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International Conference and Workshop on Computing and Communication (IEMCON)

作者： Mariana Rodrigues Villarim João Vitor Holanda de Luna Douglas de Farias Medeiros Renata Imaculada Soares Pereira Cleonilson Protasio de Souza Orlando Baiocchi Francisco Cipriano da Cunha Martins Postgraduation Program of Electr. Eng. Federal University of Paraíba João Pessoa Brazil Department of Electrical Engineering Federal University of Paraíba João Pessoa Brazil School of Engineering and Technology University of Washington Tacoma Tacoma WA USA Department of Computer Science University of Azores São Miguel Azores Portugal

Due to its particular features, LoRa is gaining more and more attention from industry and academia because it tries to combine long communication range, low-power consumption, and low-data rate application. A very important feature observed on LoRa is that it is highly robust and reliable. Due to this, LoRa is being applied in many IoT solutions in urban environment, but on hard natural environments like dense forest, near river sides, lakes and mangroves, more studies need to be carried out in order to evaluate the its quality. This paper describes experimental studies carried out to measure LoRa communication range and Received Signal Strength Indicator (RSSI), both in natural and urban environments. The experiments took place in two different places of the world, one in the northern hemisphere and another in the southern hemisphere: on the Portuguese archipelago of the Azores (in SãoMiguel Island) and in the city of João Pessoa in Northeast of Brazil, respectively. As a result, we observed that LoRa is very robust in dense urban environments, where it was possible to established long distance connections (approximately 2.1 km). However, the results were inconclusive in forest environments, because in the Azores, the LoRa connection ranged about 800 m thought the forest/lake, while in Brazil it was about 230 m.

关键词： Forestry Lakes Chirp Urban areas Frequency modulation Internet of Things Wireless communication

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Closed-loop sparse channel estimation for wideband millimeter-wave full-dimensional MIMO systems

arXiv

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arXiv 2019年

作者： Liao, Anwen Gao, Zhen Wang, Hua Chen, Sheng Alouini, Mohamed-Slim Yin, Hao School of Information and Electronics Beijing Institute of Technology Beijing100081 China School of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom King Abdulaziz University Jeddah21589 Saudi Arabia Electrical Engineering Program Division of Physical Sciences and Engineering King Abdullah University of Science and Technology Thuwal Makkah Province Saudi Arabia Institute of China Electronic System Engineering Corporation Beijing100141 China

This paper proposes a closed-loop sparse channel estimation (CE) scheme for wideband millimeter-wave hybrid full-dimensional multiple-input multiple-output and time division duplexing based systems, which exploits the channel sparsity in both angle and delay domains. At the downlink CE stage, random transmit precoding matrix is designed at base station (BS) for channel sounding, and receive combining matrices at user devices (UDs) are designed whereby the hybrid array is visualized as a low-dimensional digital array for facilitating the multi-dimensional unitary ESPRIT (MDU-ESPRIT) algorithm to estimate respective angle-of-arrivals (AoAs). At the uplink CE stage, the estimated downlink AoAs, namely, uplink angle-of-departures (AoDs), are exploited to design multi-beam transmit precoding matrices at UDs to enable BS to estimate the uplink AoAs, i.e., the downlink AoDs, and delays of different UDs, whereby the MDU-ESPRIT algorithm is used based on the designed receive combining matrix at BS. Furthermore, a maximum likelihood approach is proposed to pair the channel parameters acquired at the two stages, and the path gains are then obtained using least squares estimator. According to spectrum estimation theory, our solution can acquire the super-resolution estimations of the AoAs/AoDs and delays of sparse multipath components with low training overhead. Simulation results verify the better CE performance and lower computational complexity of our solution over state-of-the-art approaches. Copyright © 2019, The Authors. All rights reserved.

关键词： Millimeter waves

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Designing the Application of Security Text Messages into Audio Files Using Data Encryption Standard (DES) Algorithms Using the End of File (EOF) Method 1

Designing the Application of Security Text Messages into Aud...

