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5th International Young Engineers Forum in Electrical and computer engineering, YEF-ECE 2021

作者： Neves, Francisco Oliveira, João P. Oliveira, Henrique Dpt. of Electrical and Computer Engineering NOVA School of Science and Technology Caparica Portugal CTS UNINOVA Caparica Portugal Instituto de Telecomunicações Lisboa Portugal Instituto Politécnico de Beja Beja Portugal

ISBN: (纸本)9781665412643

This paper presents the design of a low-noise capacitively-coupled instrumentation amplifier with a sub-1V power supply, which is suitable for low-power sensor data acquisition systems. This amplifier is part of an Analog Front-end (AFE) which is implemented in a standard 130nm bulk CMOS technology. Beside the high-impedance input amplifier, the AFE includes a programmable switch-capacitor bandpass filter and a sigma-delta modulator. A chopper modulation technique is implemented to further reduce the flicker noise, with a positive feedback network to compensate the resulting low input impedance. The preliminary post-layout simulated results of the instrumentation amplifier achieves a total power consumption of 2.6µW, with an open loop gain of 87dB and a GBW of 584kHz and with the input reffered noise of 4.6µVrms and a NEF value of 4. The maximum CMRR of the amplifier is 101dB and the PSRR minus is greater than 66dB. For a sub 1V power supply, the input frequency range is up to 10 kHz. © 2021 IEEE.

关键词： Bandpass filters

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Amberate: A framework for automated vulnerability scanners for web applications

Computer Software

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computer Software 2011年第4期28卷 175-195页

作者： Kosuga, Yuji Kono, Kenji Dept. of Information and Computer Science Keio University Japan Dpt. of Information and Computer Science Keio University Japan CREST Core Research for Evolutional Science and Technology Japan Science and Technology Agency Japan

Many new attacks targeting web applications have been showing up one after another. However, when implementing a new vulnerability detection technique, the existing vulnerability scanners impose a burdensome task of modifying source code and installing many auxiliary functions. In this paper, we introduce the design of Amberate;a web vulnerability scanner that alleviates the burden of them and makes it easier to develop a new vulnerability detection technique.

关键词： Scanning

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A Probability Model for the Size of Investment Projects

A Probability Model for the Size of Investment Projects

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computer Modeling and Simulation, EMS, UKSIM European Symposium on FLAGGED

作者： Maurizio Naldi Dpt. of Computer Science and Civil Engineering Università di Roma Tor Vergata Rome Italy

ISBN: (纸本)9781509002078

Project size, as measured by the amount of investment required, is a relevant parameter to be used in project selection. The evaluation of a project portfolio must consider the variety of project sizes that may be met, so that a proper model should be adopted to describe that variety, especially for its use in simulation. In this paper, a log-normal probability model is suggested to describe the dispersion of project sizes within a project portfolio. The model is obtained on the basis of two real datasets spanning over ten years of observations, and after comparison with competing Gamma and Pareto models. The parameters of the log-normal model are provided as resulting from the best-fit procedure, and indications are also given for the values to use in a simulation study.

关键词： Portfolios Computational modeling Predictive models Data models Investment Probability density function Companies

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DPPL Hallway Tracker: Hospital Contact Tracing During the COVID-19 Pandemic 9

DPPL Hallway Tracker: Hospital Contact Tracing During the CO...

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9th Scholar's Yearly Symposium of Technology, engineering and Mathematics, SYSTEM 2023

作者： Marinoni, Christian Ponzi, Valerio Comminiello, Danilo Dpt. of Information Engineering Electronics and Telecommunications Sapienza University of Rome Via Eudossiana 18 Roma00184 Italy Department of Computer Control and Management Engineering Sapienza University of Rome Via Ariosto 25 Roma00185 Italy Institute for Systems Analysis and Computer Science Italian National Research Council Via dei Taurini 19 Roma00185 Italy

During the COVID-19 pandemic, the use of a people tracking system could have been crucial, particularly in sensitive environments, such as hospitals. DPPL Hallway Tracker is a framework that uses security camera footage to determine which rooms in a corridor a person has entered. It generates a database containing all the people identified and allows quick identification of potential cases of infection based on the time spent in a room and its maximum capacity. DPPL Hallway Tracker is structured in two phases: detection and re-identification. In the first phase, it exploits Mask RCNN to identify people and room doors. In the second one, it uses the deep association metric model from DeepSORT to re-identify a person as he leaves a room. © 2023 Copyright for this paper by its authors.

