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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Dat Thanh Tran Martin Magris Juho Kanniainen Moncef Gabbouj Alexandros Iosifidis Laboratory of Signal Processing Tampere University of Technology Tampere Finland Laboratory of Industrial and Information Management Tampere University of Technology Tampere Finland Department of Engineering Electrical & Computer Engineering Aarhus University Aarhus Denmark

Nowadays, with the availability of massive amount of trade data collected, the dynamics of the financial markets pose both a challenge and an opportunity for high frequency traders. In order to take advantage of the rapid, subtle movement of assets in High Frequency Trading (HFT), an automatic algorithm to analyze and detect patterns of price change based on transaction records must be available. The multichannel, time-series representation of financial data naturally suggests tensor-based learning algorithms. In this work, we investigate the effectiveness of two multilinear methods for the mid-price prediction problem against other existing methods. The experiments in a large scale dataset which contains more than 4 millions limit orders show that by utilizing tensor representation, multilinear models outperform vector-based approaches and other competing ones.

关键词： Tensile stress Mathematical model Recurrent neural networks Feature extraction Heuristic algorithms Prediction algorithms

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An intra-body communication research platform based on virtual instrument 13

An intra-body communication research platform based on virtu...

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13th IEEE International Conference on Electronic Measurement and Instruments, ICEMI 2017

作者： Lin, Shi Gao, Yueming Zhang, Hengfei Željka, Lučev Vasić Vai, Mang-I Du, Min Cifrek, Mario Pun, Sio-Hang College of Physics and Information Engineering Fuzhou University Fuzhou350116 China Key Lab of Medical Instrumentation and Pharmaceutical Technology of Fujian Province Fuzhou350116 China Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia State Key Laboratory of Analog and Mixed Signal VLSI University of Macau 999078 China Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau 999078 China Key Lab of Eco-industrial Green Technology of Fujian Province Nanping China

ISBN: (纸本)9781509050345

An intra-body communication (IBC) research platform based on virtual instrument was established for the hardware design of IBC transceiver. Firstly, the feasibility of constructing IBC research platform using optic-coupling circuit was verified via comparison of three kinds of measurement methods based on virtual instrument. Then, ASK, FSK and BPSK modulation-demodulation were realized via LabVIEW programming, and user interface of the platform was also designed. The platform could achieve signal transmission or recover under different coupling type, different channel distance and different modulation-demodulation method, etc., by means of dynamic adjusting of platform parameters. Experiment results of capacitive-coupling under the platform indicated the authenticity and feasibility of signal transmission. Finally, a full-floating IBC transceiver was designed aided by the parameters provided by the research platform under the scene of capacitive-coupling, FSK modulation and 180 cm channel distance. Moreover, Bit Error Rate (BER) of the transceiver was less than 1e-5, which meant that it is effective and convenient for the design of IBC transceiver aided by virtual instrument platform. © 2017 IEEE.

关键词： User interfaces

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Studies of scalp level connectivity and representative channels in epilepsy

Studies of scalp level connectivity and representative chann...

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Biomedical engineering International Conference (BMEiCON)

作者： Jia Wen Li Peng Un Mak Shovan Barma Sio Hang Pun Xu Tong Cui U. Kin Che Mang I. Vai State Key Laboratory of Analog and Mixed-Signal VLSI University of Macau Macau China Department of Electrical and Computer Engineering University of Macau Macau China Department of Electronics and Communication Engineering Indian Institute of Information Technology Guwahati (IIITG) Guwahati India

Epilepsy is a typical neurological disorder. To find the characteristics of epilepsy, scalp level connectivity is one of the interests that widely studied before. However, another aspect about the scalp representative channels, which presents the synchronous regions, has not yet been investigated. In this work, we focus on study the scalp responses of epilepsy by connectivity and representative channels. Electroencephalography (EEG), the technique to record the electrical activities of brain, has been utilized. An online EEG database of epilepsy reported from Karunya University in India was selected to be the testbed. By using two methods, coherence and correlation, the scalp level connectivity which shows the networks of scalp responses, can be mapped. Moreover, the representative channels can also be obtained based on the mentioned two methods. According to the statistical results of 94 subjects, the scalp channels F4, C4, P4, and T4 occupied higher percentages than others. These findings are beneficial for us to enrich the understanding of scalp responses in epilepsy.

