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15th International Conference on Information, Intelligence, Systems and Applications, IISA 2024

作者： Fensterseifer Filho, Evandro L. R. Assuncao, Joaquim V. C. Fontoura, Lisandra M. Federal University of Santa Maria - Ufsm Graduate Program in Computer Science RS Santa Maria Brazil Federal University of Santa Maria - Ufsm Applied Computing Department RS Santa Maria Brazil

ISBN: (纸本)9798350368833

Software projects are affected by technical knowledge as well as the personality of the team. Such factors can reduce or increase the software quality and development speed. For successful task allocation, it is essential to consider the skills and profile of each developer, thus maximizing their productivity. In projects with large teams, task allocation can be challenging, and the help of tools can facilitate its execution. In this work, we propose an intelligent approach for allocating software development tasks suitable to the profile of developers. From the literature, we define the appropriate skills and technical profiles for a development team, and the assessment is based on the developer completing a questionnaire. We developed a recommendation system to suggest tasks to be allocated to developers, employing text processing techniques. For validation, 495 tasks were used from an actual project developing simulator software for military training. The recommended allocations were evaluated by the project developers and used to improve the system. Validations showed that the developed approach makes consistent and coherent task recommendations to developers according to the developer profile, as participants agree with the recommendation for 76% of tasks. © 2024 IEEE.

关键词： Project management

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Seafloor Imaging Maps by Incorporating Side Scan Sonar Technology on Hybrid Autonomous Underwater Glider 6

Seafloor Imaging Maps by Incorporating Side Scan Sonar Techn...

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6th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2023

作者： Atmaja, Ardian Budi Kusuma Hidayat, Egi Muhammad Idris Riyanto Trilaksono, Bambang Siregar, Simon Habibullah, Natsir School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Institut Teknologi Bandung Telkom University Doctoral Program of Electrical Engineering Department Computer Engineering Faculty of Applied Science Indonesia

ISBN: (纸本)9798350358346

This research aims to construct a two-dimensional image to represent an underwater geometry map with a Side Scan Sonar (SSS) mounted on a Hybrid Autonomous Underwater Glider (HAUG). Building the underwater map has two stages of the process. The first stage is preprocessing which includes Time-varying gains (TVG), slant range correction, and ground range correction. The second is HAUG navigation, the movement of HAUG orientation to the angle and distance of SSS readings and plotting the geometry of the grid map. With these two stages, a two-dimensional grid map will be formed. Meanwhile, the 3D plot utilizes slant range and ground range correction to obtain the surface height of the bottom of the pool. From the experiments conducted to conduct mapping in the pool, two-dimensional and three-dimensional visual forms of the pool floor and pool walls were produced. The results of the estimated measurement of the width of the pool obtained 14.05 meters and the height of the pool 3.199 meters with an SSS beam angle of 58 degrees. © 2023 IEEE.

关键词： Geometry

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Esophageal microbiome correlates with post-esophagectomy anastomotic leak in cancer patients

ESMO Gastrointestinal Oncology

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ESMO Gastrointestinal Oncology 2025年 8卷 100172-100172页

作者： R. Naddaf H. Shmilovich S. Carasso R. Keshet-David R. Herren T. Gefen T. Goshen-Lago Y. Zwang I. Livyatan N. Shental O. Haberfeld R. Straussman S.R. Markar M. Nilsson H. Kashtan I. Ben-Aharon N. Geva-Zatorsky Rappaport Faculty of Medicine Technion Haifa Israel Division of Surgery Rabin Medical Center Petach Tikva Israel Department of Division of Oncology Rambam Health Care Center Haifa Israel Department of Molecular Cell Biology Weizmann Institute of Science Rehovot Israel Department of Computer Science and Applied Mathematics Weizmann Institute of Science Rehovot Israel Department of Mathematics and Computer Science The Open University of Israel Ra’anana Israel Department of Thoracic Surgery Rambam Health Care Center Haifa Israel Nuffield Department of Surgery University of Oxford Oxford UK Division of Surgery Department of Clinical Science Intervention and Technology Karolinska Institute Stockholm Sweden Department of Upper Abdominal Diseases Karolinska University Hospital Stockholm Sweden CIFAR Humans & the Microbiome Program CIFAR Toronto Canada