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1st Workshop on Environmental Science, Society, and technology, WESTECH 2018

作者： Pardede, A.M.H. Pramana, Anggi Zarlis, Muhammad Iskandar, Akbar Manurung, Rosida Tiurma Sriadhi, S. Kurniawan, Citra Hasibuan, Abdurrozzaq Siregar, Nurintan Asyiah Sari, Ayu Esteka Mulyaningsih, Indrya Iskandar Alam, Teguh Hidayat Ibrahim Listyorini, Tri Winarno, Edy Tulus STMIK Kaputama Binjai Sumatera Utara Indonesia Department of Computer Science Universitas Sumatera Utara Medan Indonesia Department of Informatics STMIK AKBA Makassar Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Department of Electrical Engineering Sekolah Tinggi Teknik Malang Indonesia Faculty of Engineering Universitas Islam Sumatera Utara Medan Indonesia Department of Management STIE Labuhanbatu Sumatera Utara Indonesia Department of Management STIE Sakti Alam Kerinci Jambi Indonesia Department of Indonesian Language Teaching Institut Agama Islam Negeri Syekh Nurjati Cirebon Indonesia Department of Informatics Engineering Universitas Muhammadiyah Sorong Sorong Indonesia Department of English Education Universitas Muhammadiyah Sorong Sorong Indonesia Department of Informatics Universitas Muria Kudus Indonesia Faculty of Information Technology Universitas Stikubank Semarang Indonesia Department of Mathematics Universitas Sumatera Utara Medan Indonesia

There are several ways to deal with security issues of confidential data sent via the internet, including using cryptographic techniques and steganography. Steganography is the science and art of concealing information / messages in a media in such a way that its existence is not detected by other parties who are not entitled to the information. Instead, cryptography disguises the meaning of a message, but does not hide that there is a message because the file looks suspicious. The Steganography technique used here was End Of File (EOF). The EOF technique described how to add data or files at the end of the image file. For this technique, the size of data or files that will be hidden could be larger than the size of the image file. The hidden data will be inserted at the end of the file so that it will not affect the image. This steganography application is also equipped with a cryptographic function Data Encryption Standard (DES) at the time of insertion of data that functions as a generator code and encrypts data, so that the security of a data in the file is more protected and protected from those who are not entitled to know the data. © Published under licence by IOP Publishing Ltd.

关键词： Steganography

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The application of an extracellular vesicle-based biosensor in early diagnosis and prediction of chemoresponsiveness in ovarian cancer

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Cancer Letters 2024年 581卷 216533-216533页

作者： Tsang, Benjamin K. Asare-Werehene, Meshach Hunter, Rob Gerber, Emma Reunov, Arkadiy Brine, Isaiah Chang, Chia-Yu Chang, Chia-Ching Shieh, Dar-Bin Burger, Dylan Anis, Hanan Departments of Obstetrics & Gynecology and Cellular & Molecular Medicine Centre for Infection Immunity and Inflammation Interdisciplinary School of Health Sciences University of Ottawa Ottawa ON K1N 6N5 Canada Chronic Disease Program Ottawa Hospital Research Institute The Ottawa Hospital Ottawa ON K1Y 4E9 Canada Department of Biology St. Francis Xavier University 2320 Notre Dame Avenue Antigonish NS B2G 2W5 Canada School of Electrical Engineering and Computer Science Ottawa-Carleton Institute for Biomedical Engineering University of Ottawa Ottawa ON K1N 6N5 Canada Department of Biological Science and Department of Electrophysics Technology Center for Intelligent Drug Systems and Smart Bio-devices (IDS2B) National Yang Ming Chiao Tung University Hsinchu 30068 Taiwan Institute of Basic Medical Science Institute of Oral Medicine and Department of Stomatology Advanced Optoelectronic Technology Center and Center for Micro/Nano Science and Technology National Cheng Kung University Hospital National Cheng Kung University Tainan 704 Taiwan Institute of Physics Academia Sinica Taipei 10529 Taiwan

