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2nd International Conference on Eco engineering Development 2018, ICEED 2018

作者： Gunawan, Fergyanto E. Herriyandi Soewito, Benfano Mauritsius, Tuga Surantha, Nico Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia

A system for automatic detection of road damages is essential for logistics management. At the core of the system lies an algorithm for classification of damages. This work intends to establish such an algorithm. In the current proposal, the algorithm receives data of the probe vehicle rate of rotations, extracts statistics descriptive from the data to produce a feature vector, and finally, feeds the vector to a simple-three-layer neural network to classify the damages. The types of damages are limited to four cases: normal, pothole, speed bump, and expansion joint. For the development, a probe vehicle is used to produce 400 empirical data involving those four damage cases. By using Monte Carlo approach, the established neural network model is evaluated. The results show that the approach is able to classify the cases with 85% accuracy. The study also finds that the rates of pitch and roll to be the determining factors. © 2018 Institute of Physics Publishing. All rights reserved.

关键词： Neural network models

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Diabetes Classification Using Support Vector Machine: Binary Classification Model 4

Diabetes Classification Using Support Vector Machine: Binary...

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4th International Conference on Information and Communications Technology, ICOIACT 2021

作者： Rabiha, Suciana Ghadati Wibowo, Antoni Lukas Heryadi, Yaya Computer Science Department BINUS Graduate Program-Doctor of Computer Science. Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University 11480 Indonesia Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University 11480 Indonesia

ISBN: (纸本)9781665433945

One of the health problems that require special attention is diabetes, besides the growth of this disease infection is increasing in various circles ranging from children, adults, men, women and the elderly. So to detect diabetes at an early stage, machine learning algorithms are the right choice to help detect indications of diabetes. This paper presents experimental results related to the exploration of the use of a Super Vector Machine (SVM) for data classification of Diabetes. The model used in this experiment is the Binary Classification Model. Based on the test results, the highest accuracy is obtained by using a total of 700 lines of data, which is 75,7143%. The Best estimated feasible point in Box Constraint is 272.29 with a KernelScale area of 72.627. © 2021 IEEE

关键词： Face recognition

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Hybrid clutter canceler with feedback guided predicative filtering on a heterogeneous parallel processing system

Hybrid clutter canceler with feedback guided predicative fil...

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International Waveform Diversity and Design Conference, WDD 2012

作者： Brinkhus, Jeffrey M. Jezak, Joseph A. Berdanier, Charles Levitan, Steven P. Chiarulli, Donald M. Electical and Computer Engineering University of Pittsburgh United States Computer Engineering Graduate Program University of Pittsburgh United States Electrical Engineering Wright State University United States Computer Science Department University of Pittsburgh United States

ISBN: (纸本)9781509005987

In this paper we describe a novel clutter cancellation platform based on a two stage approach that combines a feedback guided predictive front-end hybrid clutter canceller with high performance back-end filtering and target detection. The front-end architecture is based on an FPGA implementation of a Kalman filter that predicts target locations in real time and removes the target signals from the incoming data prior to hybrid cancellation. The back-end is user configurable and exploits high performance GPU and multi-core parallel hardware to simultaneously compute multiple clutter suppression and target detection algorithms coupled to an intelligent selection strategy for selecting the most accurate result. These target locations are fed back to the FPGA Kalman filter periodically to update the target predictions. © 2012 IEEE.

关键词： Kalman filters

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Aerodynamic Effects Compensation on Multi-Rotor UAVs Based on a Neural Network Control Allocation Approach

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IEEE/CAA Journal of Automatica Sinica 2022年第2期9卷 295-312页

作者： Sarah P.Madruga Augusto H.B.M.Tavares Saulo O.D.Luiz Tiago P.do Nascimento Antonio Marcus N.Lima Graduate Program of Electrical Engineering Universidade Federal de Campina GrandeCampina Grande-PBBrazil Department of Electrical Engineering Universidade Federal de Campina GrandeCampina Grande-PBBrazil IEEE Department of Computer Systems Universidade Federal da ParaibaJoao Pessoa-PBBrazil