Background Despite continuous improvement in long-term survival after esophagectomy, potential serious post-operative complications, such as anastomotic leaks (ALs), still occur. Several risk factors for ALs have been proposed, including environmental factors. Our main objective was to examine the correlation of esophageal tumor microbiome composition and functional profile with ALs. Additionally, we analyzed the microbiome of esophageal tumors and their potential correlation with clinical features of the patients. Materials and methods Surgical specimens of esophageal tumors and adjacent normal tissues were collected from consecutive patients who underwent an esophagectomy. Formalin-fixed paraffin-embedded (FFPE) tissue samples were processed using 16S ribosomal DNA multiple fragments amplicon sequencing to characterize bacterial microbiome composition. The tumor and normal tissue microbiome and bacterial functional profile were analyzed based on the clinical outcome of ALs. Results Out of 60 patients who met the inclusion criteria, 52 (86.7%) patients had both normal adjacent tissue (NAT) and tumor (T) FFPE samples included with sufficient bacterial DNA extracted for analysis. A total of 28% of participants had esophageal ALs. Proportion tests [ P < 0.05, false discovery rate (FDR) < 0.25] revealed operational taxonomic units (OTUs) significantly present in T samples as opposed to NAT samples, as well as significantly present OTUs in patients with AL as opposed to patients without AL complication. Conclusions In this study, we provide a profile of the understudied esophageal microbiome and its connection to ALs. Our results can provide potential clues on how to avoid ALs by considering a patient’s personal microbiome when providing perioperative care.

关键词： microbiome tumor microbiome esophageal cancer esophagectomy anastomotic leak

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3-D reconstruction of digital outcrop model based on multiple view images and terrestrial laser scanning 16

3-D reconstruction of digital outcrop model based on multipl...

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16th Brazilian Symposium on GeoInformatics, GEOINFO 2015

作者： Da Silva, Reginaldo Macedônio Veronez, Maurício Roberto Gonzaga, Luiz Tognoli, Francisco M.W. De Souza, Marcelo Kehl Inocencio, Leonardo Campos VIZLab Advanced Visualization Laboratory UNISINOS São LeopoldoRS Brazil PPGEO Graduate Program on Geology UNISINOS São LeopoldoRS Brazil PIPCA Applied Computer Science Graduate Program - UNISINOS São LeopoldoRS Brazil

This paper presents a comparative study about 3D reconstruction based on active and passive sensors, mainly LiDAR - Terrestrial Laser Scanner (TLS) and raster images (photography), respectively. An accuracy analysis has been performed in the positioning of outcrop point clouds obtained by both techniques. To make the comparison feasible, datasets are composed by point clouds generated from multiple images in different poses using a consumer digital camera and directly by terrestrial laser scanner. After preprocessing stages to obtain these point clouds, both are compared, through the positional discrepancies and standard deviation. A preliminary analysis has been shown the feasible employment of digital image jointly 3D reconstruction method for digital outcrop modeling, concerning with data acquisition at low cost without significantly lost of accuracy when compared with LiDAR. © 2015 National Institute for Space Research INPE All rights reserved.

关键词： Image reconstruction

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The differential geometry of shape from shading: Biology reveals curvature structure

The differential geometry of shape from shading: Biology rev...

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IEEE computer Society Conference on computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Benjamin Kunsberg Steven W. Zucker Applied Mathematics Program Yale University USA Departments of Computer Science and Applied Mathematics Yale University USA

Shape from shading is a classical inverse problem in computer vision. We introduce a novel mathematical formulation for calculating local surface shape based on covariant derivatives, rather than the customary integral minimization or P.D.E approaches. Motivated by neurobiology, we introduce the shading flow field (the tangent map to the image isophotes) between the image and the surface levels. Just as in the perceptual organization of texture, we use the parallel transport of our shading flow field to move the isophote field at different points on the unknown surface to a single point, amassing restrictions on our surface curvatures. Under simplifying assumptions we solve exactly for the light source/surface pairs needed for a local image patch to have a given shading flow. The magnitude of the brightness gradient then restricts this family to a single light source and surface estimate pair, up to the concave/convex ambiguity and an additional elliptical/saddle ambiguity. Example calculations illustrate our approach.

关键词： Light sources Mathematical model Equations Shape Vectors Brightness computer vision

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Prediction of Post-COVID-19 Pandemic Learning Mode Preferences Using Machine Learning 14

Prediction of Post-COVID-19 Pandemic Learning Mode Preferenc...