关键词： Scalp Coherence Correlation Electroencephalography Epilepsy Databases Transforms

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Biological Modeling Challenges in a Multiphysics Approach

Biological Modeling Challenges in a Multiphysics Approach

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IEEE Pulsed Power Conference

作者： Jessy Mathault Hamza Landari Frederic Tessier Paul Fortier Amine Miled LABioTRON Bioengineering Research Laboratory Electrical and Computer Engineering Department Universite Laval Radiocommunications and Signal Processing Laboratory (LRTS) Electrical and Computer Engineering Department Universite Laval

ISBN: (纸本)9781509063901

Modeling biological behaviour requires a multidisciplinary approach and very large computational resources. In this paper, we present an overview of our research work with regards to biological neuron network (NN) modeling, electrochemical reaction emulation for neurotransmitters and finite element modeling (FEM) of a very low pressure micropump for neurotransmitter concentration modulations. Three different approaches have been explored, namely MATLAB simulations of biological NN, MATLAB simulations of electro-chemical reactions and the FEM approach. Our objective through biological NN modeling is to investigate the need to develop a dedicated chip for a NN implementation or to use a strictly software approach. The objective of the electrochemical emulator is to provide a tool which can help us to understand how to decompose cyclic voltammetry curves into more conventional and easy to interpret graphs. However, although the three approaches appear independent, they are in fact all related as we investigate the computer performances needed for biological modeling.

关键词： Modeling Biological Neurotransmitters Finite element method interdisciplinary approach Biological Models simulating Research work MATLAB Cyclic voltammetry chemical reactions

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The Liver Tumor Segmentation Benchmark (LiTS)

arXiv

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arXiv 2019年

作者： Bilic, Patrick Christ, Patrick Li, Hongwei Bran Vorontsov, Eugene Ben-Cohen, Avi Kaissis, Georgios Szeskin, Adi Jacobs, Colin Mamani, Gabriel Efrain Humpire Chartrand, Gabriel Lohöfer, Fabian Holch, Julian Walter Sommer, Wieland Hofmann, Felix Hostettler, Alexandre Lev-Cohain, Naama Drozdzal, Michal Amitai, Michal Marianne Vivanti, Refael Sosna, Jacob Ezhov, Ivan Sekuboyina, Anjany Navarro, Fernando Kofler, Florian Paetzold, Johannes C. Shit, Suprosanna Hu, Xiaobin Lipková, Jana Rempfler, Markus Piraud, Marie Kirschke, Jan Wiestler, Benedikt Zhang, Zhiheng Hülsemeyer, Christian Beetz, Marcel Ettlinger, Florian Antonelli, Michela Bae, Woong Bellver, Míriam Bi, Lei Chen, Hao Chlebus, Grzegorz Dam, Erik B. Dou, Qi Fu, Chi-Wing Georgescu, Bogdan Giró-I-Nieto, Xavier Gruen, Felix Han, Xu Heng, Pheng-Ann Hesser, Jürgen Moltz, Jan Hendrik Igel, Christian Isensee, Fabian Jäger, Paul Jia, Fucang Kaluva, Krishna Chaitanya Khened, Mahendra Kim, Ildoo Kim, Jae-Hun Kim, Sungwoong Kohl, Simon Konopczynski, Tomasz Kori, Avinash Krishnamurthi, Ganapathy Li, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Lowengrub, John Ma, Jun Maier-Hein, Klaus Maninis, Kevis-Kokitsi Meine, Hans Merhof, Dorit Pai, Akshay Perslev, Mathias Petersen, Jens Pont-Tuset, Jordi Qi, Jin Qi, Xiaojuan Rippel, Oliver Roth, Karsten Sarasua, Ignacio Schenk, Andrea Shen, Zengming Torres, Jordi Wachinger, Christian Wang, Chunliang Weninger, Leon Wu, Jianrong Xu, Daguang Yang, Xiaoping Yu, Simon Chun-Ho Yuan, Yading Yue, Miao Zhang, Liping Cardoso, Jorge Bakas, Spyridon Braren, Rickmer Heinemann, Volker Pal, Christopher Tang, An Kadoury, Samuel Soler, Luc van Ginneken, Bram Greenspan, Hayit Joskowicz, Leo Menze, Bjoern Department of Informatics Technical University of Munich Germany Department of Quantitative Biomedicine University of Zurich Switzerland Ecole Polytechnique de Montréal Canada Department of Medical Imaging Radboud University Medical Center Nijmegen Netherlands Department of Biomedical Engineering Tel-Aviv University Israel Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany Philips Research China Philips China Innovation Campus Shanghai China School of Biomedical Engineering & Imaging Sciences King0s College London London United Kingdom Institute for AI in Medicine Technical University of Munich Germany Department of Computer Science Guangdong University of Foreign Studies China Institute for diagnostic and interventional radiology Klinikum rechts der Isar Technical University of Munich Germany Institute for Diagnostic and Interventional Neuroradiology Klinikum Rechts der Isar Technical University of Munich Germany Department of Hepatobiliary Surgery The Affiliated Drum Tower Hospital Nanjing University Medical School China Department of Computing Imperial College London London United Kingdom Institute for Tissue Engineering and Regenerative Medicine Helmholtz Zentrum München Neuherberg Germany Brigham and Women's Hospital Harvard Medical School United States School of Computer Science and Engineering The Hebrew University of Jerusalem Israel University of Pennsylvania PA United States Pte. Ltd. Singapore Medical Imaging and Reconstruction Lab Department of Engineering Design Indian Institute of Technology Madras India Sensetime Shanghai China Department of Radiology Perelman School of Medicine University of Pennsylvania United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PA United States Co. Ltd China MontréalQC Canada Department of Radiology Radiation Oncology and Nuclear Medicine University of Montréal

