing event) was used to develop a prediction rule for in-hospital mortality. Discrimination and calibration were assessed by the area under the receiver operating characteristic curve (AUC) and by Brier score in both the derivation and validation cohorts. Seven variables were independent risk factors for in-hospital mortality: age (Hazard Ratio [HR] 1.08, 95% Confidence Interval [CI] 1.07–1.09), male sex (HR 1.62, 95%CI 1.30–2.00), duration of symptoms before hospital admission <10 days (HR 1.72, 95%CI 1.39–2.12), diabetes (HR 1.21, 95%CI 1.02–1.45), coronary heart disease (HR 1.40 95% CI 1.09–1.80), chronic liver disease (HR 1.78, 95%CI 1.16–2.72), and lactate dehydrogenase levels at admission (HR 1.0003, 95%CI 1.0002–1.0005). The AUC was 0.822 (95%CI 0.722–0.922) in the derivation cohort and 0.820 (95%CI 0.724–0.920) in the validation cohort with good calibration. The prediction rule is freely available as a web-app (COVID-CALC: https://sites.google.com/community.unipa.it/covid-19riskpredictions/c19-rp). Conclusions A validated simple clinical prediction rule can promptly and accurately assess the risk for in-hospital mortality, improving triage and the management of patients with COVID-19.
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Calhoun, Karen, Tabia Akintobi, Al Richmond, N. Glassman, Rosanna Barrett, and Hal Strelnick. "283 Progress in Community Health Partnerships Writing, Dissemination and Reviewer Learning Community for Community-Patient Authors and Reviewers (henceforth, PCHP LC)." Journal of Clinical and Translational Science 8, s1 (April 2024): 86–87. http://dx.doi.org/10.1017/cts.2024.259.
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OBJECTIVES/GOALS: The peer-reviewed journal Progress in Community Health Partnerships (PCHP) promotes health research partnerships to improve community health. PCHP’s Writing, Dissemination and Reviewer Learning Community Pilot aims to increase stakeholders writing and reviewing for greater relevance and diversity. METHODS/STUDY POPULATION: Led by PCHP’s Editorial Team, Morehouse SOM, Community-Campus Partnerships for Health (CCPH) and a community-academic Workgroup, the LC will guide stakeholders on scholarly writing and publish collaborative research. It builds on the 2017 Writing/Dissemination Learning Institute held by Morehouse, CCPH, and Community Based Organization Partners with the APHA Public Health Caucus. The LC begins with a Workshop [https://sites.google.com/view/pchp2023/pchpcommunity2023] alongside the 2023 APHA Annual Meeting. Wrap arounds include a PCHP Special Issue (participants work), Webinars, PCHP Reflections/Community Perspectives Article Guidelines [https://www.press.jhu.edu/journals/progress-community-health-partnerships-research-education-and-action], “Beyond the Manuscript [https://open.spotify.com/show/2LiBanXAyHyOqNSeGnBPHs]” Podcast, Toolkit/Resources; and coaching. The evaluation will inform PCHP practices. RESULTS/ANTICIPATED RESULTS: Key outcomes include successful implementation of all LI activities. The cohort (approximately 40 stakeholders representing partnerships) will increase exposure to scholarly writing and peer review, ideally publish 12+ manuscripts (e.g., PCHP special issue), increase diversity in scholarly writing, and strengthen recognition/significance of stakeholder authorship in the research community. The year 1 pilot evaluation (e.g., tracking participant authorship, documenting outcomes/lessons learned) will provide evidence to encourage sustainability, model responsiveness among other peer reviewed journals, inform PCHP, and increase diversity in scholarly writing on health disparities research. DISCUSSION/SIGNIFICANCE: The pilot will build a sustainable model and how PCHPaddresses health disparities to increase diversity, equity, and inclusion. The LC aims to diversify framing community health research, supporting/publishing stakeholders work, and increasing diversity among reviewers, all impacting the field.
