Tootfinder

jung: JUNG and javax class dependencies (2012)
A network of software class dependency within the JUNG 2.0.1 and javax 1.6.0.7 library namespaces edu.uci.ics.jung and java/javax. Nodes represent classes and a directed edge indicates a dependency of one class on another.
This network has 6120 nodes and 138706 edges.
Tags: Technological, Software, Unweighted

Understanding Physical Properties of Unseen Deformable Objects by Leveraging Large Language Models and Robot Actions
Changmin Park, Beomjoon Lee, Haechan Jung, Haejin Jung, Changjoo Nam
https://arxiv.org/abs/2506.03760

Understanding Physical Properties of Unseen Deformable Objects by Leveraging Large Language Models and Robot Actions
In this paper, we consider the problem of understanding the physical properties of unseen objects through interactions between the objects and a robot. Handling unseen objects with special properties such as deformability is challenging for traditional task and motion planning approaches as they are often with the closed world assumption. Recent results in Large Language Models (LLMs) based task planning have shown the ability to reason about unseen objects. However, most studies assume rigid o…

Agree to Disagree! - Jung und trans: Was bringen Hormone? - Die ganze Doku | ARTE
https://www.arte.tv/de/videos/118858-001-A/agree-to-disagree/
Treffsicher dem Thema genähert, ist mein Eindruck. Auch gut debunked.

jung: JUNG and javax class dependencies (2012)
A network of software class dependency within the JUNG 2.0.1 and javax 1.6.0.7 library namespaces edu.uci.ics.jung and java/javax. Nodes represent classes and a directed edge indicates a dependency of one class on another.
This network has 6120 nodes and 138706 edges.
Tags: Technological, Software, Unweighted

jung: JUNG and javax class dependencies (2012)
A network of software class dependency within the JUNG 2.0.1 and javax 1.6.0.7 library namespaces edu.uci.ics.jung and java/javax. Nodes represent classes and a directed edge indicates a dependency of one class on another.
This network has 6120 nodes and 138706 edges.
Tags: Technological, Software, Unweighted

Reconstructing North Korea's Plutonium Production History with Bayesian Inference-Based Reprocessing Waste Analysis
Benjamin Jung, Johannes Bosse, Malte G\"ottsche
https://arxiv.org/abs/2506.03865

Reconstructing North Korea's Plutonium Production History with Bayesian Inference-Based Reprocessing Waste Analysis
Although North Korea's nuclear program has been the subject of extensive scrutiny, estimates of its fissile material stockpiles remain fraught with uncertainty. In potential future disarmament agreements, inspectors may need to use nuclear archaeology methods to verify or gain confidence in a North Korean fissile material declaration. This study explores the potential utility of a Bayesian inference-based analysis of the isotopic composition of reprocessing waste to reconstruct the operating hi…

Ich konnte heute die Fütterung eines Jung-Spechts beobachten. #naturePhotography

Von der Kalkscheune bis zur STATION Berlin: Die re:publica ist jung geblieben, ich bin älter geworden. Ich schwelge ein wenig in nostalgischen Erinnerungen und habe mich gefreut, viele Bekannte wenn auch kurz getroffen zu haben. Der letzte Teil meines #rp25 Fazits

Scaling Out Chip Interconnect Networks with Implicit Sequence Numbers
Giyong Jung, Saeid Gorgin, John Kim, Jungrae Kim
https://arxiv.org/abs/2507.01988 htt…

Scaling Out Chip Interconnect Networks with Implicit Sequence Numbers
As AI models outpace the capabilities of single processors, interconnects across chips have become a critical enabler for scalable computing. These processors exchange massive amounts of data at cache-line granularity, prompting the adoption of new interconnect protocols like CXL, NVLink, and UALink, designed for high bandwidth and small payloads. However, the increasing transfer rates of these protocols heighten susceptibility to errors. While mechanisms like Cyclic Redundancy Check (CRC) and …

Als ich noch jung war, da warb Bauknecht in nahezu täglicher Fernsehwerbung mit dem Claim: »Bauknecht weiß, was Frauen wünschen«. Und nein, die haben weder Dildos noch Rechte im Angebot gehabt, nur Küchenmaschinen, die der Ehemann seiner Frau kaufen sollte, damit sie ihren Platz in der Küche einnimmt.
Seitdem ist eine Menge geschehen, und das meiste davon war nötig.

MythTriage: Scalable Detection of Opioid Use Disorder Myths on a Video-Sharing Platform
Hayoung Jung, Shravika Mittal, Ananya Aatreya, Navreet Kaur, Munmun De Choudhury, Tanushree Mitra
https://arxiv.org/abs/2506.00308

MythTriage: Scalable Detection of Opioid Use Disorder Myths on a Video-Sharing Platform
Understanding the prevalence of misinformation in health topics online can inform public health policies and interventions. However, measuring such misinformation at scale remains a challenge, particularly for high-stakes but understudied topics like opioid-use disorder (OUD)--a leading cause of death in the U.S. We present the first large-scale study of OUD-related myths on YouTube, a widely-used platform for health information. With clinical experts, we validate 8 pervasive myths and release …

South Korea becomes Asia's best-performing stock market in H1 2025, as shares rise following President Lee Jae-myung's pledge to allow won-based stablecoins (Song Jung-a/Financial Times)
https://www.ft.com/content/4b19bf90-4202-4fe7-8caf-d7db6deeb768…

Crypto-crazy investors make South Korea the best-performing market in Asia
New president’s pledge to allow won-based stablecoins has led to huge gains in related shares this month

🇺🇦 #NowPlaying on #BBC6Music's #GillesPeterson
Yao Su-jung:
🎵 臉兒紅 , 心兒笑 (Thanksgiving, Snowflakes)
#YaoSujung

