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International Conference on Big Data and Smart Computing (BIGCOMP)

作者： Doyeong Hwang Minji Jeon Jaewoo Kang Department of Computer Science and Engineering Korea University Seoul Republic of Korea Interdisciplinary Graduate Program in Bioinformatics Korea University Seoul Republic of Korea

ISBN: (数字)9781728160344

ISBN: (纸本)9781728160351

Drug-Induced Liver Injury (DILI) is a major cause of failed drug candidates in clinical trials and withdrawal of approved drugs from the market. Therefore, machine learning-based DILI prediction can be key in increasing the success rate of drug discovery because drug candidates that are predicted to potentially induce liver injury can be rejected before clinical trials. However, existing DILI prediction models mainly focus on the chemical structures of drugs. Since we cannot determine whether a drug will cause liver injury based solely on its structure, DILI prediction based on the transcriptional effect of a drug on a cell is necessary. In this paper, we propose GLIT which is a model that uses transcriptional response data and chemical structures and can be used for drug-induced liver injury prediction. GLIT learns the embedding vectors of drug structures and drug-induced gene expression profiles using graph attention networks in a biological knowledge graph for predicting DILI. GLIT outperformed a baseline model that uses only drug structure information by 7% and 19.2% in terms of correct classification rate (CCR) and Matthews correlation coefficient (MCC), respectively. In addition, we conducted a literature survey to confirm whether the class labels of drugs, in the unknown DILI class, predicted by GLIT are correct.

关键词： Drugs Gene expression Neural networks Injuries Liver Predictive models Biological system modeling

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Reachability Analysis of Nonlinear Discrete-Time Systems Using Polyhedral Relaxations and Constrained Zonotopes

arXiv

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arXiv 2025年

作者： Rego, Brenner S. Raffo, Guilherme V. Terra, Marco H. Scott, Joseph K. Department of Chemical and Biomolecular Engineering Georgia Institute of Technology 311 Ferst Dr. AtlantaGA30318 United States Department of Electrical and Computer Engineering University of São Paulo SP São Carlos13566-590 Brazil Department of Electronics Engineering the Graduate Program in Electrical Engineering Federal University of Minas Gerais MG Belo Horizonte31270-901 Brazil

This paper presents a novel algorithm for reachability analysis of nonlinear discrete-time systems. The proposed method combines constrained zonotopes (CZs) with polyhedral relaxations of factorable representations of nonlinear functions to propagate CZs through nonlinear functions, which is normally done using conservative linearization techniques. The new propagation method provides better approximations than those resulting from linearization procedures, leading to significant improvements in the computation of reachable sets in comparison to other CZ methods from the literature. Numerical examples highlight the advantages of the proposed algorithm. © 2025, CC BY-NC-ND.

关键词： Numerical methods

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Experimental Evaluation of a Checklist-Based Inspection Technique to Verify the Compliance of Software Systems with the Brazilian General Data Protection Law

引用

Empirical Software engineering 2025年第5期30卷

作者： Cerqueira, Diego André de Mello, Rafael Maiani da Costa, Jéssica Soares Travassos, Guilherme Horta Systems Engineering and Computer Science Graduate Program – Federal University of Rio de Janeiro Rio de Janeiro Brazil Alexander Von Humboldt Institute for Internet and Society Berlin Germany Computing Institute – Federal University of Rio de Janeiro Rio de Janeiro Brazil

Context: Recent laws to ensure the security and protection of personal data establish new software requirements. Consequently, new technologies are needed to guarantee software quality under the perception of privacy and protection of personal data. Therefore, we created a checklist-based inspection technique (LGPDCheck) to support the identification of defects in software systems based on the principles established by the Brazilian General Data Protection Law (LGPD). Objective: To evaluate the effectiveness and efficiency of LGPDCheck for verifying privacy and data protection (PDP) in software artifacts and systems under execution compared to ad-hoc techniques. Method: To assess LGPDCheck and ad-hoc techniques experimentally through two quasi-experiments (two factors, two treatments). The first, in vitro, inspected the vision and requirements specifications artifacts of an integrated accounting information management system. The second, in vivo, they inspected a public and available mobile application used to support legal services to citizens in Brazil. Results: The studies indicate that LGPDCheck improves inspection consistency, detects more PDP defects compared to ad-hoc inspections, is more efficient than ad-hoc inspections when inspecting vision and requirements specifications artifacts, and is comparable in effectiveness to ad-hoc inspections. After initial use, LGPDCheck received positive feedback and was perceived as a useful and easy-to-use technique for detecting PDP defects. The professionals strongly recommended using LGPDCheck for this purpose. Conclusion: LGPDCheck is a feasible checklist-based inspection technique for detecting PDP defects in software systems. However, further studies are necessary to strengthen confidence in LGPDCheck as a recommended technique for privacy and data protection in software artifacts and systems in Brazil. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Software quality