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created in collaboration with seven hospitals and research institutions. Seventy-five submitted liver and liver tumor segmentation algorithms were trained on a set of 131 computed tomography (CT) volumes and were tested on 70 unseen test images acquired from different patients. We found that not a single algorithm performed best for both liver and liver tumors in the three events. The best liver segmentation algorithm achieved a Dice score of 0.963, whereas, for tumor segmentation, the best algorithms achieved Dices scores of 0.674 (ISBI 2017), 0.702 (MICCAI 2017), and 0.739 (MICCAI 2018). Retrospectively, we performed additional analysis on liver tumor detection and revealed that not all top-performing segmentation algorithms worked well for tumor detection. The best liver tumor detection method achieved a lesion-wise recall of 0.458 (ISBI 2017), 0.515 (MICCAI 2017), and 0.554 (MICCAI 2018), indicating the need for further research. LiTS remains an active benchmark and resource for research, e.g., contributing the liver-related segmentation tasks in http://***/. In addition, both data and online evaluation are accessible via ***. © 2019, CC BY-NC-ND.

关键词： Deep learning

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Benchmark dataset for mid-price forecasting of limit order book data with machine learning methods

arXiv

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arXiv 2017年

作者： Ntakaris, Adamantios Magris, Martin Kanniainen, Juho Gabbouj, Moncef Iosifidis, Alexandros Laboratory of Signal Processing Tampere University of Technology Korkeakoulunkatu 1 Tampere Finland Laboratory of Industrial and Information Management Tampere University of Technology Korkeakoulunkatu 8 Tampere Finland Department of Engineering Electrical and Computer Engineering Aarhus University Inge Lehmanns Gade 10 Aarhus Denmark

Managing the prediction of metrics in high-frequency financial markets is a challenging task. An efficient way is by monitoring the dynamics of a limit order book to identify the information edge. This paper describes the first publicly available benchmark dataset of high-frequency limit order markets for mid-price prediction. We extracted normalized data representations of time series data for five stocks from the NASDAQ Nordic stock market for a time period of ten consecutive days, leading to a dataset of ≈4,000,000 time series samples in total. A day-based anchored cross-validation experimental protocol is also provided that can be used as a benchmark for comparing the performance of state-of-the-art methodologies. Performance of baseline approaches are also provided to facilitate experimental comparisons. We expect that such a large-scale dataset can serve as a testbed for devising novel solutions of expert systems for high-frequency limit order book data analysis. Copyright © 2017, The Authors. All rights reserved.

关键词： Regression analysis

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Author Correction: Drug screening of cancer cell lines and human primary tumors using droplet microfluidics

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Scientific reports 2019年第1期9卷 18660页

作者： Ada Hang-Heng Wong Haoran Li Yanwei Jia Pui-In Mak Rui Paulo da Silva Martins Yan Liu Chi Man Vong Hang Cheong Wong Pak Kin Wong Haitao Wang Heng Sun Chu-Xia Deng Cancer Centre Faculty of Health Sciences University of Macau Macau China. State-Key Laboratory of Analog and Mixed-Signal VLSI (AMSV) University of Macau Macau China. Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macau China. Instituto Superior Técnico Universidade de Lisboa Lisboa Portugal. Department of Computer and Information Science Faculty of Science and Technology University of Macau Macau China. Department of Electromechanical Engineering Faculty of Science and Technology University of Macau Macau China. Cancer Centre Faculty of Health Sciences University of Macau Macau China. cxdeng@umac.mo.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Notice of Violation of IEEE Publication Principles: Application of LDPC codes on PUF error correction based on code-offset construction

Notice of Violation of IEEE Publication Principles: Applicat...