Multi Source COVID-19 Detection via Kernel-Density-based Slice Sampling
Chia-Ming Lee, Bo-Cheng Qiu, Ting-Yao Chen, Ming-Han Sun, Fang-Ying Lin, Jung-Tse Tsai, I-An Tsai, Yu-Fan Lin, Chih-Chung Hsu
https://arxiv.org/abs/2507.01564

Multi Source COVID-19 Detection via Kernel-Density-based Slice Sampling
We present our solution for the Multi-Source COVID-19 Detection Challenge, which classifies chest CT scans from four distinct medical centers. To address multi-source variability, we employ the Spatial-Slice Feature Learning (SSFL) framework with Kernel-Density-based Slice Sampling (KDS). Our preprocessing pipeline combines lung region extraction, quality control, and adaptive slice sampling to select eight representative slices per scan. We compare EfficientNet and Swin Transformer architectur…

Noninvertible symmetry and topological holography for modulated SPT in one dimension
Jintae Kim, Yizhi You, Jung Hoon Han
https://arxiv.org/abs/2507.02324 …

Noninvertible symmetry and topological holography for modulated SPT in one dimension
We examine noninvertible symmetry (NIS) in one-dimensional (1D) symmetry-protected topological (SPT) phases protected by dipolar and exponential-charge symmetries, which are two key examples of modulated SPT (MSPT). To set the stage, we first study NIS in the $\mathbb{Z}_N \times \mathbb{Z}_N$ cluster model, extending previous work on the $\mathbb{Z}_2 \times \mathbb{Z}_2$ case. For each symmetry type (charge, dipole, exponential), we explicitly construct the noninvertible Kramers-Wannier (KW) …

Synthesizable by Design: A Retrosynthesis-Guided Framework for Molecular Analog Generation
Shuan Chen, Gunwook Nam, Yousung Jung
https://arxiv.org/abs/2507.02752

Synthesizable by Design: A Retrosynthesis-Guided Framework for Molecular Analog Generation
The disconnect between AI-generated molecules with desirable properties and their synthetic feasibility remains a critical bottleneck in computational drug and material discovery. While generative AI has accelerated the proposal of candidate molecules, many of these structures prove challenging or impossible to synthesize using established chemical reactions. Here, we introduce SynTwins, a novel retrosynthesis-guided molecular analog design framework that designs synthetically accessible molecu…

Critical Metallicity of Cool Supergiant Formation. II. Physical Origin
Po-Sheng Ou, Ke-Jung Chen
https://arxiv.org/abs/2506.01753 https://

Critical Metallicity of Cool Supergiant Formation. II. Physical Origin
This study investigates the physical origin of the critical metallicity ($Z_{\rm c}\sim 0.001$) required for the formation of cool supergiants, as revealed by stellar evolution models. Using model grids that vary in mass, metallicity, opacity, and nuclear reaction rates, we identify a threshold terminal-age main-sequence (TAMS) radius ($R_{\rm T}$) that determines whether a star of a given mass can evolve into the red supergiant (RSG) phase. Through stellar models and homology relations, we sho…

Replaced article(s) found for hep-th. https://arxiv.org/list/hep-th/new
[1/2]:
- Holography Transformer
Chanyong Park, Sejin Kim, Jung Hun Lee

Attention-Aided MMSE for OFDM Channel Estimation: Learning Linear Filters with Attention
TaeJun Ha, Chaehyun Jung, Hyeonuk Kim, Jeongwoo Park, Jeonghun Park
https://arxiv.org/abs/2506.00452

Attention-Aided MMSE for OFDM Channel Estimation: Learning Linear Filters with Attention
In orthogonal frequency division multiplexing (OFDM), accurate channel estimation is crucial. Classical signal processing based approaches, such as minimum mean-squared error (MMSE) estimation, often require second-order statistics that are difficult to obtain in practice. Recent deep neural networks based methods have been introduced to address this; yet they often suffer from high complexity. This paper proposes an Attention-aided MMSE (A-MMSE), a novel model-based DNN framework that learns t…

High-speed control and navigation for quadrupedal robots on complex and discrete terrain
Hyeongjun Kim, Hyunsik Oh, Jeongsoo Park, Yunho Kim, Donghoon Youm, Moonkyu Jung, Minho Lee, Jemin Hwangbo
https://arxiv.org/abs/2506.02835

High-speed control and navigation for quadrupedal robots on complex and discrete terrain
High-speed legged navigation in discrete and geometrically complex environments is a challenging task because of the high-degree-of-freedom dynamics and long-horizon, nonconvex nature of the optimization problem. In this work, we propose a hierarchical navigation pipeline for legged robots that can traverse such environments at high speed. The proposed pipeline consists of a planner and tracker module. The planner module finds physically feasible foothold plans by sampling-based optimization wi…

Crystals and quantum twist automorphisms
Woo-Seok Jung, Euiyong Park
https://arxiv.org/abs/2507.01306 https://arxiv.org/pdf/2507.0130…

Crystals and quantum twist automorphisms
Let $η_w$ be the quantum twist automorphism for the quantum unipotent coordinate ring $\mathrm{A}_q(\mathfrak{n}(w))$ introduced by Kimura and Oya. In this paper, we study the quantum twist automorphism $η_w$ in the viewpoint of the crystal bases theory and provide a crystal-theoretic description of $η_w$. In the case of the $*$-twisted minuscule crystals of classical finite types, we provide a combinatorial description of $η_w$ in terms of (shifted) Young diagrams. We further investigate t…

InfiniteAudio: Infinite-Length Audio Generation with Consistency
Chaeyoung Jung, Hojoon Ki, Ji-Hoon Kim, Junmo Kim, Joon Son Chung
https://arxiv.org/abs/2506.03020