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Quantum computing hardware for HEP algorithms and sensing

arXiv

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arXiv 2022年

作者： Alam, M. Sohaib Belomestnykh, Sergey Bornman, Nicholas Cancelo, Gustavo Chao, Yu-Chiu Checchin, Mattia Dinh, Vinh San Grassellino, Anna Gustafson, Erik J. Harnik, Roni McRae, Corey Rae Harrington Huang, Ziwen Kapoor, Keshav Kim, Taeyoon Kowalkowski, James B. Kramer, Matthew J. Krasnikova, Yulia Kumar, Prem Kurkcuoglu, Doga Murat Lamm, Henry Lyon, Adam L. Milathianaki, Despina Murthy, Akshay Mutus, Josh Nekrashevich, Ivan Oh, JinSu Özgüler, A. Barış Perdue, Gabriel Nathan Reagor, Matthew Romanenko, Alexander Sauls, James A. Stefanazzi, Leandro Tubman, Norm M. Venturelli, Davide Wang, Changqing You, Xinyuan van Zanten, David M.T. Zhou, Lin Zhu, Shaojiang Zorzetti, Silvia NASA Ames Research Center Moffett FieldCA94035 United States Mountain ViewCA94043 United States Fermi National Accelerator Laboratory BataviaIL60510 United States Scientific Computing Division Fermi National Accelerator Laboratory BataviaIL60510 United States Northwestern-Fermilab Center for Applied Physics and Superconducting Technologies Northwestern University EvanstonIL60208 United States Graduate Program in Applied Physics Northwestern University EvanstonIL60208 United States Theory Division Fermi National Accelerator Laboratory BataviaIL60510 United States Department of Physics Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO80305 United States National Institute of Standards and Technology Boulder CO80305 United States Department of Physics and Astronomy Northwestern University EvanstonIL60208 United States Ames Laboratory U.S. Department of Energy AmesIA50011 United States Center for Photonic Communication and Computing ECE Department Northwestern University EvanstonIL60208 United States Rigetti Computing Inc. BerkeleyCA94710 United States NASA Ames Research Center Moffett FieldCA94035 United States

Quantum information science harnesses the principles of quantum mechanics to realize computational algorithms with complexities vastly intractable by current computer platforms. Typical applications range from quantum chemistry to optimization problems and also include simulations for high energy physics. The recent maturing of quantum hardware has triggered preliminary explorations by several institutions (including Fermilab) of quantum hardware capable of demonstrating quantum advantage in multiple domains, from quantum computing to communications, to sensing. The Superconducting Quantum Materials and Systems (SQMS) Center, led by Fermilab, is dedicated to providing breakthroughs in quantum computing and sensing, mediating quantum engineering and HEP based material science. The main goal of the Center is to deploy quantum systems with superior performance tailored to the algorithms used in high energy physics. In this Snowmass paper, we discuss the two most promising superconducting quantum architectures for HEP algorithms, i.e. three-level systems (qutrits) supported by transmon devices coupled to planar devices and multi-level systems (qudits with arbitrary N energy levels) supported by superconducting 3D cavities. For each architecture, we demonstrate exemplary HEP algorithms and identify the current challenges, ongoing work and future opportunities. Furthermore, we discuss the prospects and complexities of interconnecting the different architectures and individual computational nodes. Finally, we review several different strategies of error protection and correction and discuss their potential to improve the performance of the two architectures. This whitepaper seeks to reach out to the HEP community and drive progress in both HEP research and QIS hardware. Copyright © 2022, The Authors. All rights reserved.

关键词： High energy physics

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On Stability of Event-Triggered Systems With Sliding Mode Control

On Stability of Event-Triggered Systems With Sliding Mode Co...