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Effects of Hydrogen on Endurance Characteristics in NAND Flash Memories

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ECS Advances 2022年第4期1卷 042001-042001页

作者： Chiu, Yung-Yueh Liu, Wen-Chien Chen, Yu-Jung Kumaria, Roshni Takeshita, Toshiaki Yano, Masaru Shirota, Riichiro Department of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu 300 Taiwan College of Semiconductor Research National Tsing Hua University Hsinchu 300 Taiwan EECS International Graduate Program National Yang Ming Chiao Tung University Hsinchu 300 Taiwan Winbond Electronics Corporation Kanagawa 222-0033 Japan

This study comprehensively investigates the effect of hydrogen content in forming gas annealing (FGA) on the endurance of NAND flash memories by statistically analyzing the transconductance (G_m,max) characteristics. The G_m,max degradation (ΔG_m,max) worsened with higher cycling temperature, delayed time period from erasing to programming (t_EP) operation, and higher word-line bias (V_A) during t_EP. Moreover, these effects become more pronounced as the hydrogen content in FGA increases. Using the measured G_m,max distributions and Monte -Carlo TCAD technology, the activation energy (E_A) of oxide damage creation can be extracted. The extracted E_A values were 50 meV and 160 meV for the diluted (4%) and pure (100%) hydrogen samples, respectively. This suggests that a higher hydrogen concentration results in more ionized hydrogen atoms remaining in the oxide layer. During t_EP, these hydrogen ions can drift near the Si/SiO₂ surface, where they may react to form trap states. E_A is revealed to have a linear relationship with respect to V_A, where the slope is independent of the hydrogen content in FGA. © 2022 The Author(s). Published on behalf of The Electrochemical Society by IOP Publishing Limited.

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Quantum simulation of an extended Dicke model with a magnetic solid

Communications Materials

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Communications Materials 2024年第1期5卷 42页

作者： Marquez Peraca, Nicolas Li, Xinwei Moya, Jaime M. Hayashida, Kenji Kim, Dasom Ma, Xiaoxuan Neubauer, Kelly J. Fallas Padilla, Diego Huang, Chien-Lung Dai, Pengcheng Nevidomskyy, Andriy H. Pu, Han Morosan, Emilia Cao, Shixun Bamba, Motoaki Kono, Junichiro Department of Physics and Astronomy Rice University HoustonTX United States Department of Physics California Institute of Technology PasadenaCA United States Applied Physics Graduate Program Smalley–Curl Institute Rice University HoustonTX United States Division of Applied Physics Graduate School of Engineering Hokkaido University Hokkaido Japan Department of Electrical and Computer Engineering Rice University HoustonTX United States Department of Physics International Center of Quantum and Molecular Structures and Materials Genome Institute Shanghai University Shanghai China Department of Physics and Center for Quantum Frontiers of Research and Technology National Cheng Kung University Tainan Taiwan Department of Chemistry Rice University HoustonTX United States Department of Physics I Kyoto University Kyoto Japan The Hakubi Center for Advanced Research Kyoto University Kyoto Japan PRESTO Japan Science and Technology Agency Saitama Japan Department of Physics Yokohama National University Yokohama Japan Department of Materials Science and NanoEngineering Rice University HoustonTX United States

The Dicke model describes the cooperative interaction of an ensemble of two-level atoms with a single-mode photonic field and exhibits a quantum phase transition as a function of light–matter coupling strength. Extending this model by incorporating short-range atom–atom interactions makes the problem intractable but is expected to produce new physical phenomena and phases. Here, we simulate such an extended Dicke model using a crystal of ErFeO3, where the role of atoms (photons) is played by Er3+ spins (Fe3+ magnons). Through terahertz spectroscopy and magnetocaloric effect measurements as a function of temperature and magnetic field, we demonstrated the existence of a novel atomically ordered phase in addition to the superradiant and normal phases that are expected from the standard Dicke model. Further, we elucidated the nature of the phase boundaries in the temperature–magnetic-field phase diagram, identifying both first-order and second-order phase transitions. These results lay the foundation for studying multiatomic quantum optics models using well-characterized many-body solid-state systems. © The Author(s) 2024.

关键词： Atoms

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Feasibility study of Information Technology Investment (a case study of ODOO ERP: Project Management Module Implementation in Indonesia Based Company) 10

Feasibility study of Information Technology Investment (a ca...