InfiniteAudio: Infinite-Length Audio Generation with Consistency
This paper presents InfiniteAudio, a simple yet effective strategy for generating infinite-length audio using diffusion-based text-to-audio methods. Current approaches face memory constraints because the output size increases with input length, making long duration generation challenging. A common workaround is to concatenate short audio segments, but this often leads to inconsistencies due to the lack of shared temporal context. To address this, InfiniteAudio integrates seamlessly into existin…

HST pre-imaging of a free-floating planet candidate microlensing event
Mateusz Kapusta, Przemek Mroz, Yoon-Hyun Ryu, Andrzej Udalski, Szymon Kozlowski, Sean Terry, Michal K. Szymanski, Igor Soszynski, Pawel Pietrukowicz, Radoslaw Poleski, Jan Skowron, Krzysztof Ulaczyk, Mariusz Gromadzki, Krzysztof Rybicki, Patryk Iwanek, Marcin Wrona, Mateusz J. Mr\'oz, Michael D. Albrow, Sun-Ju Chung, Andrew Gould, Cheongho Han, Kyu-Ha Hwang, Youn Kil Jung, In-Gu Shin, Yossi Shvartzvald, Jennifer…

HST pre-imaging of a free-floating planet candidate microlensing event
High-cadence microlensing observations uncovered a population of very short-timescale microlensing events, which are believed to be caused by the population of free-floating planets (FFP) roaming the Milky Way. Unfortunately, the light curves of such events are indistinguishable from those caused by wide-orbit planets. To properly differentiate both cases, one needs high-resolution observations that would allow resolving a putative luminous companion to the lens long before or after the event. …

FlexiSAGA: A Flexible Systolic Array GEMM Accelerator for Sparse and Dense Processing
Mika Markus M\"uller, Konstantin L\"ubeck, Alexander Louis-Ferdinand Jung, Jannik Steinmetz, Oliver Bringmann
https://arxiv.org/abs/2506.01566

FlexiSAGA: A Flexible Systolic Array GEMM Accelerator for Sparse and Dense Processing
Artificial Intelligence (AI) algorithms, such as Deep Neural Networks (DNNs), have become an important tool for a wide range of applications, from computer vision to natural language processing. However, the computational complexity of DNN inference poses a significant challenge, particularly for processing on resource-constrained edge devices. One promising approach to address this challenge is the exploitation of sparsity in DNN operator weights. In this work, we present FlexiSAGA, an archi…

jung: JUNG and javax class dependencies (2012)
A network of software class dependency within the JUNG 2.0.1 and javax 1.6.0.7 library namespaces edu.uci.ics.jung and java/javax. Nodes represent classes and a directed edge indicates a dependency of one class on another.
This network has 6120 nodes and 138706 edges.
Tags: Technological, Software, Unweighted

Programmable Co-Transcriptional Splicing: Realizing Regular Languages via Hairpin Deletion
Da-Jung Cho, Szil\'ard Zsolt Fazekas, Shinnosuke Seki, Max Wiedenh\"oft
https://arxiv.org/abs/2506.23384

Programmable Co-Transcriptional Splicing: Realizing Regular Languages via Hairpin Deletion
RNA co-transcriptionality, where RNA is spliced or folded during transcription from DNA templates, offers promising potential for molecular programming. It enables programmable folding of nano-scale RNA structures and has recently been shown to be Turing universal. While post-transcriptional splicing is well studied, co-transcriptional splicing is gaining attention for its efficiency, though its unpredictability still remains a challenge. In this paper, we focus on engineering co-transcriptiona…

Photo-Thermal Actuation of Hybrid Microgels with Dual Laser Optical Tweezers
S. -H. Jung, C. Zhang, N. Stauffer, F. Scheffold, L. Isa
https://arxiv.org/abs/2507.00735

Photo-Thermal Actuation of Hybrid Microgels with Dual Laser Optical Tweezers
Soft actuators that respond to external stimuli play a fundamental role in microscale robotics, active matter, and bio-inspired systems. Among these actuators, photo-thermal hybrid microgels (HMGs) containing plasmonic nanoparticles enable rapid, spatially controlled actuation via localized heating. Understanding their dynamic behavior at the single-particle level is crucial for optimizing performance. However, traditional bulk characterization methods such as dynamic light scattering (DLS), pr…

A DNA Methylation Classification Model Predicts Organ and Disease Site
Keng-Jung Lee, Dharanya Sampath, Konstantinos Mavrommatis
https://arxiv.org/abs/2506.00146

A DNA Methylation Classification Model Predicts Organ and Disease Site
Cell-free DNA (cfDNA) analysis is a powerful, minimally invasive tool for monitoring disease progression, treatment response, and early detection. A major challenge, however, is accurately determining the tissue of origin, especially in complex or heterogeneous disease contexts. To address this, we developed a machine learning framework that leverages tissue-specific DNA methylation signatures to classify both tissue and disease origin from cfDNA data. Our model integrates methylation datasets …

"The creation of something new is not accomplished by the intellect but by the play instinct acting from inner necessity. The creative mind plays with the objects it loves."
-Carl Jung
#acting #coaching

Turbulence in Primordial Dark Matter Halos and Its Impact on the First Star Formation
Meng-Yuan Ho, Ke-Jung Chen, Pei-Cheng Tung
https://arxiv.org/abs/2505.23768

Turbulence in Primordial Dark Matter Halos and Its Impact on the First Star Formation
We present high-resolution simulations of the first star-forming clouds in 15 minihalos with masses ranging from $\sim 10^5$ to $10^7\ \text{M}_{\odot}$ at redshifts $z \sim 17 - 20$, using the \texttt{GIZMO} code. Our simulations incorporate detailed primordial gas physics and adopt initial conditions from the state-of-the-art TNG cosmological simulations. To achieve the required resolution, we apply a particle-splitting technique that increases the resolution of the original TNG data by a fac…