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Pratondo, Agus Novianty, Astri Putro, Budi Laksono Komala Sari, Siska Telkom University School of Applied Sciences Department of Multimedia Engineering Bandung Indonesia Telkom University School of Electrical Engineering Department of Computer Engineering Bandung Indonesia Indonesia University of Education Department of Computer Science Education Bandung Indonesia Telkom University School of Applied System Diploma Program of Information System Bandung Indonesia

ISBN: (纸本)9798350335095

The COVID-19 epidemic has had a huge impact on the educational landscape, prompting the adoption of online and remote learning as viable alternatives to conventional in-person instruction. In order to create effective educational methods as institutions prepare for the post-pandemic period, it is essential to understand students' preferences for various learning modes. With the aid of machine learning techniques, this study seeks to forecast preferences for learning styles in post-pandemic higher education. The study made use of a dataset compiled from a wide range of college students, which included information on the institution type (public or private), program type (bachelor's or diploma), academic discipline (science or humanities), gender, year of study, internet use, communication costs, comorbidity status, vaccination history, gadget and laptop ownership, and preferred learning mode (online, in-person, or both). For the aim of prediction, a Support Vector Machine (SVM) was used. Its kernel functions included linear, polynomial, radial basis function (RBF), and sigmoid. Performance criteria like accuracy, precision, recall, and F1 score were used to assess the models after the dataset was randomly partitioned into training and testing sets. The findings showed that for identifying the preferred mode of learning, SVM with the RBF kernel had the highest prediction accuracy (91.67%). Further proving the RBF kernel's efficacy, the confusion matrix analysis showed that high values in the diagonal represented accurate predictions for each of the three classes (both online and onsite). The results imply that machine learning approaches, in particular SVM with the RBF kernel, may accurately forecast students' preferences for learning modes in the post-pandemic situation. In a post-pandemic society, the findings provide insightful information that may be used to build adaptable and inclusive learning models and put them into practice. © 2023 IEEE.

关键词： Support vector machines

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Ibaqpy: A scalable Python package for baseline quantification in proteomics leveraging SDRF metadata

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Journal of Proteomics 2025年 317卷

作者： Zheng, Ping Audain, Enrique Webel, Henry Dai, Chengxin Klein, Joshua Hitz, Marc-Phillip Sachsenberg, Timo Bai, Mingze Perez-Riverol, Yasset Chongqing Key Laboratory of Big Data for Bio Intelligence Chongqing University of Posts and Telecommunications Chongqing China Institute of Medical Genetics University Medicine Oldenburg Carl von Ossietzky University Oldenburg Germany The Novo Nordisk Foundation Center for Biosustainability Technical University of Denmark Lyngby Denmark State Key Laboratory of Proteomics Beijing Proteome Research Center National Center for Protein Sciences (Beijing) Beijing Institute of Life Omics Beijing China Program for Bioinformatics Boston University Boston United States Department of Computer Science Applied Bioinformatics University of Tübingen Tübingen Germany Institute for Bioinformatics and Medical Informatics University of Tübingen Tübingen Germany European Molecular Biology Laboratory European Bioinformatics Institute Wellcome Genome Campus Cambridge United Kingdom

Intensity-based absolute quantification (iBAQ) is essential in proteomics as it allows for the assessment of a protein's absolute abundance in various samples or conditions. However, the computation of these values for increasingly large-scale and high-throughput experiments, such as those using DIA, TMT, or LFQ workflows, poses significant challenges in scalability and reproducibility. Here, we present ibaqpy (https://***/bigbio/ibaqpy), a Python package designed to compute iBAQ values efficiently for experiments of any scale. Ibaqpy leverages the Sample and Data Relationship Format (SDRF) metadata standard to incorporate experimental metadata into the quantification workflow. This allows for automatic normalization and batch correction while accounting for key aspects of the experimental design, such as technical and biological replicates, fractionation strategies, and sample conditions. Designed for large-scale proteomics datasets, ibaqpy can also recompute iBAQ values for existing experiments when an SDRF is available. We showcased ibaqpy's capabilities by reanalyzing 17 public proteomics datasets from ProteomeXchange, covering HeLa cell lines with 4921 samples and 5766 MS runs, quantifying a total of 11,014 proteins. In our reanalysis, ibaqpy is a key component in automating reproducible quantification, reducing manual effort and making quantitative proteomics more accessible while supporting FAIR principles for data reuse. Significance: Proteomics studies often rely on intensity-based absolute quantification (iBAQ) to assess protein abundance across various biological conditions. Despite its widespread use, computing iBAQ values at scale remains challenging due to the increasing complexity and volume of proteomics experiments. Existing tools frequently lack metadata integration, limiting their ability to handle experimental design intricacies such as replicates, fractions, and batch effects. Our work introduces ibaqpy, a scalable Python package that lev

