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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Sampriti Soor B. S. Daya Sagar School of Computer Engineering Kalinga Institute of Industrial Technology Bhubaneswar India Systems Science and Informatics Unit Indian Statistical Institute Bangalore India

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Watershed partitioning, following a maximal vertex-cut constraint, ensures each basin is strictly isolated from its neighboring basins. This partition is composed of watershed arcs positioned between pairs of adjacent basins. When these arcs create a connected partition, applying watershed partition on an arc-graph ensures that the corresponding arcs of watershed points in the arc-graph still maintain this connected partition. This crucial property is leveraged in the proposed iterative watershed partition method for extracting hierarchical partition lines in an image. The method effectively extracts river basins from SRTM DEM data of the Indian state Uttarakhand, revealing a well-structured hierarchy of catchment basins.

关键词： Image segmentation Geoscience and remote sensing Watersheds Object detection Gray-scale Rivers Iterative methods

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Causal Structure Learning from Imperfect Longitudinal Data in Healthcare 11

Causal Structure Learning from Imperfect Longitudinal Data i...

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11th IEEE International Conference on Healthcare informatics, ICHI 2023

作者： Yang, Haoyu Tourani, Roshan Li, Jia Caraballo, Pedro Steinbach, Michael Kumar, Vipin Simon, Gyorgy University of Minnesota Dept. of Computer Science and Engineering Minneapolis United States University of Minnesota Institute for Health Informatics Minneapolis United States Mayo Clinic Dept. of Internal Medicine Rochester United States

ISBN: (纸本)9798350302639

Causal Structure Discovery (CSD) is the task of learning the set of underlying causal relationships from observational data. Due to their computational scalability and flexibility, a recently developed class of CSD methods, NOTEARS, based on a formulation allowing for continuous optimization, is gaining popularity. However, this formulation can lead to incorrect edge orientations when little/no likelihood advantage is conferred upon any edge orientation, e.g., a → b → c versus c → b → a. In longitudinal data, like electronic health records (EHRs), temporal relationships are observable among many pairs of variables. Such temporal relationship is imperfect but still suggest an orientation since causal effects cannot travel backwards in time. Following this idea, we propose methods to incorporate precedence constraints into continuous optimization-based CSD methods. Experiments on both a synthetic and two real-world datasets validate the effectiveness of the proposed precedence constraints. © 2023 IEEE.

关键词： Machine learning

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NPRportrait 1.0:A three-level benchmark for non-photorealistic rendering of portraits

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Computational Visual Media 2022年第3期8卷 445-465页

作者： Paul L.Rosin Yu-Kun Lai David Mould Ran Yi Itamar Berger Lars Doyle Seungyong Lee Chuan Li Yong-Jin Liu Amir Semmo Ariel Shamir Minjung Son Holger Winnemöller School of Computer Science and Informatics Cardiff UniversityCardiffUK School of Computer Science Carleton UniversityOttawaCanada Department of Computer Science and Technology Tsinghua UniversityBeijingChina Reichman University(the Interdisciplinary Center) HerzliyaIsrael Department of Computer Science and Engineering Pohang University of Science and TechnologyPohangRepublic of Korea Lambda Labs Inc.San FranciscoUSA Hasso Plattner Institute University of PotsdamPotsdamGermany Multimedia Processing Laboratory Samsung Advanced Institute of TechnologySuwonRepublic of Korea Adobe Systems Inc.San JoseUSA

Recently,there has been an upsurge of activity in image-based non-photorealistic rendering(NPR),and in particular portrait image stylisation,due to the advent of neural style transfer(NST).However,the state of performance evaluation in this field is poor,especially compared to the norms in the computer vision and machine learning ***,the task of evaluating image stylisation is thus far not well defined,since it involves subjective,perceptual,and aesthetic *** make progress towards a solution,this paper proposes a new structured,threelevel,benchmark dataset for the evaluation of stylised portrait *** criteria were used for its construction,and its consistency was validated by user ***,a new methodology has been developed for evaluating portrait stylisation algorithms,which makes use of the different benchmark levels as well as annotations provided by user studies regarding the characteristics of the *** perform evaluation for a wide variety of image stylisation methods(both portrait-specific and general purpose,and also both traditional NPR approaches and NST)using the new benchmark dataset.