From Block to Byte: Transforming PCIe SSDs with CXL Memory Protocol and Instruction Annotation
Miryeong Kwon, Donghyun Gouk, Junhyeok Jang, Jinwoo Baek, Hyunwoo You, Sangyoon Ji, Hongjoo Jung, Junseok Moon, Seungkwan Kang, Seungjun Lee, Myoungsoo Jung
https://arxiv.org/abs/2506.15613

From Block to Byte: Transforming PCIe SSDs with CXL Memory Protocol and Instruction Annotation
This paper explores how Compute Express Link (CXL) can transform PCIe-based block storage into a scalable, byte-addressable working memory. We address the challenges of adapting block storage to CXL's memory-centric model by emphasizing cacheability as a key enabler and advocating for Type 3 endpoint devices, referred to as CXL-SSDs. To validate our approach, we prototype a CXL-SSD on a custom FPGA platform and propose annotation mechanisms, Determinism and Bufferability, to enhance performance…

Sturz aus 3. Stock - Todesrätsel um schöne Flugbegleiterin in Wien #News #Nachrichten

Low Overhead Allocation Sampling in a Garbage Collected Virtual Machine
Christoph Jung, C. F. Bolz-Tereick
https://arxiv.org/abs/2506.16883 https://…

Low Overhead Allocation Sampling in a Garbage Collected Virtual Machine
Compared to the more commonly used time-based profiling, allocation profiling provides an alternate view of the execution of allocation heavy dynamically typed languages. However, profiling every single allocation in a program is very inefficient. We present a sampling allocation profiler that is deeply integrated into the garbage collector of PyPy, a Python virtual machine. This integration ensures tunable low overhead for the allocation profiler, which we measure and quantify. Enabling alloca…

Making the Right Thing: Bridging HCI and Responsible AI in Early-Stage AI Concept Selection
Ji-Youn Jung, Devansh Saxena, Minjung Park, Jini Kim, Jodi Forlizzi, Kenneth Holstein, John Zimmerman
https://arxiv.org/abs/2506.17494

Making the Right Thing: Bridging HCI and Responsible AI in Early-Stage AI Concept Selection
AI projects often fail due to financial, technical, ethical, or user acceptance challenges -- failures frequently rooted in early-stage decisions. While HCI and Responsible AI (RAI) research emphasize this, practical approaches for identifying promising concepts early remain limited. Drawing on Research through Design, this paper investigates how early-stage AI concept sorting in commercial settings can reflect RAI principles. Through three design experiments -- including a probe study with ind…

Sudoku: Decomposing DRAM Address Mapping into Component Functions
Minbok Wi, Seungmin Baek, Seonyong Park, Mattan Erez, Jung Ho Ahn
https://arxiv.org/abs/2506.15918

Sudoku: Decomposing DRAM Address Mapping into Component Functions
Decomposing DRAM address mappings into component-level functions is critical for understanding memory behavior and enabling precise RowHammer attacks, yet existing reverse-engineering methods fall short. We introduce novel timing-based techniques leveraging DRAM refresh intervals and consecutive access latencies to infer component-specific functions. Based on this, we present Sudoku, the first software-based tool to automatically decompose full DRAM address mappings into channel, rank, bank gro…

Identification of Noise-Associated Glitches in KAGRA O3GK with Hveto
T. Akutsu, M. Ando, M. Aoumi, A. Araya, Y. Aso, L. Baiotti, R. Bajpai, K. Cannon, A. H. -Y. Chen, D. Chen, H. Chen, A. Chiba, C. Chou, M. Eisenmann, K. Endo, T. Fujimori, S. Garg, D. Haba, S. Haino, R. Harada, H. Hayakawa, K. Hayama, S. Fujii, Y. Himemoto, N. Hirata, C. Hirose, H. -F. Hsieh, H. -Y. Hsieh, C. Hsiung, S. -H. Hsu, K. Ide, R. Iden, S. Ikeda, H. Imafuku, R. Ishikawa, Y. Itoh, M. Iwaya, H-B. Jin, K. Jung, T…

Identification of Noise-Associated Glitches in KAGRA O3GK with Hveto
Transient noise ("glitches") in gravitational wave detectors can mimic or obscure true signals, significantly reducing detection sensitivity. Identifying and excluding glitch-contaminated data segments is therefore crucial for enhancing the performance of gravitational-wave searches. We perform a noise analysis of the KAGRA data obtained during the O3GK observation. Our analysis is performed with hierarchical veto (Hveto) which identifies noises based on the statistical time correlation between…

Doppelg\"anger Method: Breaking Role Consistency in LLM Agent via Prompt-based Transferable Adversarial Attack
Daewon Kang, YeongHwan Shin, Doyeon Kim, Kyu-Hwan Jung, Meong Hi Son
https://arxiv.org/abs/2506.14539

Doppelgänger Method: Breaking Role Consistency in LLM Agent via Prompt-based Transferable Adversarial Attack
Since the advent of large language models, prompt engineering now enables the rapid, low-effort creation of diverse autonomous agents that are already in widespread use. Yet this convenience raises urgent concerns about the safety, robustness, and behavioral consistency of the underlying prompts, along with the pressing challenge of preventing those prompts from being exposed to user's attempts. In this paper, we propose the ''Doppelgänger method'' to demonstrate the risk of an agent being hij…

A Novel Analysis Framework for Microstructural Characterization of Ferroelectric Hafnia: Experimental Validation and Application
Yoonsang Park, Jaeduck Jang, Hyangsook Lee, Kihong Kim, Kyooho Jung, Yunseong Lee, Jaewoo Lee, Eunji Yang, Sanghyun Jo, Sijung Yoo, Hyun Jae Lee, Donghoon Kim, Duk-Hyun Choe, Seunggeol Nam
https://arxi…