关键词： COVID-19

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Order-preserving factor discovery from misaligned data

Order-preserving factor discovery from misaligned data

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2010 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2010

作者： Puig, Arnau Tibau Wiesel, Ami Zaas, Aimee Ginsburg, Geoffrey S. Fleury, Gilles Hero III, Alfred O. Dpt. of Electrical Engineering University of Michigan United States E3S - SUPELEC Systems Sciences Signal Processing and Electronic Systems Department Supélec France School of Computer Science and Engineering Hebrew University of Jerusalem Israel Institute for Genome Sciences and Policy Duke University United States Division of Infectious Diseases and International Health Dpt. of Medicine Duke University School of Medicine United States

ISBN: (纸本)9781424489770

We present a factor analysis method that accounts for possible temporal misalignment of the factor loadings across the population of samples. Our main hypothesis is that the data contains a subset of variables with similar but delayed profiles obeying a consistent precedence ordering relationship. Our model is motivated by the difficulty of gene expression analysis across subjects who have common patterns of immune response but show different onset times after a uniform innoculation time of a viral pathogen. The proposed method is based on a linear model with additional degrees of freedom that account for each subject's inherent delays. We present an algorithm to fit this model in a totally unsupervised manner and demonstrate its effectiveness on extracting gene expression factors affecting host response using a flu-virus human challenge study dataset. © 2010 IEEE.

关键词： Gene expression

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Developing Distributed Reasoning-Based Applications for the Semantic Web

Developing Distributed Reasoning-Based Applications for the ...

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International Conference on Advanced information Networking and Applications Workshops (AINAW)

作者： Dimitrios Koutsomitropoulos Georgia Solomou Tzanetos Pomonis Panagiotis Aggelopoulos Theodore Papatheodorou High Performance Information Systems Laboratory Computer Engineering and Informatics Dpt. University of Patras Patras Greece

ISBN: (纸本)9781424467013;9780769540191

In order for Semantic Web applications to be successful a key component should be their ability to take advantage of rich content descriptions in meaningful ways. Reasoning consists a key part in this process and it consequently appears at the core of the Semantic Web architecture stack. From a practical point of view however, it is not always clear how applications may take advantage of the knowledge discovery capabilities that reasoning can offer to the Semantic Web. In this paper we present and survey current methods that can be used to integrate inference-based services with such applications. We argue that an important decision is to have reasoning tasks logically and physically distributed. To this end, we discuss relevant protocols and languages such as DIG and SPARQL and give an overview of our Knowledge Discovery Interface. Further, we describe the lessons-learned from remotely invoking reasoning services through the OWL API.

关键词： Semantic Web Application software OWL Protocols Service oriented architecture Ontologies Conferences information systems Laboratories computer networks

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When free riding is the best choice: The case of network charges for content providers

When free riding is the best choice: The case of network cha...

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International Conference on Network and Service Management

作者： Maurizio Naldi Giuseppe D'Acquisto Università di Roma Tor Vergata Dpt. of Computer Science and Civil Engineering Roma Italy

Content providers are often accused of free riding by exploiting the network to distribute their content without sharing their revenues with the network providers. In order to assess the correctness of such an accusation, we set up a game-theoretical model, where content providers releasing their contents for free and under the payment of a usage-based charge are both present. In this model, the network provider charges both content providers a usage-based charge (network charge) as well. The network provider and the paid content provider act as the players, using the respective retail prices as strategic leverages. Both the cases where network charges are set by the network provider and by a regulatory authority are examined. The Nash equilibrium is determined in a closed form. In a typical scenario, the solution represented by zero network charges maximizes both the network provider's revenues and the social welfare: free riding for content providers appears as the best choice under both the viewpoints of the selfish network provider and the regulatory authority.