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International Workshop on Variable Structure Systems, VSS

作者： Abhisek K. Behera Bijnan Bandyopadhyay Department of Electrical and Computer Engineering Seoul National University Seoul South Korea Interdisciplinary Program in Systems and Control Engineering Indian Institute of Technology Bombay Mumbai India

In this paper, we investigate the stability of a controlled system in the event-triggering framework. By designing the triggering scheme, the control signals are updated when it is demanded subject to some satisfactory system performance. However, the stability of the system is not yet fully investigated with respect to the triggering conditions. So, the main purpose of the paper is to analyse the stability of the system with respect to the proposed triggering scheme. In this paper, sliding mode control (SMC) is used to design the event-triggered control. Our analysis proposes a new notion called bounded event property for the event which guarantees the triggering instants are generated in finite-time for all possible values of the triggering parameter. It is shown that the event-triggered SMC ensures possess the bounded event property and moreover the proposed triggering mechanism also guarantees the stability of the closed loop system stability.

关键词： Stability analysis Trajectory Closed loop systems Manifolds Steady-state Sliding mode control System performance

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A novel CAD system for detecting acute rejection of renal allografts based on integrating imaging-markers and laboratory biomarkers

A novel CAD system for detecting acute rejection of renal al...

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2018 IEEE International Conference on Imaging Systems and Techniques, IST 2018

作者： Shehata, Mohamed Ghazal, Mohammed Khalifa, Fahmi El-Ghar, Mohamed Abou Khalil, Ashraf Dwyer, Amy C. El-Giziri, Ahmed El-Melegy, Moumen El-Baz, Ayman BioImaging Lab University of Louisville LouisvilleKY40292 United States Electrical and Computer Engineering Department Abu Dhabi University Abu Dhabi United Arab Emirates Radiology Department Urology and Nephrology Center University of Mansoura Mansoura35516 Egypt Computer Science and Information Technology Department Abu Dhabi University Abu Dhabi United Arab Emirates Kidney Disease Program University of Louisville LouisvilleKY40202 United States Department of Electrical Engineering Assiut University Assiut71516 Egypt

ISBN: (纸本)9781538666289

The goal of this paper is to determine the parameters that are correlated with the biopsy diagnosis of acute renal rejection (AR) post-transplantation, using laboratory biomarkers and (3D+-value) diffusion weighted MR (DW-MR) image-markers. 16 patients with non-rejection (NR) and 45 patients with AR renal allografts determined by their renal biopsy as a gold standard were included. All kidneys were evaluated using both laboratory biomarkers (e.g., creatinine clearance (CrCl) and serum creatinine (SCr)) and DW-MR image-markers. To extract the latter, DW-MR kidney images were first segmented using a geometric deformable model, then, DW-MR image-markers known as apparent diffusion coefficients (ADCs), were estimated for segmented kidneys at multiple b-values (i.e. strength and timing, of, the, field, gradients, (b50,b 100,...,b 1000 s/mm2)). A statistical analysis investigating possible correlations between potential biomarkers of AR and the biopsy diagnosis was firstly performed. Two categories of parameters were mainly examined: (i) laboratory biomarkers (CrCl and SCr) and (ii) the average ADC (aADC) at individual b-values. Analysis of Variance(ANOVA) and the likelihood ratio (χ2) tests found that both CrCl and SCr affected significantly the likelihood of AR, as did the aADC for the individual b-values of b 100, b 500, b 600, b 700, and b 900s/mm2. Nevertheless, patient demographics (i.e. age and sex) and the aADC at the remaining b-values had no significant effect. The statistical analysis results encouraged us to investigate if this can lead to building a computer-aided diagnostic (CAD) system with the ability to classify AR from NR renal allografts. To achieve this goal, stacked auto-encoders (SAEs) based on deep learning approach were trained using the fusion of the statistically significant DW-MR image-markers and laboratory biomarkers for the classification purposes. Preliminary results obtained (92% accuracy, 92% sensitivity, and 94% specificity) hold a lot of

关键词： Creatinine

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Automatic Extraction of Medication Mentions from Tweets-Overview of the BioCreative VII Shared Task 3 Competition

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Database : the journal of biological databases and curation 2023年第2023期2023卷 baac108页