A Novel Analysis Framework for Microstructural Characterization of Ferroelectric Hafnia: Experimental Validation and Application
Herein, we present a novel analysis framework for grain size profile of ferroelectric hafnia to tackle critical shortcomings inherent in the current microstructural analysis. We vastly enhanced visibility of grains with ion beam treatment and performed accurate grain segmentation using deep neural network (DNN). By leveraging our new method, we discovered unexpected discrepancies that contradict previous results, such as deposition temperature (Tdep) and post-metallization annealing (PMA) depen…

Demonstrating Interoperable Channel State Feedback Compression with Machine Learning
Dani Korpi, Rachel Wang, Jerry Wang, Abdelrahman Ibrahim, Carl Nuzman, Runxin Wang, Kursat Rasim Mestav, Dustin Zhang, Iraj Saniee, Shawn Winston, Gordana Pavlovic, Wei Ding, William J. Hillery, Chenxi Hao, Ram Thirunagari, Jung Chang, Jeehyun Kim, Bartek Kozicki, Dragan Samardzija, Taesang Yoo, Andreas Maeder, Tingfang Ji, Harish Viswanathan

Demonstrating Interoperable Channel State Feedback Compression with Machine Learning
Neural network-based compression and decompression of channel state feedback has been one of the most widely studied applications of machine learning (ML) in wireless networks. Various simulation-based studies have shown that ML-based feedback compression can result in reduced overhead and more accurate channel information. However, to the best of our knowledge, there are no real-life proofs of concepts demonstrating the benefits of ML-based channel feedback compression in a practical setting, …

Personalized LLM Decoding via Contrasting Personal Preference
Hyungjune Bu, Chanjoo Jung, Minjae Kang, Jaehyung Kim
https://arxiv.org/abs/2506.12109 https:…

Personalized LLM Decoding via Contrasting Personal Preference
As large language models (LLMs) are progressively deployed in various real-world applications, personalization of LLMs has become increasingly important. While various approaches to LLM personalization such as prompt-based and training-based methods have been actively explored, the development of effective decoding-time algorithms remains largely overlooked, despite their demonstrated potential. In this paper, we propose CoPe (Contrasting Personal Preference), a novel decoding-time approach app…

Integrated bright source of polarization-entangled photons using lithium niobate photonic chips
Changhyun Kim, Hansol Kim, Minho Choi, Junhyung Lee, Yongchan Park, Sunghyun Moon, Jinil Lee, Hyeon Hwang, Min-Kyo Seo, Yoon-Ho Kim, Yong-Su Kim, Hojoong Jung, Hyounghan Kwon
https://arxiv.org/abs/2506.23625

Integrated bright source of polarization-entangled photons using lithium niobate photonic chips
Quantum photonics has rapidly advanced as a key area for developing quantum technologies by harnessing photons' inherent quantum characteristics, particularly entanglement. Generation of entangled photon pairs, known as Bell states, is crucial for quantum communications, precision sensing, and quantum computing. While bulk quantum optical setups have provided foundational progress, integrated quantum photonic platforms now offer superior scalability, efficiency, and integrative potential. In th…

Phenylalanine modification in plasma-driven biocatalysis revealed by solvent accessibility and reactive dynamics in combination with protein mass spectrometry
Hanna-Friederike Poggemann, Sabrina Klopsch, Simon Homann, Tim Dirks, Sina Sch\"akermann, Julia E. Bandow, Timo Jacob, Christoph Jung
https://arxiv.org/abs/2506.20205…

Phenylalanine modification in plasma-driven biocatalysis revealed by solvent accessibility and reactive dynamics in combination with protein mass spectrometry
Biocatalysis is an emerging field that provides an environmentally friendly alternative to conventional catalysis, but still it faces some challenges. One of the major difficulties for biocatalysts that require reactive species like H2O2 as co-substrates lies in the concentration of these reactive species. On the one hand, they are used as reactants, but on the other hand, they inactivate the enzymes at high concentrations. When utilizing non-thermal plasma to deliver H2O2 for biocatalysis, it …

d-Boolean algebras and their bitopological representation
Hang Yang, Dexue Zhang
https://arxiv.org/abs/2505.17806 https://arxiv.org/p…

d-Boolean algebras and their bitopological representation
We present a Stone duality for bitopological spaces in analogy to the duality between Stone spaces and Boolean algebras, in the same vein as the duality between d-sober bitopological spaces and spatial d-frames established by Jung and Moshier. Precisely, we introduce the notion of d-Boolean algebras and prove that the category of such algebras is dually equivalent to the category of Stone bitopological spaces, which are compact and zero-dimensional bitopological spaces satisfying the T0 separat…

software_dependencies: Software dependencies (2010)
Several networks of software dependencies. Nodes represent libraries and a directed edge denotes a library dependency on another.
This network has 1040 nodes and 5363 edges.
Tags: Technological, Software, Unweighted
https://networks.skewed.d…

On quadratic persistence and Pythagoras numbers of totally real projective varieties
Jong In Han, Jaewoo Jung, Euisung Park
https://arxiv.org/abs/2506.13247

On quadratic persistence and Pythagoras numbers of totally real projective varieties
In this paper, we study the relationship between quadratic persistence and the Pythagoras number of totally real projective varieties. Building upon the foundational work of Blekherman et al. in arXiv:1902.02754, we extend their characterizations of arithmetically Cohen-Macaulay varieties with next-to-maximal quadratic persistence to arbitrary case. Our main result classifies totally real non-aCM varieties of codimension $c$ and degree $d$ that exhibit next-to-maximal quadratic persistence in t…