关键词： Games Advertising Equations Network neutrality Conferences Nash equilibrium

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Deep Learning Based Framework for Multi-disease Detection Using CNN-BiLSTM 12th

Deep Learning Based Framework for Multi-disease Detection U...

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12th International Conference on Soft Computing for Problem Solving, SocProS 2023

作者： Yadav, Pooja Sharma, S.C. Yadav, Hemant Electronics & Computer Discipline DPT IIT Roorkee Uttarakhand India Department of Computer Science and Information Technology MJP Rohilkhand University Uttar Pradesh Bareilly India Department of Computer Science Future Institute of Engineering and Technology Uttar Pradesh Bareilly India

ISBN: (纸本)9789819732913

There has been a surge in interest in developing accurate and efficient illness prediction models to help in early diagnosis and treatment planning in recent years. Despite innovations in deep learning techniques, there is enormous potential for leveraging these techniques for illness prediction across different domains. This study presents a deep learning-based technique for predicting multiple diseases, like diabetes, liver, and Kidney, to improve diagnosis accuracy and facilitate prompt treatments. In this paper, the authors employ two deep learning algorithms, CNN, LSTM, and proposed CNN-BILSTM, to determine if patients are at risk of illness. The suggested CNN-BiLSTM approaches outperform others for all three diseases, representing a major improvement, especially for a disease that impacts a large population. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Forecasting

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Forecast Uncertainty in Procurement Decisions for Cloud Storage

Forecast Uncertainty in Procurement Decisions for Cloud Stor...

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International Conference on computer Modeling and Simulation, UKSIM

作者： Maurizio Naldi Dpt. of Computer Science and Civil Engineering Università di Roma Tor Vergata Roma Italy

In public vs. private solutions (i.e. Cloud vs. In-house, or leased vs. Owned) for storage, both alternatives have their pros and cons. Cloud storage can easily adapt to the company needs, but exhibits a higher unit cost than in-house solutions. On the other hand, if the company relies on its own storage equipment, it must periodically purchase it on the basis of forecasts, which may prove imprecise and lead to idle equipment. In this paper, we propose a comparative evaluation tool for the two procurement approaches, where the cloud can play the role of either exclusive storage medium or supplement to in-house equipment (in the case of underestimation of storage needs). The tool considers the impact of equipment acquisition intervals and forecast accuracy over a long time horizon, adopting a Geometric Brownian Motion model for the evolution of storage capacity needs, it can be employed as a decision support tool for procurement decisions.

关键词： Cloud computing Companies Procurement Market research Stochastic processes Mathematical model Computational modeling

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WSRNet: Joint spotting and recognition of handwritten words

arXiv

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arXiv 2020年

作者： Retsinas, George Sfikas, Giorgos Maragos, Petros School of Electrical and Computer Engineering National Technical University of Athens Greece Dpt. of Computer Science and Engineering University of Ioannina Greece

In this work, we present a unified model that can handle both Keyword Spotting and Word Recognition with the same network architecture. The proposed network is comprised of a non-recurrent CTC branch and a Seq2Seq branch that is further augmented with an Autoencoding module. The related joint loss leads to a boost in recognition performance, while the Seq2Seq branch is used to create efficient word representations. We show how to further process these representations with binarization and a retraining scheme to provide compact and highly efficient descriptors, suitable for keyword spotting. Numerical results validate the usefulness of the proposed architecture, as our method outperforms the previous state-of-the-art in keyword spotting, and provides results in the ballpark of the leading methods for word recognition. Copyright © 2020, The Authors. All rights reserved.

关键词： Vocabulary control

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