引用

10th International Conference on ICT for Smart Society, ICISS 2019

作者： Jingga, Fredy Kosala, Raymond Supangkat, Suhono Harso Ranti, Benny School of Information Systems Bina Nusantara University Computer Science Department BINUS Graduate Program-Doctor of Computer Science Information Systems Department Jakarta11480 Indonesia Bina Nusantara University Computer Science Department BINUS Graduate Program-Doctor of Computer Science Jakarta11480 Indonesia Bandung Institute of Technology School of Electrical Engineering and Informatics Bandung Indonesia

ISBN: (纸本)9781728148809

IT Governance are one of the needs in managing Enterprise Level IT. This study shows part of the decision domain of IT Governance Help, which are IT Investment and Prioritization. The purpose of this study is to determine feasibility of implementation open source ERP system Odoo project management module that replaces current system based on operational, economic, and technical aspects. The method used are Fit/Gap Analysis and Cost Benefit model using economic impact worksheet. The analysis is done by comparing the requirement with features owned by current system and Odoo ERP system. This research resulted that Odoo ERP System is feasible in the 3 aspects, the operational feasibility Odoo reaching 72% Fit, the economic feasibility with ROI of 84%, and technical feasibility indicating the technical requirement can be fulfilled by leasing AWS server. The conclusion is the open source ERP system Odoo project management module is feasible to be applied in terms of 3 aspects that have been studied, those are operational, economic, and technical. © 2019 IEEE.

关键词： Cost benefit analysis

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Loss tangent fluctuations due to two-level systems in superconducting microwave resonators

arXiv

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arXiv 2024年

作者： Vallières, André Russell, Megan E. You, Xinyuan Garcia-Wetten, David A. Goronzy, Dominic P. Walker, Mitchell J. Bedzyk, Michael J. Hersam, Mark C. Romanenko, Alexander Lu, Yao Grassellino, Anna Koch, Jens McRae, Corey Rae H. Graduate Program in Applied Physics Northwestern University EvanstonIL60208 United States Fermi National Accelerator Laboratory BataviaIL60510 United States Department of Physics and Astronomy Northwestern University EvanstonIL60208 United States Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Department of Chemistry Northwestern University EvanstonIL60208 United States Department of Electrical and Computer Engineering Northwestern University EvanstonIL60208 United States Center for Applied Physics and Superconducting Technologies Northwestern University EvanstonIL60208 United States Electrical Computing and Energy Engineering Department University of Colorado BoulderCO80309 United States Department of Physics University of Colorado BoulderCO80309 United States National Institute of Standards and Technology BoulderCO80305 United States

Superconducting microwave resonators are critical to quantum computing and sensing technologies. Additionally, they are common proxies for superconducting qubits when determining the effects of performance-limiting loss mechanisms such as from two-level systems (TLS). The extraction of these loss mechanisms is often performed by measuring the internal quality factor Qi as a function of power or temperature. In this work, we investigate large temporal fluctuations of Qi at low powers over periods of 12 to 16 hours (relative standard deviation σQi/Qi = 13%). These fluctuations are ubiquitous across multiple resonators, chips and cooldowns. We are able to attribute these fluctuations to variations in the TLS loss tangent due to two main indicators. First, measured fluctuations decrease as power and temperature increase. Second, for interleaved measurements, we observe correlations between low- and medium-power Qi fluctuations and an absence of correlations with high-power fluctuations. Agreement with the TLS loss tangent mean is obtained by performing measurements over a time span of a few hours. We hypothesize that, in addition to decoherence due to coupling to individual near-resonant TLS, superconducting qubits are affected by these observed TLS loss tangent fluctuations. © 2024, CC BY.

关键词： Qubits

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Unitary Excitation Transfer between Coupled Cavities Using Temporal Switching

引用

Physical Review Letters 2021年第1期127卷 013902-013902页

作者： Yarden Mazor Michele Cotrufo Andrea Alù Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 USA School of Electrical Engineering Tel-Aviv University Ramat-Aviv Tel-Aviv 69978 Israel Photonics Initiative Advanced Science Research Center City University of New York New York New York 10031 USA Physics Program Graduate Center of the City University of New York New York New York 10016 USA

Tailored time variations can enable efficient control over signal flows, giving rise to exotic wave phenomena. In this work, we demonstrate how abrupt temporal switching of the coupling between two cavities can tailor the energy flow between them beyond the limitations of static scenarios, enabling unitary excitation transfer. The proposed scheme is robust with respect to a wide range of nonidealities, with implications for classical and quantum phenomena, from computing to nanophotonic systems.