MOA-2022-BLG-091Lb and KMT-2024-BLG-1209Lb: Microlensing planets detected through weak caustic-crossing signals
Cheongho Han, Chung-Uk Lee, Andrzej Udalski, Ian A. Bond, Hongjing Yang, Michael D. Albrow, Sun-Ju Chung, Andrew Gould, Youn Kil Jung, Kyu-Ha Hwang, Yoon-Hyun Ryu, Yossi Shvartzvald, In-Gu Shin, Jennifer C. Yee, Weicheng Zang, Tanagodchaporn Inyanya, Sang-Mok Cha, Doeon Kim, Dong-Jin Kim, Seung-Lee Kim, Dong-Joo Lee, Yongseok Lee, Byeong-Gon Park, Richard W. Pogge, Przemek Mr…

MOA-2022-BLG-091Lb and KMT-2024-BLG-1209Lb: Microlensing planets detected through weak caustic-crossing signals
The light curves of the microlensing events MOA-2022-BLG-091 and KMT-2024-BLG-1209 exhibit anomalies with very similar features. These anomalies appear near the peaks of the light curves, where the magnifications are moderately high, and are distinguished by weak caustic-crossing features with minimal distortion while the source remains inside the caustic. To achieve a deeper understanding of these anomalies, we conducted a comprehensive analysis of the lensing events. We carried out binary-len…

A simplified algorithmic realization of Galois actions on special values of modular functions
Ja Kyung Koo, Dong Hwa Shin, Dong Sung Yoon
https://arxiv.org/abs/2506.14139

A simplified algorithmic realization of Galois actions on special values of modular functions
We propose an explicit and practical algorithm for computing Galois conjugates and irreducible polynomials for special values of modular functions evaluated at CM points associated with imaginary quadratic orders. Our approach builds upon the theory of extended form class groups developed by Jung et al., offering a refinement of earlier methods by Stevenhagen and Cho, respectively.

KMT-2022-BLG-0086: Another binary-lens binary-source microlensing event
Sun-Ju Chung, Kyu-Ha Hwang, Jennifer C. Yee, Andrew Gould, Ian A. Bond, Hongjing Yang, Michael D. Albrow, Youn Kil Jung, Cheongho Han, Yoon-Hyun Ryu, In-Gu Shin, Yossi Shvartzvald, Weicheng Zang, Sang-Mok Cha, Dong-Jin Kim, Seung-Lee Kim, Chung-Uk Lee, Dong-Joo Lee, Yongseok Lee, Byeong-Gon Park, Richard W. Pogge, Fumio Abe, David P. Bennett, Aparna Bhattacharya, Akihiko Fukui, Ryusei Hamada, Yuki Hirao, Stela Ishi…

KMT-2022-BLG-0086: Another binary-lens binary-source microlensing event
We present the analysis of a microlensing event KMT-2022-BLG-0086 of which the overall light curve is not described by a binary-lens single-source (2L1S) model, which suggests the existence of an extra lens or an extra source. We found that the event is best explained by the binary-lens binary-source (2L2S) model, but the 2L2S model is only favored over the triple-lens single-source (3L1S) model by $Δχ^{2} \simeq 9$. Although the event has noticeable anomalies around the peak of the light cur…

Replaced article(s) found for physics.app-ph. https://arxiv.org/list/physics.app-ph/new
[1/1]:
- Membrane phononic crystals for high-Qm mechanical defect modes in piezoelectric aluminum nitride
Ciers, Nindito, Jung, Pfeifer, Dadgar, Strittmatter, Wieczorek
…

Persistent Homology of Music Network with Three Different Distances
Eunwoo Heo, Byeongchan Choi, Myung ock Kim, Mai Lan Tran, Jae-Hun Jung
https://arxiv.org/abs/2506.13595

Persistent Homology of Music Network with Three Different Distances
Persistent homology has been widely used to discover hidden topological structures in data across various applications, including music data. To apply persistent homology, a distance or metric must be defined between points in a point cloud or between nodes in a graph network. These definitions are not unique and depend on the specific objectives of a given problem. In other words, selecting different metric definitions allows for multiple topological inferences. In this work, we focus on apply…

Deutsche Polizisten schützen die Faschisten
Samstag, 17.05.2025 in Herford
@…
Danke für die Hintergrundinformationen :antifa:
https://mastodon.bida.im/@rkowl/11433…

Science for Peace and the need for Civil Clauses at universities and civilian research institutions
J. Altmann, U. Amaldi, M. Barone, A. Bassalat, M. Bona, J. Beullens, H. Brand, S. Brentjes, D. Britzger, J. Ellis, S. Franchoo, A. Giammanco, A. Glazov, C. Heck, H. Jung, S. Kraml, L. L\"onnblad, M. Mangano, M. Renneberg, Th. Riebe, A. Sabio-Vera, R. Sanders, J. Scheffran, M. Schmelling, T. Schucker, T. Suzuki, A. Tanasijczuk, I. Tsakov, D. Valls-Gabaud, M. Walker

Science for Peace and the need for Civil Clauses at universities and civilian research institutions
After the end of World War II, the commitment to confine scientific activities in universities and research institutions to peaceful and civilian purposes has entered, in the form of {\it Civil Clauses}, the charters of many research institutions and universities. In the wake of recent world events, the relevance and scope of such Civil Clauses has been questioned in reports issued by some governments and by the EU Commission, a development that opens the door to a possible blurring of the dist…

Machine Learning-Based Estimation of Monthly GDP
Yonggeun Jung
https://arxiv.org/abs/2506.14078 https://arxiv.org/pdf/2506.14078

Machine Learning-Based Estimation of Monthly GDP
This paper proposes a scalable framework to estimate monthly GDP using machine learning methods. We apply Multi-Layer Perceptron (MLP), Long Short-Term Memory networks (LSTM), Extreme Gradient Boosting (XGBoost), and Elastic Net regression to map monthly indicators to quarterly GDP growth, and reconcile the outputs with actual aggregates. Using data from China, Germany, the UK, and the US, our method delivers robust performance across varied data environments. Benchmark comparisons with prior U…