作者： Davy Weissenbacher Karen O'Connor Siddharth Rawal Yu Zhang Richard Tzong-Han Tsai Timothy Miller Dongfang Xu Carol Anderson Bo Liu Qing Han Jinfeng Zhang Igor Kulev Berkay Köprü Raul Rodriguez-Esteban Elif Ozkirimli Ammer Ayach Roland Roller Stephen Piccolo Peijin Han V G Vinod Vydiswaran Ramya Tekumalla Juan M Banda Parsa Bagherzadeh Sabine Bergler João F Silva Tiago Almeida Paloma Martinez Renzo Rivera-Zavala Chen-Kai Wang Hong-Jie Dai Luis Alberto Robles Hernandez Graciela Gonzalez-Hernandez Department of Computational Biomedicine Cedars-Sinai Medical Center Los Angeles CA USA. DBEI The Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Computer Science and Information Engineering National Central University No. 300 Zhongda Rd Zhongli District Taoyuan 320 Taiwan. IoX Center National Taiwan University Da'an District Section 4 Roosevelt Rd No. 1 Barry Lam Hall Taipei 106 Taiwan. Research Center for Humanities and Social Sciences Academia Sinica No. 128 Section 2 Academia Rd Nangang District Taipei 115 Taiwan. Computational Health Informatics Program Boston Children's Hospital Boston MA USA. Department of Pediatrics Harvard Medical School Boston MA USA. NVIDIA Santa Clara CA USA. Department of Statistics Florida State University Tallahassee FL USA. Data and Analytics Chapter F. Hoffmann-La Roche Ltd Switzerland. Pharmaceutical Research and Early Development Roche Innovation Center Basel Switzerland. Speech and Language Technology Lab DFKI Berlin Germany. Department of Biology Brigham Young University Provo UT USA. Department of Computational Medicine and Bioinformatics Medical School University of Michigan Ann Arbor MI USA. Department of Learning Health Sciences Medical School University of Michigan Ann Arbor MI USA. School of Information University of Michigan Ann Arbor MI USA. Department of Computer Science Georgia State University Atlanta GA USA. CLaC Labs Concordia University Montreal Canada. DETI Institute of Electronics and Informatics Engineering of Aveiro University of Aveiro Portugal. Department of Computation University of A Coruña Spain. Computer Science and Engineering Department Universidad Carlos III de Madrid Madrid Spain. Big Data Laboratory Chunghwa Telecom Laboratories Taoyuan Taiwan. Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan. Department of Electrical Engineering College of Electrical Engineering and Computer Sci

This study presents the outcomes of the shared task competition BioCreative VII (Task 3) focusing on the extraction of medication names from a Twitter user's publicly available tweets (the user's 'timeline'). In general, detecting health-related tweets is notoriously challenging for natural language processing tools. The main challenge, aside from the informality of the language used, is that people tweet about any and all topics, and most of their tweets are not related to health. Thus, finding those tweets in a user's timeline that mention specific health-related concepts such as medications requires addressing extreme imbalance. Task 3 called for detecting tweets in a user's timeline that mentions a medication name and, for each detected mention, extracting its span. The organizers made available a corpus consisting of 182 049 tweets publicly posted by 212 Twitter users with all medication mentions manually annotated. The corpus exhibits the natural distribution of positive tweets, with only 442 tweets (0.2%) mentioning a medication. This task was an opportunity for participants to evaluate methods that are robust to class imbalance beyond the simple lexical match. A total of 65 teams registered, and 16 teams submitted a system run. This study summarizes the corpus created by the organizers and the approaches taken by the participating teams for this challenge. The corpus is freely available at https://***/tasks/biocreative-vii/track-3/. The methods and the results of the competing systems are analyzed with a focus on the approaches taken for learning from class-imbalanced data.

