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1CONN Creative Reklam Ajansı
Sektörünüzle ilgili genel ve yerel bilgileri büyük bir titizlikle araştırıyor, sizin için gerçekleştireceğimiz çalışmalarımıza bu bilgiler ışığında yön veriyoruz. İlk düşündüğümüz; “Biz, bu markaya ne katabiliriz?”
ANSAC: Adaptive Non-minimal Sample and Consensus
While RANSAC-based methods are robust to incorrect image correspondences (outliers), their hypothesis generators are not robust to correct image correspondences (inliers) with positional error (noise). This slows down their convergence because hypotheses drawn from a minimal set of noisy inliers can deviate significantly from the optimal model. This work addresses this problem by introducing ANSAC, a RANSAC-based estimator that accounts for noise by adaptively using more than the minimal number of correspondences required to generate a hypothesis. ANSAC estimates the inlier ratio (the fraction of correct correspondences) of several ranked subsets of candidate correspondences and generates hypotheses from them. Its hypothesis-generation mechanism prioritizes the use of subsets with high inlier ratio to generate high-quality hypotheses. ANSAC uses an early termination criterion that keeps track of the inlier ratio history and terminates when it has not changed significantly for a period of time. The experiments show that ANSAC finds good homography and fundamental matrix estimates in a few iterations, consistently outperforming state-of-the-art methods.
High-Performance Astrophysical Simulations and Analysis with Python
The usage of the high-level scripting language Python has enabled new mechanisms for data interrogation, discovery and visualization of scientific data. We present yt, an open source, community-developed astrophysical analysis and visualization toolkit for data generated by high-performance computing (HPC) simulations of astrophysical phenomena. Through a separation of responsibilities in the underlying Python code, yt allows data generated by incompatible, and sometimes even directly competing, astrophysical simulation platforms to be analyzed in a consistent manner, focusing on physically relevant quantities rather than quantities native to astrophysical simulation codes. We present on its mechanisms for data access, capabilities for MPI-parallel analysis, and its implementation as an in situ analysis and visualization tool.
One-Class Slab Support Vector Machine
This work introduces the one-class slab SVM (OCSSVM), a one-class classifier that aims at improving the performance of the one-class SVM. The proposed strategy reduces the false positive rate and increases the accuracy of detecting instances from novel classes. To this end, it uses two parallel hyperplanes to learn the normal region of the decision scores of the target class. OCSSVM extends one-class SVM since it can scale and learn non-linear decision functions via kernel methods. The experiments on two publicly available datasets show that OCSSVM can consistently outperform the one-class SVM and perform comparable to or better than other state-of-the-art one-class classifiers.
It is not enough to give your moderation rules to ChatGPT: Policy-as-Prompt Moderation and Its Potential Impacts on Community Governance
Content moderation practices and governance paradigms are changing rapidly, as fewer human moderators are deployed as `experts' by social media companies in a centralized manner. Instead, the companies are focusing more on community approaches, relying on volunteers to provide accurate information and make correct decisions. In decentralized moderation, communities have always relied on volunteers, updated community guidelines, and internal discussions thereof. For both content moderation paradigms, Artificial Intelligence (AI) seems like it could help ease moderation burdens of time, mental health, and accuracy. One possible way to operationalize AI in content moderation is a `policy-as-prompt'' approach, where the policy is formulated as a natural-language prompt and then passed to a large language model (LLM). This model then aids in moderation tasks. In this paper, we briefly lay out the technical and governance properties of this approach, and argue that its limitations lead to specific risks and harms that have to be addressed. Towards alleviating them, we lay out multiple considerations towards more effective prompt governance, but ultimately find that writing prompts alone …
High-Entropy Polar Regions Around the First Protostars
We report on simulations of the formation of the first stars in the Universe, where we identify regions of hot atomic gas (fH2 < 10-6) at densities above 10-14 g/cc, heated to temperatures ranging between 3000 and 8000 K. Within this temperature range atomic hydrogen is unable to cool effectively. We describe the kinetic and thermal characteristics of these regions and investigate their origin. We find that these regions, while small in total mass fraction of the cloud, may be dynamically important over the accretion timescale for the central clump in the cloud, particularly as a chemical, rather than radiative, mechanism for clearing the polar regions of the accretion disk of material and terminating accretion along these directions. These inherently three-dimensional effects stress the need for multi-dimensional calculations of protostellar accretion for reliable predictions of the masses of the very first stars.