Numerical Modeling of n-Hexane Pyrolysis with an Optimized Kinetic Mechanism in a Hydrogen Plasma Reactor
Subin Choi, Chanmi Jung, Dae Hoon Lee, Jeongan Choi, Jaekwang Kim
https://arxiv.org/abs/2506.13789

Numerical Modeling of n-Hexane Pyrolysis with an Optimized Kinetic Mechanism in a Hydrogen Plasma Reactor
The physicochemical mechanisms underlying the pyrolysis of n-hexane in a high temperature Ar-H2 environment were investigated for plasma pyrolysis process. An optimal chemical kinetics model was developed using the Reaction Mechanism Generator (RMG), an automated tool for constructing reaction mechanisms. This model was validated through 0-D analyses, where simulation result were compared with existing kinetic models (LLNL,JetSurf) and experimental data from conventional n-hexane pyrolysis. Sub…

Aerodynamics and Aeroacoustics of da Vinci's Aerial Screw
Suryansh Prakhar, Jung-Hee Seo, Rajat Mittal
https://arxiv.org/abs/2506.10223 https://…

Aerodynamics and Aeroacoustics of da Vinci's Aerial Screw
Leonardo da Vinci's aerial screw, conceived in the 15th century, represents one of the earliest conceptualizations of lift-generating rotary flight. Despite its historical significance, the aerodynamic and aeroacoustic performance of this rotor has received limited scientific attention. In this study, we employ direct numerical simulations to analyze the aerodynamic forces and acoustic emissions of a modernized da Vinci aerial screw design across a range of Reynolds numbers (2000, 4000, and 800…

A Taylor Series Approximation Model for Characterizing the Output Resistance of a GFET
Xiomara Ribero-Figueroa, Anibal Pacheco-Sanchez, Tzu-Jung Huang, David Jim\'enez, Ivan Puchades, Reydezel Torres-Torres
https://arxiv.org/abs/2506.10592

A Taylor Series Approximation Model for Characterizing the Output Resistance of a GFET
The mobility-degradation-based model for the drain-to-source or output resistance of a graphene field-effect-transistor is linearized here using a Taylor series approximation. This simplification is shown to be valid from magnitudes of the gate voltage not significantly higher than the Dirac voltage, and it enables the analytical determination of the transconductance parameter, the voltage related to residual charges, and a bias-independent series resistance of the GFET. Furthermore, a continuo…

X-ray Polarization Detection of the Pulsar Wind Nebula in G21.5-0.9 with IXPE
Niccol\`o Di Lalla, Nicola Omodei, Niccol\`o Bucciantini, Jack T. Dinsmore, Nicol\`o Cibrario, Stefano Silvestri, Josephine Wong, Patrick Slane, Tsunefumi Mizuno, Michela Negro, Roger W. Romani, Riccardo Ferrazzoli, Stephen Chi-Yung Ng, Miltiadis Michailidis, Yi-Jung Yang, Fei Xie, Martin C. Weisskopf, Philip Kaaret, Iv\'an Agudo, L. A. Antonelli, Matteo Bachetti, Luca Baldini, Wayne H. Baumgartner, Ronal…

X-ray Polarization Detection of the Pulsar Wind Nebula in G21.5-0.9 with IXPE
We present the X-ray polarization observation of G21.5-0.9, a young Galactic supernova remnant (SNR), conducted with the Imaging X-ray Polarimetry Explorer (IXPE) in October 2023, with a total livetime of approximately 837 ks. Using different analysis methods, such as a space-integrated study of the entire region of the PWN and a space-resolved polarization map, we detect significant polarization from the pulsar wind nebula (PWN) at the center of the SNR, with an average polarization degree of …

Acoustic-Driven Surface Cleaning with Millimeter-Sized Bubbles at Translational Resonance
Yan Jun Lin, Zhengyang Liu, Sunghwan Jung
https://arxiv.org/abs/2506.06581

Acoustic-Driven Surface Cleaning with Millimeter-Sized Bubbles at Translational Resonance
Traditional surface cleaning methods often suffer from drawbacks such as chemical harshness, potential for surface damage, and high energy consumption. This study investigates an alternative approach: acoustic-driven surface cleaning using millimeter-sized bubbles excited at low, sub-cavitation frequencies. We identify and characterize a distinct translational resonance of these bubbles, occurring at significantly lower frequencies (e.g., 50 Hz for 1.3 mm diameter bubbles) than the Minnaert res…

The Memory Paradox: Why Our Brains Need Knowledge in an Age of AI
Barbara Oakley, Michael Johnston, Ken-Zen Chen, Eulho Jung, Terrence J. Sejnowski
https://arxiv.org/abs/2506.11015

The Memory Paradox: Why Our Brains Need Knowledge in an Age of AI
In the age of generative AI and ubiquitous digital tools, human cognition faces a structural paradox: as external aids become more capable, internal memory systems risk atrophy. Drawing on neuroscience and cognitive psychology, this paper examines how heavy reliance on AI systems and discovery-based pedagogies may impair the consolidation of declarative and procedural memory -- systems essential for expertise, critical thinking, and long-term retention. We review how tools like ChatGPT and calc…

CXL-GPU: Pushing GPU Memory Boundaries with the Integration of CXL Technologies
Donghyun Gouk, Seungkwan Kang, Seungjun Lee, Jiseon Kim, Kyungkuk Nam, Eojin Ryu, Sangwon Lee, Dongpyung Kim, Junhyeok Jang, Hanyeoreum Bae, Myoungsoo Jung
https://arxiv.org/abs/2506.15601