关键词： Big data Bioinformatics Data integration Proteomics Quantification

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Inertial Hegselmann-Krause systems

Inertial Hegselmann-Krause systems

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American Control Conference (ACC)

作者： Bernard Chazelle Chu Wang Department of Computer Science Princeton University Program in Applied and Computational Mathematics Princeton University

ISBN: (纸本)9781467386838

We derive an energy bound for inertial Hegselmann-Krause (HK) systems, which we define as a variant of the classic HK model in which the agents can change their weights arbitrarily at each step. We use the bound to prove the convergence of HK systems with closed-minded agents, which settles a conjecture of long standing. This paper also introduces anchored HK systems and show their equivalence to the symmetric heterogeneous model.

关键词： Convergence Communication networks Kinetic theory Protocols Nickel Mobile communication Turning

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Centimetre-scale electron diffusion in photoactive organic heterostructures

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NATURE 2018年第7690期554卷 77-+页

作者： Burlingame, Quinn Coburn, Caleb Che, Xiaozhou Panda, Anurag Qu, Yue Forrest, Stephen R. Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor Michigan 48109 USA Department of Physics University of Michigan Ann Arbor Michigan 48109 USA Applied Physics Program University of Michigan Ann Arbor Michigan 48109 USA Department of Materials Science and Engineering University of Michigan Ann Arbor Michigan 48109 USA

The unique properties of organic semiconductors, such as flexibility and lightness, are increasingly important for information displays, lighting and energy generation. But organics suffer from both static and dynamic disorder, and this can lead to variable-range carrier hopping(1,2), which results in notoriously poor electrical properties, with low electron and hole mobilities and correspondingly short charge-diffusion lengths of less than a micrometre(3,4). Here we demonstrate a photoactive (light-responsive) organic heterostructure comprising a thin fullerene channel sandwiched between an electron-blocking layer and a blended donor: C-70 fullerene heterojunction that generates charges by dissociating excitons. Centimetre-scale diffusion of electrons is observed in the fullerene channel, and this can be fitted with a simple electron diffusion model. Our experiments enable the direct measurement of charge diffusivity in organic semiconductors, which is as high as 0.83 +/- 0.07 square centimetres per second in a C-60 channel at room temperature. The high diffusivity of the fullerene combined with the extraordinarily long charge-recombination time yields diffusion lengths of more than 3.5 centimetres, orders of magnitude larger than expected for an organic system.

关键词： Electrical and electronic engineering Electronic and spintronic devices Electronic devices Electronic properties and materials

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EPC information services with No-SQL datastore for the Internet of Things

EPC information services with No-SQL datastore for the Inter...

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2014 IEEE International Conference on RFID, IEEE RFID 2014

作者： Le, Tuan Dinh Kim, Seong Hoon Nguyen, Minh Hoang Kim, Daeyoung Shin, Seung Young Lee, Kyung Eun Da Rosa Righi, Rodrigo Deparment of Computer Science KAIST Daejeon Korea Republic of Samsung Electronics Korea Republic of Graduate Program in Applied Computing Universidade Do Vale Do Rio Dos Sinos São Leopoldo Brazil

ISBN: (纸本)9781479935871

With the emergence of the Internet of Things (IoT) vision, RFID technology has attracted more and more interests from many industries. In the EPCglobal standard which standardizes RFID architectural framework and interfaces, the Electronic Product Code Information System (EPCIS) - the repository in the RFID network - plays a pivotal role in storing dynamic and historical RFID trajectory data, well-tailored to supply chain applications. However, in the IoT era, EPCIS should be capable of storing a large amount of realtime and continuous time-series RFID data in a scalable manner. Therefore, in this paper, we analyze the requirements and current design of EPCIS and report current limitations of SQL-based approaches for IoT applications. To cope with these limitations, we explore a NoSQL-based approach for EPCIS in the IoT and propose a column-family-based data model and customization for Cassandra-based EPCIS. Using real-world implementation, we also conduct a performance comparison between MySQL and Cassandra in different deployment scenarios (i.e., physical and virtual machines). As a result, we show the benefits of using Cassandra datastore for EPCIS in the IoT in terms of response time, throughput, and flexibility. © 2014 IEEE.

关键词： Internet of things

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