Combining Simulations and Spectroscopy to Design Protective Coatings on Sulfide Solid Electrolytes
Sulfide solid electrolytes are attractive for all-solid-state batteries because of their high Li-ion conductivity and favorable processability, but their practical use is limited by electrochemical instability and moisture-induced degradation. Molecular surface coatings offer a scalable strategy to improve humidity tolerance and interfacial stability, yet there is limited understanding of the molecular-level factors governing surface interactions. By combining large-scale atomistic simulations enabled by a machine-learning potential with targeted experiments, we present a comprehensive framework for designing molecular coatings on Li$_6$PS$_5$Cl (LPSCl). Using a PET-MAD interatomic potential fine-tuned on an r$^2$SCAN reference dataset covering LPSCl surfaces, molecular adsorbates, and their interactions, we model surface adsorption of carboxylic (CA), sulfonic (SA), and phosphonic (PA) acids with alkyl chains of varying lengths and the interaction of these coated surfaces with water at finite temperature. The simulations show that lithiated head groups generally exhibit more favorable adsorption energies. Impedance spectroscopy shows that the lithiated coatings maintain 40--55\% …
CHIPS: A Service for Collecting, Organizing, Processing, and Sharing Medical Image Data in the Cloud
Web browsers are increasingly used as middleware platforms offering a central access point for service provision. Using backend containerization, RESTful APIs, and distributed computing allows for complex systems to be realized that address the needs of modern compute intense environments. In this paper, we present a web-based medical image data and information management software platform called CHIPS (Cloud Healthcare Image Processing Service). This cloud-based services allows for authenticated and secure retrieval of medical image data from resources typically found in hospitals, organizes and presents information in a modern feed-like interface, provides access to a growing library of plugins that process these data, allows for easy data sharing between users and provides powerful 3D visualization and real-time collaboration. Image processing is orchestrated across additional cloud-based resources using containerization technologies.
Large Scale Dynamo in a Primordial Accretion Flow -- An Interpretation from Hydrodynamic Simulation
Without an existing large scale coherent magnetic field in the early Universe, Population III (PopIII) stars would likely rotate at or near break-up speed. In this work, focusing on the accretion phase of PopIII stars, we investigate the possibility of generating a coherent magnetic field through large scale dynamo processes, as well as the corresponding field saturation level. Using results from hydrodynamic simulations, we demonstrate that primordial accretion disks are turbulent with a Shakura-Sunyaev disk parameter $α_{ss} \gtrsim 10^{-3}$, and evidence helical turbulence with a dynamo number $\vert D_{αΩ} \vert \gg 10$. The presence of helical turbulence at these levels allows large scale dynamo modes to grow, and the saturation level is determined by the amount of net helicity remaining in the dynamo-active regions (a.k.a. the quenching problem). %We demonstrate that the magnetic field can reach approximate equipartition, with $B/B_{\rm eq} \sim 3$, indicating that the dynamo quenching problem could be alleviated through an accretion flow. We demonstrate that, if the accretion could successfully alleviate the quenching problem, the magnetic field can reach approximate …
Face Verification in Polar Frequency Domain: a Biologically Motivated Approach
We present a novel local-based face verification system whose components are analogous to those of biological systems. In the proposed system, after global registration and normalization, three eye regions are converted from the spatial to polar frequency domain by a Fourier-Bessel Transform. The resulting representations are embedded in a dissimilarity space, where each image is represented by its distance to all the other images. In this dissimilarity space a Pseudo-Fisher discriminator is built. ROC and equal error rate verification test results on the FERET database showed that the system performed at least as state-of-the-art methods and better than a system based on polar Fourier features. The local-based system is especially robust to facial expression and age variations, but sensitive to registration errors.
Large Scale SfM with the Distributed Camera Model
We introduce the distributed camera model, a novel model for Structure-from-Motion (SfM). This model describes image observations in terms of light rays with ray origins and directions rather than pixels. As such, the proposed model is capable of describing a single camera or multiple cameras simultaneously as the collection of all light rays observed. We show how the distributed camera model is a generalization of the standard camera model and describe a general formulation and solution to the absolute camera pose problem that works for standard or distributed cameras. The proposed method computes a solution that is up to 8 times more efficient and robust to rotation singularities in comparison with gDLS. Finally, this method is used in an novel large-scale incremental SfM pipeline where distributed cameras are accurately and robustly merged together. This pipeline is a direct generalization of traditional incremental SfM; however, instead of incrementally adding one camera at a time to grow the reconstruction the reconstruction is grown by adding a distributed camera. Our pipeline produces highly accurate reconstructions efficiently by avoiding the need for many bundle …
Dentastik Klinik Yönetimi
Kliniğinizin tüm dünyası Tek bir akış. İlk temastan son kontrole. Satıştan tedaviye. Birbirine bağlı her an, tek ekosistemde.
1Klinik CMS Web Yönetim Sistemi
Yeni Nesil Klinik Deneyimi. Bilim, teknoloji ve estetiği modern hasta deneyimiyle bir araya getiriyoruz. Dijital planlama, kişiye özel tedavi yaklaşımı ve güçlü hasta iletişimi.