CXL-GPU: Pushing GPU Memory Boundaries with the Integration of CXL Technologies
This work introduces a GPU storage expansion solution utilizing CXL, featuring a novel GPU system design with multiple CXL root ports for integrating diverse storage media (DRAMs and/or SSDs). We developed and siliconized a custom CXL controller integrated at the hardware RTL level, achieving two-digit nanosecond roundtrip latency, the first in the field. This study also includes speculative read and deterministic store mechanisms to efficiently manage read and write operations to hide the endp…

MATER: Multi-level Acoustic and Textual Emotion Representation for Interpretable Speech Emotion Recognition
Hyo Jin Jon, Longbin Jin, Hyuntaek Jung, Hyunseo Kim, Donghun Min, Eun Yi Kim
https://arxiv.org/abs/2506.19887

MATER: Multi-level Acoustic and Textual Emotion Representation for Interpretable Speech Emotion Recognition
This paper presents our contributions to the Speech Emotion Recognition in Naturalistic Conditions (SERNC) Challenge, where we address categorical emotion recognition and emotional attribute prediction. To handle the complexities of natural speech, including intra- and inter-subject variability, we propose Multi-level Acoustic-Textual Emotion Representation (MATER), a novel hierarchical framework that integrates acoustic and textual features at the word, utterance, and embedding levels. By fusi…

GPS Spoofing Attacks on AI-based Navigation Systems with Obstacle Avoidance in UAV
Ji Hyuk Jung, Mi Yeon Hong, Ji Won Yoon
https://arxiv.org/abs/2506.08445

GPS Spoofing Attacks on AI-based Navigation Systems with Obstacle Avoidance in UAV
Recently, approaches using Deep Reinforcement Learning (DRL) have been proposed to solve UAV navigation systems in complex and unknown environments. However, despite extensive research and attention, systematic studies on various security aspects have not yet been conducted. Therefore, in this paper, we conduct research on security vulnerabilities in DRL-based navigation systems, particularly focusing on GPS spoofing attacks against the system. Many recent basic DRL-based navigation systems fun…

On Energy-Efficient Passive Beamforming Design of RIS-Assisted CoMP-NOMA Networks
Muhammad Umer, Muhammad Ahmed Mohsin, Aamir Mahmood, Haejoon Jung, Haris Pervaiz, Mikael Gidlund, Syed Ali Hassan
https://arxiv.org/abs/2506.17189

On Energy-Efficient Passive Beamforming Design of RIS-Assisted CoMP-NOMA Networks
This paper investigates the synergistic potential of reconfigurable intelligent surfaces (RIS) and non-orthogonal multiple access (NOMA) to enhance the energy efficiency and performance of next-generation wireless networks. We delve into the design of energy-efficient passive beamforming (PBF) strategies within RIS-assisted coordinated multi-point (CoMP)-NOMA networks. Two distinct RIS configurations, namely, enhancement-only PBF (EO) and enhancement & cancellation PBF (EC), are proposed and an…

SAIL: Faster-than-Demonstration Execution of Imitation Learning Policies
Nadun Ranawaka Arachchige, Zhenyang Chen, Wonsuhk Jung, Woo Chul Shin, Rohan Bansal, Pierre Barroso, Yu Hang He, Yingyang Celine Lin, Benjamin Joffe, Shreyas Kousik, Danfei Xu
https://arxiv.org/abs/2506.11948

SAIL: Faster-than-Demonstration Execution of Imitation Learning Policies
Offline Imitation Learning (IL) methods such as Behavior Cloning are effective at acquiring complex robotic manipulation skills. However, existing IL-trained policies are confined to executing the task at the same speed as shown in demonstration data. This limits the task throughput of a robotic system, a critical requirement for applications such as industrial automation. In this paper, we introduce and formalize the novel problem of enabling faster-than-demonstration execution of visuomotor p…

Why Do Stars Turn Red? II. Solutions of Steady-State Stellar Structure
Po-Sheng Ou, Ke-Jung Chen
https://arxiv.org/abs/2506.07630 https://

Why Do Stars Turn Red? II. Solutions of Steady-State Stellar Structure
To investigate the physical origin of red giants (RGs) and red supergiants (RSGs), we construct steady-state models of stellar envelopes by explicitly solving the stellar structure equations, with boundary conditions set at the stellar surface and the hydrogen burning shell. For comparison, we consider both polytropic and realistic models. Polytropic models adopt a polytropic equation of state (EOS) and neglect energy transport, while realistic models incorporate radiative and convective energy…

Containerized In-Storage Processing and Computing-Enabled SSD Disaggregation
Miryeong Kwon, Donghyun Gouk, Eunjee Na, Jiseon Kim, Junhee Kim, Hyein Woo, Eojin Ryu, Hyunkyu Choi, Jinwoo Baek, Hanyeoreum Bae, Mahmut Kandemir, Myoungsoo Jung
https://arxiv.org/abs/2506.06769

Containerized In-Storage Processing and Computing-Enabled SSD Disaggregation
ISP minimizes data transfer for analytics but faces challenges in adaptation and disaggregation. We propose DockerSSD, an ISP model leveraging OS-level virtualization and lightweight firmware to enable containerized data processing directly on SSDs. Key features include Ethernet over NVMe for network-based ISP management and Virtual Firmware for secure, efficient container execution. DockerSSD supports disaggregated storage pools, reducing host overhead and enhancing large-scale services like L…

🇺🇦 #NowPlaying on BBCRadio3's #NightTracks
Kevin Puts, Ji Su Jung, Baltimore Symphony Orchestra & Marin Alsop:
🎵 Marimba Concerto: II. Broad and Deliberate
#KevinPuts #JiSuJung #BaltimoreSymphonyOrchestra #MarinAlsop
https://open.spotify.com/track/0BSTnV555VRGLB1wlMgLmk