关键词： non-photorealistic rendering(NPR) image stylization style transfer portrait evaluation benchmark

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Research Progress On Name Data Networking To Achieve A Superior National Product In Indonesia 8

Research Progress On Name Data Networking To Achieve A Super...

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8th International Conference on Wireless and Telematics, ICWT 2022

作者： Syambas, Nana Rachmana Juhana, Tutun Hendrawan Mulyana, Eueung Edward, Ian Joseph Matheus Situmorang, Hamonangan Mayasari, Ratna Negara, Ridha Muldina Yovita, Leanna Vidya Wibowo, Tody Ariefianto Ahdan, Syaiful Nurkahfi, Galih Nugraha Nurhayati, Ade Mulya, Hafiz Budiana, Mochamad Soebagja Institute of Technology School of Electrical Engineering and Informatics Bandung Bandung Indonesia Telkom University School of Electrical Engineering Bandung Indonesia Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia Lampung35132 Indonesia Bandung Institute of Technology School of Electrical Engineering and Informatics Bandung40132 Indonesia Faculty of Engineering Institut Teknologi Telkom Jakarta Jakarta11710 Indonesia

ISBN: (数字)9781665451222

ISBN: (纸本)9781665451222

Global traffic data are proliferating, including in Indonesia. The number of internet users in Indonesia reached 205 million in January 2022. This data means that 73.7% of Indonesia's population has used the internet. The median internet speed for mobile phones in Indonesia is 15.82 Mbps, while the median internet connection speed for Wi-Fi in Indonesia is 20.13 Mbps. As predicted by many, real-time traffic such as multimedia streaming dominates more than 79% of traffic on the internet network. This condition will be a severe challenge for the internet network, which is required to improve the Quality of Experience (QoE) for user mobility, such as reducing delay, data loss, and network costs. However, IP-based networks are no longer efficient at managing traffic. Named Data Network (NDN) is a promising technology for building an agile communication model that reduces delays through a distributed and adaptive name-based data delivery approach. NDN replaces the 'where' paradigm with the concept of 'what'. User requests are no longer directed to a specific IP address but to specific content. This paradigm causes responses to content requests to be served by a specific server and can also be served by the closest device to the requested data. NDN router has CS to cache the data, significantly reducing delays and improving the internet network's quality of Service (QoS). Motivated by this, in 2019, we began intensive research to achieve a national flagship product, an NDN router with different functions from ordinary IP routers. NDN routers have cache, forwarding, and routing functions that affect data security on name-based networks. Designing scalable NDN routers is a new challenge as NDN requires fast hierarchical name-based lookups, perpackage data field state updates, and large-scale forward tables. We have a research team that has conducted NDN research through simulation, emulation, and testbed approaches using virtual machines to get the best NDN router design be

关键词： Testbeds

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Development of a Website-Based Financial Transaction Management System Using Agile with the Scrum Framework 10

Development of a Website-Based Financial Transaction Managem...

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10th International Conference on ICT for Smart Society, ICISS 2023

作者： Latifah, Ayu Ramdan, Galih Muhammad Sidik, Muhamad Lutfhi Farid Faturrohman, Nadhif Nursyaban, Dzikri Ramelan, Agus Rahman, Fachrur Razy School of Electrical and Informatics Engineering Bandung Institute of Technology Bandung Indonesia Institut Teknologi Garut Department of Computer Science Garut Indonesia Universitas Sebelas Maret Electrical Engineering Departement Solo Indonesia Metal Industry Polytechnic of Morowali Department of Installation and Electrical Engineering Central Sulawesi Indonesia

ISBN: (纸本)9798350339543

The process of managing financial transactions, especially in the education sector, is still mostly carried out conventionally, so it has the potential to cause many risks, such as loss or damage to documents related to difficulties in searching for data as needed, transaction processes that take quite a long time, financial records that are not properly recorded. Well, it is prone to discrepancies between the nominal filing and the nominal disbursed conventional representations of financial statements that make the stakeholder evaluation process uncomfortable, and many other things. Therefore this research was conducted to build a website-based information system that can prevent this from happening in the future. The method used in the development of this information system is the Agile method with the Scrum framework. The Scrum framework consists of five stages, starting from Initiate, Plan, and Estimate, Implement, Review and Retrospect, and Release. This website was built using the Javascript programming language using the Vue JS framework for the Front-end. With this website-based application, it is hoped that transaction activities can be carried out better and correctly without being limited by space and time. © 2023 IEEE.