This paper shows that the aerodynamic effects can be compensated in a quadrotor system by means of a control allocation approach using neural ***,the system performance can be improved by replacing the classic allocation matrix,without using the aerodynamic inflow equations *** network training is performed offline,which requires low computational *** target system is a Parrot MAMBO drone whose flight control is composed of PD-PID controllers followed by the proposed neural network control allocation *** a quadrotor is particularly susceptible to the aerodynamics effects of interest to this work,because of its small *** compared the mechanical torques commanded by the flight controller,i.e.,the control input,to those actually generated by the actuators and established at the *** was observed that the proposed neural network was able to closely match them,while the classic allocation matrix could not achieve *** allocation error was also determined in both ***,the closed-loop performance also improved with the use of the proposed neural network control allocation,as well as the quality of the thrust and torque signals,in which we perceived a much less noisy behavior.

关键词： Aerodynamics effects control allocation minidrone multi-rotor UAV neural networks

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Towards a Double Hybrid VTOL UAV System∗∗This work was supported by CAPES grant number 001 17

Towards a Double Hybrid VTOL UAV System∗∗This work was sup...

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17th Latin American Robotics Symposium, 12th Brazilian Symposium on Robotics and 11th Workshop on Robotics in Education, LARS-SBR-WRE 2020

作者： Lucena, Alysson N. Goncalves, Luiz M.G. Graduate Program in Electrial and Computer Engineering of Universidade Federal Do Rio Grande Do Norte Natal59.076-200 Brazil

ISBN: (纸本)9780738111537

We draw complete efforts towards the development of a double hybrid tailsitter UAV system, which is basically composed of a multirotor with 2 electric powertrain sets and a flying wing with combustion powertrain set. Our goal is to design a UAV that diminishes consumption for vertically taking off and landing and to perform the horizontal flight with greatest possible autonomy on flight time and distance. Considering these requirements, the UAV is conceptualized and built as a flying wing propelled by a pusher configuration powerplant, with combustion engine propeller, a multi-engine composed of two powerplant sets with electric motors and propellers, positioned on the leading edge of the wing, and two standard elevation control surfaces and two vertical stabilizers that also have the support function for takeoff and landing. Several takeoff, flight, and transition tests were carried out successfully, but autonomy (time and distance) tests due to the COVID19 pandemic. Results show versatility of the hybrid tailsitter for operations in the flight field, in a limited location. The built prototype has proven to be functional and the hybrid system effective, to date. © 2020 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Plasmonic bacteria on a nanoporous mirror via hydrodynamic trapping for rapid identification of waterborne pathogens

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Light(Science & Applications) 2018年第1期7卷 359-367页

作者： Keumrai Whang Jong-Hwan Lee Yonghee Shin Wooju Lee Young Wan Kim Dongchoul Kim Luke P.Lee Taewook Kang Department of Chemical and Biomolecular Engineering Sogang UniversitySeoul 04107Korea Berkeley Sensor and Actuator Center Departments of BioengineeringElectrical Engineering and Computer ScienceBiophysics Graduate ProgramUniversity of CaliforniaBerkeleyBerkeleyCA 94720USA Department of Mechanical Engineering Sogang UniversitySeoul 04107Korea

A rapid,precise method for identifying waterborne pathogens is critically needed for effective disinfection and better ***,conventional methods,such as culture-based counting,generally suffer from slow detection times and low ***,we developed a rapid detection method for tracing waterborne pathogens by an innovative optofluidic platform,a plasmonic bacteria on a nanoporous mirror,that allows effective hydrodynamic cell trapping,enrichment of pathogens,and optical signal *** designed and simulated the integrated optofluidic platform to maximize the enrichment of the bacteria and to align bacteria on the nanopores and plasmonic mirror via hydrodynamic cell *** nanoparticles are self-assembled to form antenna arrays on the surface of bacteria,such as Escherichia coli and Pseudomonas aeruginosa,by replacing citrate with hydroxylamine hydrochloride in order to amplify the signal of the plasmonic optical *** to the synergistic contributions of focused light via the nanopore geometry,self-assembled nanoplasmonic optical antennas on the surface of bacteria,and plasmonic mirror,we obtain a sensitivity of detecting *** as low as 102 cells/ml via surface-enhanced Raman *** believe that our label-free strategy via an integrated optofluidic platform will pave the way for the rapid,precise identification of various pathogens.