关键词： Metamaterials Coupled oscillators

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Instruction Multi-Constraint Molecular Generation Using a Teacher-Student Large Language Model

arXiv

引用

arXiv 2024年

作者： Zhou, Peng Wang, Jianmin Li, Chunyan Wang, Zixu Liu, Yiping Sun, Siqi Lin, Jianxin Wei, Leyi Cai, Xibao Lai, Houtim Liu, Wei Wang, Longyue Liu, Yuansheng Zeng, Xiangxiang College of Information Science and Engineering Hunan University Changsha China The Interdisciplinary Graduate Program in Integrative Biotechnology Yonsei University Incheon21983 Korea Republic of School of Informatics Yunnan Normal University Kunming650500 China Department of Computer Science University of Tsukuba Tsukuba3058577 Japan Research Institute of Intelligent Complex Systems Fudan University Shanghai200433 China Shanghai AI Laboratory Shanghai200232 China Centre for Artificial Intelligence driven Drug Discovery Faculty of Applied Science Macao Polytechnic University China School of Informatics Xiamen University Xiamen China Tencent AI Lab China

While various models and computational tools have been proposed for structure and property analysis of molecules, generating molecules that conform to all desired structures and properties remains a challenge. Here, we introduce a multi-constraint molecular generation large language model, TSMMG, which, akin to a student, incorporates knowledge from various small models and tools, namely, the 'teachers'. To train TSMMG, we construct a large set of text-molecule pairs by extracting molecular knowledge from these 'teachers', enabling it to generate novel molecules that conform to the descriptions through various text prompts. We experimentally show that TSMMG remarkably performs in generating molecules meeting complex, natural language-described property requirements across two-, three-, and four-constraint tasks, with an average molecular validity of over 99% and success ratio of 82.58%, 68.03%, and 67.48%, respectively. The model also exhibits adaptability through zero-shot testing, creating molecules that satisfy combinations of properties that have not been encountered. It can comprehend text inputs with various language styles, extending beyond the confines of outlined prompts, as confirmed through empirical validation. Additionally, the knowledge distillation feature of TSMMG contributes to the continuous enhancement of small models, while the innovative approach to dataset construction effectively addresses the issues of data scarcity and quality, which positions TSMMG as a promising tool in the domains of drug discovery and materials science. Copyright © 2024, The Authors. All rights reserved.

关键词： Students

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Accelerating Real-Time Imaging for Radiotherapy: Leveraging Multi-GPU Training with PyTorch

Accelerating Real-Time Imaging for Radiotherapy: Leveraging ...

引用

International Conference on Machine Learning and Applications (ICMLA)

作者： Ruth Obe Brandt Kaufmann Kaelen Baird Sam Kadel Yasmin Soltani Mostafa Cham Matthias K. Gobbert Carlos A. Barajas Zhuoran Jiang Vijay R. Sharma Lei Ren Stephen W. Peterson Jerimy C. PoIf Dept. of Computer Science and of Software Engineering U. of Houston-Clear Lake USA Dept. of Mathematics and Statistics U. of San Francisco USA Dept. of Computer Science and of Mathematics Skidmore College USA Dept. of Computer Science and of Psychology Mount Holyoke College USA Dept. of Biomedical Engineering U. of Houston USA Dept. of Information Systems U. of Maryland Baltimore County Dept. of Mathematics and Statistics U. of Maryland Baltimore County Medical Physics Graduate Program Duke University USA Dept. of Radiation Oncology U. of Maryland School of Medicine USA Department of Radiation Oncology U. of Maryland School of Medicine USA Dept. of Physics U. of Cape Town South Africa H3D Inc. USA

Proton beam therapy is an advanced form of cancer radiotherapy that uses high-energy proton beams to deliver precise and targeted radiation to tumors. This helps to mit-igate unnecessary radiation exposure in healthy tissues. Real-time imaging of prompt gamma rays with Compton cameras has been suggested to improve therapy efficacy. However, the camera's non-zero time resolution leads to incorrect interaction classifications and noisy images that are insufficient for accurately assessing proton delivery in patients. To address the challenges posed by the Compton camera's image quality, machine learning techniques are employed to classify and refine the generated data. These machine-learning techniques include recurrent and feedforward neural networks. A PyTorch model was designed to improve the data captured by the Compton camera. This decision was driven by PyTorch's flexibility, powerful capabilities in handling sequential data, and enhanced G PU usage. This accelerates the model's computations on large-scale radiotherapy data. Through hyperparameter tuning, the validation accuracy of our PyTorch model has been improved from an initial 7 % to over 60 %. Moreover, the PyTorch Distributed Data Parallelism strategy was used to train the RNN models on multiple G PU s, which significantly reduced the training time with a minor impact on model accuracy.

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