关键词： Websites

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Wireless Localization with Space-Time Coded Reconfigurable Intelligent Surfaces

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IEEE Transactions on Antennas and Propagation 2025年

作者： Gholami, Mehdi Khajavi, Soheil Neshat, Mohammad Tewes, Simon Sezgin, Aydin University of Tehran School of Electrical and Computer Engineering College of Engineering Tehran Iran University of Sussex School of Engineering and Informatics Falmer United Kingdom Ruhr University Bochum Institute of Digital Communication Systems Bochum Germany

In this paper, a novel approach for wireless localization is proposed and experimentally validated that leverages space-time coded reconfigurable intelligent surfaces (RIS). It is demonstrated that applying proper single-bit codes to each RIS element enables accurate determination of the direction of arrival (DOA) at the receiver. Moreover, we introduce different scenarios for which such technique can be used for localization. By incorporating RIS, a passive component, the method significantly reduces the complexity found in previous localization techniques. In addition, the use of 1-bit codes minimizes hardware requirements, offering a reliable and low-cost solution for localization in advanced telecommunications networks. © 1963-2012 IEEE.

关键词： Space time adaptive processing

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Effectiveness of non-invasive brain stimulation on depressive symptoms targeting prefrontal cortex in functional magnetic resonance imaging studies:a combined systematic review and meta-analysis

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Psychoradiology 2024年第1期4卷 123-134页

作者： Yao Xiao Shuai Dong Chunyu Pan Huiling Guo Lili Tang Xizhe Zhang Fei Wang Early Intervention Unit Department of PsychiatryAffiliated Nanjing Brain HospitalNanjing Medical UniversityNanjing 210029China Functional Brain Imaging Institute of Nanjing Medical University Nanjing 210029China School of Biomedical Engineering and Informatics Nanjing Medical UniversityNanjing 211166China School of Computer Science and Engineering Northeastern UniversityShenyang 110167China

The prefrontal cortex(PFC)is a critical non-invasive brain stimulation(NIBS)target for treating ***,the alterations of brain activations post-intervention remain inconsistent and the clinical moderators that could improve symptomatic effectiveness are *** study aim was to systematically review the effectiveness of NIBS on depressive symptoms targeting PFC in functional magnetic resonance imaging(fMRI)*** our study,we delivered a combined activation likelihood estimation(ALE)meta-analysis and *** November 2020,three databases(PubMed,Web of Science,EMBASE)were searched and 14 studies with a total sample size of 584 were included in the ALE meta-analysis;after NIBS,four clusters in left cerebrum revealed significant activation while two clusters in right cerebrum revealed significant deactivation(P<0.001,cluster size>150 mm3).Eleven studies were statistically reanalyzed for depressive symptoms pre–post active-NIBS and the pooled effect size was very large[(d=1.82,95%CI(1.23,2.40)];significant moderators causing substantial heterogeneity(Chi squared=75.25,P<0.01;I2=87%)were detected through subgroup analysis and univariate *** meta-regression was then conducted accordingly and the model suggested good fitness(Q=42.32,P<0.01).In all,NIBS targeting PFC balanced three core depressive-related neurocognitive networks(the salience network,the default mode network,and the central executive network);the striatum played a central role and might serve as a candidate treatment biomarker;gender difference,treatment-resistant condition,comorbidity,treatment duration,and localization all contributed to moderating depressive symptoms during *** high-quality,multi-center randomized controlled trails delivering personalized NIBS are needed for clinical practice in the future.

关键词： non-invasive brain stimulation prefrontal cortex depressive symptom functional magnetic resonance imaging activation likelihood estimation meta-analysis meta-regression

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GAN-generated Synthetic Data and SVM-based Feature Selection for Improved Cardiovascular Disease Prediction

GAN-generated Synthetic Data and SVM-based Feature Selection...