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Evdokimov, V. I., V. I. Sibirko, S. G. Shapovalov, Yu R. Yunusova, and V. A. Martynov. "Assessment of fire risks in Russian Federation in general and its megacities using the example of Moscow and St. Petersburg, 2009–2021." Disaster Medicine, no. 3 (September 2023): 19–23. http://dx.doi.org/10.33266/2070-1004-2023-3-19-23.
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Summary. The purpose of the study is, in connection with the change in the procedure for statistical recording of fires, to assess their health consequences in the Russian Federation as a whole and its megacities using the example of Moscow and St. Petersburg for 13 years (2009–2021). Materials and methods of research. Data on the number of fires was taken from the Federal Database “Fires” [https://sites.google.com/site/statistikapozaro/]; population size – on the Rosstat website [https://rosstat.gov.ru/]. Retrospectively, fire statistics since 2009 have included fires. The results of the study were checked for normal distribution of characteristics. The dynamics of indicators was studied using the analysis of time series, for which a 2nd order polynomial trend was used, etc. Research results and their analysis. As a result of the study, the following risks were calculated for the population of the Russian Federation as a whole, Moscow and St. Petersburg: the risk of being caught in a fire; risk of dying in a fire; risk of injury in a fire; individual risk of dying in a fire per 100 thousand population; individual risk of injury in a fire per 100 thousand population. Conclusions: As a rule, the magnitude of individual fire risks in megacities, due to the coordinated work of fire crews during fire fighting, evacuation of people and a number of other circumstances, was less than in the Russian Federation as a whole; there is also a downward trend. The individual risk of death in a fire in Moscow and St. Petersburg was low for Russia; in Moscow the individual risk of injury was low, in St. Petersburg it was average. The calculated new fire risks can be used when carrying out more targeted work to reduce them in the regions of the Russian Federation.
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Міyer, Тetiana І., Larysa S. Holodiuk, and Valentyn О. Savosh. "PREVENTING THE PRE-SICK CONDITIONS OF THOSE WHO PRACTICE LIFELONG LEARNING." Wiadomości Lekarskie 74, no. 1 (January 2021): 107–11. http://dx.doi.org/10.36740/wlek202101121.
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The aim: Disclosure of the results of the study of the expediency of considering the fluidity of mental processes in the triad “organism – personality Disclosure of the results of the study of the expediency of considering the fluidity of mental processes in the triad “organism – personality – environment” and the alternate stages of the dynamics of performance to prevent the occurrence of pre-painful conditions in students, combining professional activity with formal education. Materials and methods: The complex of research methods is used in the work: general scientific (analysis, synthesis, comparison, systematization, generalization) and empirical (observations, discussions, questionnaires). The research was carried out within the framework of the international project “AHIA” (innovation in education; access mode: https://sites.google.com/view/project-axia/). The Spielberger-Hanin questionnaire was used to achieve the stated purpose of the study, the purpose of which was to assess reactive and personal anxiety. Results: The results of a study aimed at organizing a lifelong learning process based on mental processes and stages of performance dynamics showed that the likelihood of pre-painful conditions in those who combine full-time education in higher education with professional activity significantly decreases their self-actualization. Educational events taking place here and now, and recognizing the theoretical and practical significance of the educational material at the level of intrinsic motives. It is established that the likelihood of pre-morbid conditions in those who learn during life significantly increases in the case of reduced functional reserves of their body as a result of the intense and prolonged performance of educational activities with the simultaneous experience of “negatively” colored actual emotional states, generated by activities or events ) experiences of relationships in professional activity, family, family, etc. Conclusions: The proposed article describes the effectiveness and appropriateness of using mental processes and stages of performance dynamics as a means to prevent the onset of painful conditions in lifelong learners.
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Palukuri, Meghana Venkata, and Edward M. Marcotte. "Super.Complex: A supervised machine learning pipeline for molecular complex detection in protein-interaction networks." PLOS ONE 16, no. 12 (December 31, 2021): e0262056. http://dx.doi.org/10.1371/journal.pone.0262056.
