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arXiv 2020年

作者： Ferreira, Mafalda Falcão Camacho, Rui Teixeira, Luís F. Doctoral Program in Informatics Engineering Faculty of Engineering University of Porto INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal Department of Informatics Engineering Faculty of Engineering University of Porto Porto - Portugal

Cancer is still one of the most devastating diseases of our time. One way of automatically classifying tumor samples is by analyzing its derived molecular information (i.e., its genes expression signatures). In this work, we aim to distinguish three different types of cancer: thyroid, skin, and stomach. For that, we compare the performance of a Denoising Autoencoder (DAE) used as weight initialization of a deep neural network. Although we address a different domain problem in this work, we have adopted the same methodology of Ferreira et al.. In our experiments, we assess two different approaches when training the classification model: (a) fixing the weights, after pre-training the DAE, and (b) allowing fine-tuning of the entire classification network. Additionally, we apply two different strategies for embedding the DAE into the classification network: (1) by only importing the encoding layers, and (2) by inserting the complete autoencoder. Our best result was the combination of unsupervised feature learning through a DAE, followed by its full import into the classification network, and subsequent fine-tuning through supervised training, achieving an F1 score of 98.04% ± 1.09 when identifying cancerous thyroid samples. Copyright © 2020, The Authors. All rights reserved.

关键词： Classification (of information)

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Parallel 3D temperature image reconstruction using multi-color magnetic particle imaging (MPI)

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AIP Conference Proceedings 2024年第1期3230卷

作者： Klaus N. Quelhas Mark-Alexander Henn Ricardo Farias Weston L. Tew Solomon I. Woods National Institute of Standards and Technology (NIST) 100 Bureau Drive Gaithersburg MD USA Systems Engineering and Computer Science Program (PESC) Federal University of Rio de Janeiro Rio de Janeiro RJ Brazil College of Computer Mathematical & Natural Sciences University of Maryland 7998 Regents Dr College Park MD USA

Magnetic Particle Imaging (MPI) is a novel technique developed for remotely detecting magnetic nanoparticle (MNP) tracers, with great potential for biomedical imaging (as an alternative to traditional methods like MRI or CT), cell tracking, targeted drug delivery and magnetic hyperthermia. More recently, MPI has been studied as a potential method of non-contact temperature measurement. This work presents a simulation study of the multi-color MPI method tailored for 3D temperature imaging, discusses the feasibility of the method for 3D temperature measurements, and shows a parallel implementation of the multi-color T-MPI reconstruction algorithm in graphics processing unit (GPU). While the use of the parallel algorithm resulted in executions about 40x faster when compared to the serial implementation, the method exhibited serious limitations in accurately resolving particle temperatures between the calibration temperatures by interpolation.

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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...

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

arXiv

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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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LoRaWAN Intelligent Outdoor Smart Street Lighting

LoRaWAN Intelligent Outdoor Smart Street Lighting

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IEEE International Conference on Communication, Networks and Satellite (ComNetSat)

作者： Pandapotan Siagian Erick Fernando Faculty of Informatics and Electrical Engineering Computer Engineering Study Program Del Institute of Technology North Sumatera Indonesia School of Information Systems Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9780738125176

ISBN: (纸本)9781665418614

Nowadays, The roads have increased the number of streetlights for the roads vehicles/pedestrians, which raises investment and energy. Observations made to obtain most of the road lights are always active at night, even when there are no vehicles or pedestrians on the road. The problems that occur are the waste of energy sources that are used in streetlights. This research designs the concept of intelligent traffic flow based (LED) for energy optimization, maximum efficiency. This concept uses intelligent light architecture using the LoRaWAN Mesh network. The application of this concept offers system reliability, reduces costs, and makes user satisfaction. The results of this study are demonstrated by experimenting with comparing conventional LED lights. The proposed system, resulting in 33% to 62% energy savings depending on when the usage process in streetlights. Smart lighting LEDs with LoRaWAN provide a remote-control mechanism that can be dynamically adjusted based on environmental conditions, distance, and automatic motion.

关键词： Lighting Sensors Light emitting diodes Intelligent sensors Sensor systems Batteries Roads

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programmable threshold sensing in wireless devices using Ising dynamics

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Nature Electronics 2025年 1-8页

作者： Nicolas Casilli Hussein M. E. Hussein Ryan Tetro Luca Colombo Matteo Rinaldi Cristian Cassella Seunghwi Kim Andrea Alù Philip X.-L. Feng Institute for Nano Systems Innovation (NanoSI) Department of Electrical and Computer Engineering Northeastern University Boston MA USA Photonics Initiative Advanced Science Research Center City University of New York New York City NY USA Physics Program Graduate Center City University of New York New York City NY USA Department of Electrical and Computer Engineering University of Florida Gainesville FL USA