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Medical Technologies National Conference (TIPTEKNO)

作者： Amel Sulaiman Mandan Nidhal Mohsin Hazzaa Oktay Yildiz Computer Science Department Informatics Institute Gazi University Ankara Turkey Department of Computer Engineering Faculty of Engineering Gazi University Ankara Turkey

Early diagnosis requires cardiovascular disease forecasting. Past patient interests can improve machine learning predictions. This study uses a Generative Adversarial Network (GAN) to augment data to address the issue of insufficient datasets. Our objective is to use the GAN and feature selection (FS) to tackle the issue of class imbalance. The study assesses the efficacy of three different machine learning (ML) algorithms in predicting coronary artery disease (CAD). The UCI repository provided the Z-Alizadeh sani dataset for our analysis. A GAN was used to balance an imbalanced dataset. We used GAN to augment data and synthesise data to improve the models. Support Vector Machine (SVM) as feature selection tool was used to extract more effective attributes. We trained and tested CAD prediction using machine learning algorithms using 5-fold cross validation. We compared the machine-learning algorithm’s outcomes with and without GAN-based data enhancement and feature selection to evaluate its predicted accuracy. According to results GAN and feature selection improved accuracy, sensitivity, and specificity for all algorithms, suggesting that generated data and selected attributes can identify positive and negative cases.

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State-based Sandbox Tool for Distributed Malware Detection with Avoid Techniques 13

State-based Sandbox Tool for Distributed Malware Detection w...

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13th International Conference on Dependable Systems, Services and Technologies, DESSERT 2023

作者： Rehida, Pavlo Markowsky, George Sachenko, Anatoliy Savenko, Oleg Khmelnytskyi National University Department of Computer Engineering and Information Systems Khmelnytskyi Ukraine Kennesaw State University Department of Software Engineering and Game Development Marietta United States Kazimierz Pulaski University of Technology and Humanities Department of Informatics Radom Poland Research Institute for Intelligent Computer Systems West Ukrainian National Unversity Ternopil Ukraine

ISBN: (纸本)9798350396119

This paper deals with the problem of detecting the malware by using emulation approach. Modern malware include various avoid techniques, to hide its anomaly actions. Advantages of using sandbox and emulation technologies are described. Various anti-emulation techniques that are used in modern malware considered. Obfuscation as one primary approach to hide malware malicious actions described and discussed. State of emulator is presented, and the advantages of its usage are covered. Distributed model for malware detection is considered. Basic emulator and its current capabilities presented. Prepared files that represent malware are described. Experimental results for developed files that differs with included avoid techniques are presented. Disadvantages of proposed approach is described. Future research and sandbox improvement are described. © 2023 IEEE.

关键词： anti-emulation techniques malware detection obfuscation techniques sandbox

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SkinSAM: Adapting the Segmentation Anything Model for Skin Cancer Segmentation

SkinSAM: Adapting the Segmentation Anything Model for Skin C...

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Medical Imaging 2024: Image Perception, Observer Performance, and Technology Assessment

作者： Hu, Mingzhe Li, Yuheng Yang, Xiaofeng Department of Computer Science and Informatics Emory University AtlantaGA United States Department of Biomedical Engineering Emory University AtlantaGA United States Department of Radiation Oncology Winship Cancer Institute School of Medicine Emory University AtlantaGA United States

ISBN: (纸本)9781510671621

Skin cancer is a prevalent and potentially fatal disease that requires accurate and efficient diagnosis and treatment. Although manual tracing is the current standard in clinics, automated tools are desired to reduce human labor and improve accuracy. However, developing such tools is challenging due to the highly variable appearance of skin cancers and complex objects in the background. In this paper, we present SkinSAM, a fine-tuned model based on the Segment Anything Model that showed outstanding segmentation performance. The models are validated on HAM10000 dataset which includes 10015 dermatoscopic images. While larger models (ViT_L, ViT_H) performed better than the smaller one (ViT_b), the finetuned model (ViT_b_finetuned) exhibited the greatest improvement, with a Mean pixel accuracy of 0.945, Mean dice score of 0.8879, and Mean IoU score of 0.7843. Among the lesion types, vascular lesions showed the best segmentation results. Our research demonstrates the great potential of adapting SAM to medical image segmentation tasks. © 2024 SPIE.

关键词： Diagnosis

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