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International Conference on ASIC

作者： Kai Sun Yingjie Lao Weiqiang Liu Xiaohu You Chuan Zhang National Mobile Communications Research Laboratory Southeast University Nanjing China Lab of Efficient Architectures for Digital-communication and Signal-processing (LEADS) Department of Electrical and Computer Engineering Clemson University Clemson SC USA College of Electronic and Information Engineering NUAA Nanjing China

Notice of Violation of IEEE Publication Principles "Application of LDPC Codes on PUF Error Correction Based on Code-offset Construction" by Kai Sun, Yingjie Lao, Weiqiang Liu, Xiaohu You, and Chuan Zhang Proceedings of the IEEE 12th International Conference on ASIC (ASICON), October 2017, pp. 867-870 After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles. This paper copies original text from the papers cited below. The original text was copied with references to the original author(s) and/or paper titles, but did not delineate sufficiently to identify the reused material. The first author, Kai Sun, was solely responsible for the misconduct, which was done without the knowledge of the other authors "On Error Correction for Physical Unclonable Functions" by Sven Puchinger, Sven Muelich, Martin Bossert, Matthias Hiller, Georg Sigl in the Proceedings of the International ITG Conference on Systems, Communications and Coding, February 2015 "A New Error Correction Scheme for Physical Unclonable Functions" by Sven Muelich, Martin Bossert in the Proceedings of the International ITG Conference on Systems, Communications and Coding, February 2017 As a newly emerging technology, physical unclonable functions (PUFs) have drawn a lot of attentions. For their cryptographic applications, error correction is an indispensable component to fight against environmental factors which influence PUFs' performance. Recently, BCH codes have been applied to the error correction part to enhance the stability of an cryptographic system using PUFs. In this paper, low-density parity-check (LDPC) codes are first used to correct errors caused by environmental factors and shown to perform better than BCH codes in some conditions. In addition, normalized minsum algorithm has been considered to balance the performance and complexity of LDPC decoding.

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Mathematical model of human forearm based muscle fiber tissues’ anisotropic characteristics

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Open Biotechnology Journal 2016年 10卷 234-238页

作者： Qin, Yu-Ping Zhang, Shuang Liu, Yi-He The Engineering and Technical College Chengdu University of Technology Leshan614000 China The College of Computer Science Neijiang Normal University Neijiang641000 China The State Key Laboratory of Analog and Mixed-signal VLSI University of Macau 999078 China The Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau 999078 China

On the basis of human muscle fiber tissues’ characteristics,it is first proposed to establish the analytical model of galvanic coupling intra-body communication channel. In this model,the parallel and the transverse electrical characteristics of muscular tissue are fully considered,and the model accurately presents the transmission mechanism of galvanic coupling intra-body communication signals in the channel. © Qin et al.

关键词： Analytical models

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An intra-body communication research platform based on virtual instrument

An intra-body communication research platform based on virtu...

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2017 13th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)

作者： Lin Shi Gao Yueming Zhang Hengfei Lu?ev Vasi? ?eljka Vai Mang-I Du Min Cifrek Mario Pun Sio-Hang College of Physics and Information Engineering Fuzhou University Key Lab of Medical Instrumentation & Pharmaceutical Technology of Fujian Province Faculty of Electrical Engineering and Computing University of Zagreb State Key Laboratory of Analog and Mixed Signal VLSI University of Macau Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Key Lab of Eco-industrial Green Technology of Fujian Province

An intra-body communication(IBC) research platform based on virtual instrument was established for the hardware design of IBC transceiver. Firstly, the feasibility of constructing IBC research platform using optic-coupling circuit was verified via comparison of three kinds of measurement methods based on virtual instrument. Then, ASK, FSK and BPSK modulation-demodulation were realized via Lab VIEW programming, and user interface of the platform was also designed. The platform could achieve signal transmission or recover under different coupling type, different channel distance and different modulation-demodulation method, etc., by means of dynamic adjusting of platform parameters. Experiment results of capacitive-coupling under the platform indicated the authenticity and feasibility of signal transmission. Finally, a full-floating IBC transceiver was designed aided by the parameters provided by the research platform under the scene of capacitive-coupling, FSK modulation and 180 cm channel distance. Moreover, Bit Error Rate(BER) of the transceiver was less than 1 e-5, which meant that it is effective and convenient for the design of IBC transceiver aided by virtual instrument platform.

关键词： Intra-body Communication(IBC) virtual instrument transceiver modulation-demodulation

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