Ising machines—comprising dissipatively coupled nodes capable of emulating the behaviour of ferromagnetic spins—can form analogue computing engines that surpass the sequential processing constraints of von Neumann architectures. However, the incorporation of Ising dynamics into radio-frequency wireless technologies remains limited, especially in terms of their potential to enhance wireless sensing capabilities. Here we report a passive wireless sensor that uses Ising dynamics to accurately implement threshold sensing. The device correlates the occurrence of violations in a sensed parameter with transitions in the coupling state of two parametric oscillators acting as Ising spins. As a result, the accuracy of the device is unaffected by distortions in its input and output signals due to multipath and is less prone to clutter caused by co-site interference. We illustrate the potential of the approach in temperature threshold sensing using a microfabricated lithium niobate microelectromechanical temperature sensor to couple two radio-frequency parametric oscillators, and show that such a system allows the sensor threshold to be wirelessly reprogrammed.

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FaSTrack: A modular framework for real-time motion planning and guaranteed safe tracking

arXiv

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arXiv 2021年

作者： Chen, Mo Herbert, Sylvia L. Hu, Haimin Pu, Ye Fisac, Jaime F. Bansal, Somil Han, SooJean Tomlin, Claire J. School of Computing Science Simon Fraser University Canada Department of Mechanical and Aerospace Engineering UC San Diego United States Department of Electrical Engineering Princeton University United States Department of Electrical and Electronic Engineering University of Melbourne Australia Department of Electrical Engineering and Computer Sciences UC Berkeley United States Control and Dynamical Systems Program California Institute of Technology United States

Real-time, guaranteed safe trajectory planning is vital for navigation in unknown environments. However, real-time navigation algorithms typically sacrifice robustness for computation speed. Alternatively, provably safe trajectory planning tends to be too computationally intensive for real-time replanning. We propose FaSTrack, Fast and Safe Tracking, a framework that achieves both real-time replanning and guaranteed safety. In this framework, real-time computation is achieved by allowing any trajectory planner to use a simplified planning model of the system. The plan is tracked by the system, represented by a more realistic, higher-dimensional tracking model. We precompute the tracking error bound (TEB) due to mismatch between the two models and due to external disturbances. We also obtain the corresponding tracking controller used to stay within the TEB. The precomputation does not require prior knowledge of the environment. We demonstrate FaSTrack using Hamilton-Jacobi reachability for precomputation and three different real-time trajectory planners with three different tracking-planning model pairs. Copyright © 2021, The Authors. All rights reserved.

关键词： Trajectories

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Development of Low-Temperature Doping Process in Cdse-Nanocrystal Thin Films for Flexible Electronic and Optoelectronic Devices

SSRN

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SSRN 2022年

作者： Lee, Yong Min Jung, Byung Ku Ahn, Junhyuk Park, Taesung Shin, Chanho Ng, Tse Nga Kim, In Soo Choi, Ji-Hyuk Oh, Soong Ju Department of Semiconductor Systems Engineering Korea University Seoul02841 Korea Republic of Department of Materials Science and Engineering Korea University Seoul02841 Korea Republic of Materials Science Engineering Program Department of Electrical and Computer Engineering University of California San Diego La Jolla CA92093 United States Nanophotonics Research Center Korea Institute of Science and Technology Seoul02792 Korea Republic of Department of Converging Science and Technology KHU KIST Seoul02447 Korea Republic of Resources Utilization Research Center Korea Institute of Geoscience and Mineral Resources Daejeon34132 Korea Republic of

We introduce an effective surface-doping strategy for CdSe nanocrystals (NCs) by examining the size-dependency of the doping behavior. A CdSe NC thin-film transistor (TFT) is fabricated via a doping process with InCl3 treatment followed by an annealing process. Spectroscopic and electronic device characterization reveal that smaller NCs are more effectively doped than larger NCs at all annealing temperatures. This is attributed to the larger specific surface area, where the dopant can be more readily coordinated. The degenerate behavior of a 3.3-nm CdSe-NC TFT appears at a lower temperature than that of larger NC TFTs. We achieve a high electron mobility and on-to-off current ratio of 1.79 cm2/Vs and 5.2 × 105, respectively, in a low-temperature annealing process (150 °C) with 3.3-nm CdSe NCs. This facilitates the fabrication of a flexible CdSe-NC TFT, which is demonstrated on a polyethylene terephthalate substrate with an Al2O3 dielectric layer using atomic layer deposition. The flexible 3.3-nm CdSe-NC TFT is successfully fabricated even at 150 °C, with a high on-to-off current ratio and low hysteresis at a low operation voltage, which is impossible for larger CdSe-NC TFTs. © 2022, The Authors. All rights reserved.