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Cloud-AC-OPF: Model reduction technique for multi-scenario optimal power flow via chance-constrained optimization

arXiv

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arXiv 2019年

作者： Frolov, Vladimir Roald, Line Chertkov, Michael Skolkovo Institute of Science and Technology Nobel Street 3 Moscow Region143026 Russia Electrical & Computer Engineering University of Wisconsin 1415 Engineering Drive MadisonWI53706 United States Center for Nonlinear Studies and Theoretical Division T-4 LANL Los AlamosNM87545 United States Program in Applied Mathematics University of Arizona TucsonAZ85721 United States

—Many practical planning and operational applications in power systems require simultaneous consideration of a large number of operating conditions or Multi-Scenario AC-Optimal Power Flow (MS-AC-OPF) solution. However, when the number of exogenously prescribed conditions is large, solving the problem as a collection of single AC-OPFs may be time-consuming or simply intractable computationally. In this paper, we suggest a model reduction approach, coined Cloud-AC-OPF, which replaces a collection of samples by their compact representation in terms of mean and standard deviation. Instead of determining an optimal generation dispatch for each sample individually, we parametrize the generation dispatch as an affine function. The Cloud-AC-OPF is mathematically similar to a generalized Chance-Constrained AC-OPF (CC-AC-OPF) of the type recently discussed in the literature, but conceptually different as it discusses applications to long-term planning. We further propose a tractable formulation and implementation, and illustrate our construction on the example of 30-bus IEEE model. Copyright © 2019, The Authors. All rights reserved.

关键词： Acoustic generators

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The association for the advancement of artificial intelligence 2020 workshop program

The association for the advancement of artificial intelligen...

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作者： Bang, Grace Barash, Guy Bea, Ryan Cali, Jacques Castillo-Effen, Mauricio Chen, Xin Cynthia Chhaya, Niyati Dhoopar, Rohan Dumancic, Sebastijan Espinoza, Huáscar Farchi, Eitan Fioretto, Ferdinando Fuentetaja, Raquel Galley, Michel Geib, Christopher Hernández-Orallo, José Huang, Xiaowei Keren, Sarah Kim, Seokhwan Jaidka, Kokil Liu, Xiaomo Lu, Tyler Ma, Zhiqiang Mallah, Richard McDermid, John Michalowski, Martin Mirsky, Reuth Héigeartaigh, Seán Ó. Ramachandran, Deepak Segovia-Aguas, Javier Shaban-Nejad, Arash Shehory, Onn Shwartz, Vered Srivastava, Siddharth Talamadupula, Kartik Tang, Jian Zhang, Dell Zhang, Jian S&P Global. Western Digital University of Southampton United Kingdom Blue Prism Group PLC Lockheed Martin's Advanced Technology Laboratories ArlingtonVA United States University of Hong Kong Hong Kong Adobe Research Google Research Katholieke Universiteit Leuven Belgium Commissariat à ĺÉnergie Atomique France IBM Research Department of Electrical Engineering and Computer Science Syracuse University United States Universidad Carlos III de Madrid Spain Microsoft Research AI SIFT LLC Universitat Politècnica de València Spain Leverhulme Centre for the Future of Intelligence United Kingdom Department of Computer Science University of Liverpool United Kingdom National University of Singapore Singapore Harvard School of Engineering and Applied Sciences in the of Fields of Multiagent Environment Design and Goal Recognition Design Amazon Alexa AI Future of Life Institute United States University of York Assuring Autonomy International Program United Kingdom University of Minnesota School of Nursing MinneapolisMN United States University of Texas at Austin AustinTX United States Institut de Robòtica i Informàtica Industrial Spanish Council for Scientific Research Technical University of Catalonia Spain Oak Ridge National Laboratory Center for Biomedical Informatics Department of Pediatrics University of Tennessee Health Science Center United States Bar Ilan University Israel University of Washington SeattleWA United States Autonomous Agents and Intelligent Robots lab of the School of Computing Informatics Decision Systems Arizona State University United States DiDi AI Labs School of Industrial and System Engineering Georgia Institute of Technology United States University of London United Kingdom Microsoft Azure

The Association for the Advancement of Artificial Intelligence 2020 Workshop program included twenty-three workshops covering a wide range of topics in artificial intelligence. This report contains the required reports, which were submitted by most, but not all, of the workshop chairs. Copyright © 2020, Association for the Advancement of Artificial Intelligence. All rights reserved.

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