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Characterization of protein complexes, i.e. sets of proteins assembling into a single larger physical entity, is important, as such assemblies play many essential roles in cells such as gene regulation. From networks of protein-protein interactions, potential protein complexes can be identified computationally through the application of community detection methods, which flag groups of entities interacting with each other in certain patterns. Most community detection algorithms tend to be unsupervised and assume that communities are dense network subgraphs, which is not always true, as protein complexes can exhibit diverse network topologies. The few existing supervised machine learning methods are serial and can potentially be improved in terms of accuracy and scalability by using better-suited machine learning models and parallel algorithms. Here, we present Super.Complex, a distributed, supervised AutoML-based pipeline for overlapping community detection in weighted networks. We also propose three new evaluation measures for the outstanding issue of comparing sets of learned and known communities satisfactorily. Super.Complex learns a community fitness function from known communities using an AutoML method and applies this fitness function to detect new communities. A heuristic local search algorithm finds maximally scoring communities, and a parallel implementation can be run on a computer cluster for scaling to large networks. On a yeast protein-interaction network, Super.Complex outperforms 6 other supervised and 4 unsupervised methods. Application of Super.Complex to a human protein-interaction network with ~8k nodes and ~60k edges yields 1,028 protein complexes, with 234 complexes linked to SARS-CoV-2, the COVID-19 virus, with 111 uncharacterized proteins present in 103 learned complexes. Super.Complex is generalizable with the ability to improve results by incorporating domain-specific features. Learned community characteristics can also be transferred from existing applications to detect communities in a new application with no known communities. Code and interactive visualizations of learned human protein complexes are freely available at: https://sites.google.com/view/supercomplex/super-complex-v3-0.
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Singh, Abhay. "Quantifying unmeasured confounding in three epidemiological studies associating myelodysplastic syndromes (MDS) with cardiovascular disease (CVD)." Journal of Clinical Oncology 38, no. 15_suppl (May 20, 2020): e19532-e19532. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e19532.
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e19532 Background: Confounding occurs when an investigator studies the effect of an exposure on the occurrence of an outcome, but in the process measures the effect of another factor (a confounding variable). Knowledge of possible causal pathways assists an investigator to minimize confounding, but despite utmost attempts, errors are frequent. To assess role of a possible confounder (smoking), data from 3 studies (1. Herrera at al. 2019 2. Goldberg et al. 2010 and 3. Brunner et al. 2017) associating MDS (exposure) with CVD (outcome) was used to conduct sensitivity analysis. Methods: 2 x 2 tables were constructed with data from 3 studies (part 2 of table below). A vector defining the proportion of confounder (smoking) among exposed [prop (Smoking+|MDS+)], unexposed [prop (Smoking+|MDS-)] and risk ratio associating smoking status with CVD (part 1) using historical data was deduced. Extracted data was added to online bias analysis tool ( https://sites.google.com/site/biasanalysis/ ) to calculate crude as well as mantel-haenszel (MH) relative risk (RR) adjusted for smoking. Results: RRs unadjusted for smoking status for studies 1, 2 and 3 were 1.31, 1.34 and 2.21, respectively, signifying increased risk of CVD in MDS patients (part 3). Upon adjustment for smoking status, MH-RR for MDS-CVD relationship was 0.95, 0.97 for studies 1 and 2 respectively, signifying no increased CVD risk and 1.59 for study 3 signifying increased CVD risk but lower upon adjustment. Conclusions: Making inference of MDS-CVD association without accounting for smoking status can blur effects and at times result in false associations. Given ambiguity in results from these 3 studies, further evidence is needed to better assess MDS-CVD relationship. A simple online tool allows estimating nonrandom errors, assess magnitude and direction of biases, and help clinicians/researchers quantify these biases for better interpretation of observational data in a time efficient manner. Other bias analyses for these studies will be presented. [Table: see text]