关键词： Nanocrystals

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Low-Velocity-Favored Transition Radiation

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Physical Review Letters 2023年第11期131卷 113002-113002页

作者： Jialin Chen Ruoxi Chen Fuyang Tay Zheng Gong Hao Hu Yi Yang Xinyan Zhang Chan Wang Ido Kaminer Hongsheng Chen Baile Zhang Xiao Lin Interdisciplinary Center for Quantum Information State Key Laboratory of Extreme Photonics and Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center College of Information Science & Electronic Engineering Zhejiang University Hangzhou 310027 China International Joint Innovation Center the Electromagnetics Academy at Zhejiang University Zhejiang University Haining 314400 China Department of Electrical and Computer Engineering Technion-Israel Institute of Technology Haifa 32000 Israel Department of Electrical and Computer Engineering Rice University Houston Texas 77005 USA Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston Texas 77005 USA School of Electrical and Electronic Engineering Nanyang Technological University Singapore 639798 Singapore Department of Physics University of Hong Kong Hong Kong 999077 China Key Lab of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang Jinhua Institute of Zhejiang University Zhejiang University Jinhua 321099 China Shaoxing Institute of Zhejiang University Zhejiang University Shaoxing 312000 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Singapore 637371 Singapore Centre for Disruptive Photonic Technologies Nanyang Technological University Singapore 637371 Singapore

When a charged particle penetrates through an optical interface, photon emissions emerge—a phenomenon known as transition radiation. Being paramount to fundamental physics, transition radiation has enabled many applications from high-energy particle identification to novel light sources. A rule of thumb in transition radiation is that the radiation intensity generally decreases with the decrease of particle velocity v; as a result, low-energy particles are not favored in practice. Here, we find that there exist situations where transition radiation from particles with extremely low velocities (e.g., v/c<10−3) exhibits comparable intensity as that from high-energy particles (e.g., v/c=0.999), where c is the light speed in free space. The comparable radiation intensity implies an extremely high photon extraction efficiency from low-energy particles, up to 8 orders of magnitude larger than that from high-energy particles. This exotic phenomenon of low-velocity-favored transition radiation originates from the interference of the excited Ferrell-Berreman modes in an ultrathin epsilon-near-zero slab. Our findings may provide a promising route toward the design of integrated light sources based on low-energy electrons and specialized detectors for beyond-standard-model particles.

关键词： Atom or molecule scattering from surfaces Atomic & molecular collisions Cherenkov radiation Crystal optics Electron beams & optics Light-matter interaction Optical sources & detectors Optical transient phenomena Plasmonics

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SRBench++: Principled Benchmarking of Symbolic Regression With Domain-Expert Interpretation

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IEEE Transactions on Evolutionary Computation 2024年 1-1页

作者： de Franca, F.O. Virgolin, M. Kommenda, M. Majumder, M.S. Cranmer, M. Espada, G. Ingelse, L. Fonseca, A. Landajuela, M. Petersen, B. Glatt, R. Mundhenk, N. Lee, C.S. Hochhalter, J.D. Randall, D.L. Kamienny, P. Zhang, H. Dick, G. Simon, A. Burlacu, B. Kasak, Jaan Machado, Meera Wilstrup, Casper Cavaz, W.G.L. Federal University of ABC Santo Andre Brazil Evolutionary Intelligence group Centrum Wiskunde and Informatica Science Park Amsterdam Netherlands University of Applied Sciences Upper Austria Hagenberg Austria Computational Health Informatics Program Boston Children’s Hospital Harvard Medical School Boston USA Center for Computational Astrophysics Flatiron Institute and Department of Astrophysical Sciences of Princeton University USA LASIGE Faculdade de Ciências Universidade de Lisboa Lisboa Portugal Computational Engineering Division Lawrence Livermore National Laboratory Livermore USA Department of Mechanical Engineering University of Utah Utah USA Meta FAIR France Victoria University of Wellington School of Engineering and Computer Science New Zealand University of otago Department of Information Science New Zealand Institut für Angewandte Physik Universität TübingenMax Planck Institute for Intelligent Systems Tübingen Germany Abzu AI Orient Plads 1 Nordhavn Denmark

Symbolic regression searches for analytic expressions that accurately describe studied phenomena. The main promise of this approach is that it may return an interpretable model that can be insightful to users, while maintaining high accuracy. The current standard for benchmarking these algorithms is SRBench, which evaluates methods on hundreds of datasets that are a mix of real-world and simulated processes spanning multiple domains. At present, the ability of SRBench to evaluate interpretability is limited to measuring the size of expressions on real-world data, and the exactness of model forms on synthetic data. In practice, model size is only one of many factors used by subject experts to determine how interpretable a model truly is. Furthermore, SRBench does not characterize algorithm performance on specific, challenging sub-tasks of regression such as feature selection and evasion of local minima. In this work, we propose and evaluate an approach to benchmarking SR algorithms that addresses these limitations of SRBench by 1) incorporating expert evaluations of interpretability on a domain-specific task, and 2) evaluating algorithms over distinct properties of data science tasks. We evaluate 12 modern symbolic regression algorithms on these benchmarks and present an in-depth analysis of the results, discuss current challenges of symbolic regression algorithms and highlight possible improvements for the benchmark itself. Authors

关键词： Benchmarking

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