关键词： mirror trapping precise

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Dynamic Sampling-Based Meta-Learning Using Multilingual Acoustic Data for Under-Resourced Speech Recognition

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IEEE Access 2024年 12卷 106070-106083页

作者： Hsieh, I-Ting Wu, Chung-Hsien Zhao, Zhe-Hong National Cheng Kung University Graduate Program of Multimedia Systems and Intelligent Computing Tainan70101 Taiwan National Cheng Kung University Department of Computer Science and Information Engineering Tainan70101 Taiwan

Under-resourced automatic speech recognition (ASR) has become an active field of research and has experienced significant progress during the past decade. However, the performance of under-resourced ASR trained by existing methods is still far inferior to high-resourced ASR for practical applications. In this paper, speech data from languages that share the most phonemes with the under-resourced language are selected as supplementary resources for meta-training based on the Model-Agnostic Meta-Learning (MAML) strategy. Besides supplementary language selection, this paper proposes a dynamic sampling method instead of the original random sampling method to select support and query sets for each task in MAML to improve meta-training performance. In this study, Taiwanese is selected as the under-resourced language, and the speech corpus of five languages, including Mandarin, English, Japanese, Cantonese, and Thai, are chosen as supplementary training data for acoustic model training. The proposed dynamic sampling approach uses phonemes, pronunciation, and speech recognition models as the basis to determine the proportion of each supplementary language to select helpful utterances for MAML. For evaluation, with the selected utterances from each supplementary language for meta-training, we obtained a Word Error Rate of 20.24% and a Syllable Error Rate of 8.35% for Taiwanese ASR, which were better than the baseline model (26.18% and 13.99%) using only the Taiwanese corpus and other methods. © 2013 IEEE.

关键词： Speech recognition

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A progress report and a proposal: Interactivity in ubiquitous learning enhanced by virtual tutors in e-learning contents

A progress report and a proposal: Interactivity in ubiquitou...

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2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing, SUTC 2008

作者： Yamamoto, Toshiyuki Miyashita, Ryo Department of Media Informatics Kanazawa Institute of Technology Japan Graduate Program in Information and Computer Engineering Kanazawa Institute of Technology Japan

ISBN: (纸本)9780769531588

It is proposed in this session that the interactivity necessary in ubiquitous learning can be enhanced by the virtual tutor who mediates between the learner and the e-Learning contents. Arousing students' intellectual curiosity and raising their motivation to learn are the two great goals for e-Learning contents developers. It is supposed that the interaction in the communication between the teacher and his/her students in a regular classroom can be maintained in e-Learning with the help of Virtual Tutor, which appears on the learning contents in a timely fashion to give learners advice, encouragement, reminders, and such. The session includes discussions to develop such a system making use of the most updated technology as well as demonstrations of such a system which has been experimented at Department of Media Informatics. It is proved that the learning environment where human interactivity is essential can be reconstructed in terms of the proposed Virtual Tutor. This paper presentation includes demonstrations of QED as well as a discussion of the importance of interactivity in ubiquitous e-Learning. © 2008 IEEE.

关键词： Students

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Industry-Academy Collaboration in Agile Methodology: a Systematic Literature Review 17

Industry-Academy Collaboration in Agile Methodology: a Syste...

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17th Iberian Conference on Information Systems and Technologies, CISTI 2022

作者： Marques, Denis de Gois de A. Dallegrave, Tamara Larissa D. Lima Barbosa, Luis E. de Oliveira Rodrigues, Cleyton M. Santos, Wylliams Barbosa Graduate Program in Computer Engineering Polytechnic School of Pernambuco POLI/UPE Recife Brazil University of Pernambuco UPE Caruaru Brazil

ISBN: (纸本)9789893334362

Industry-Academy Collaborative Research (IAC) in Software engineering is being applied and developed widely in practice. These collaborative, research practices help both academic and software industry environments. As a way of observing what is being developed in SE, the objective of this article is to present an exploratory and empirical study of IAC practices in the context of Agile Software Development (ASD), exploring and characterizing solutions and practices, the challenges encountered in the application of the IAC and in collaboration. A Systematic Literature Review (SLR) was carried out in the five main academic databases, and snowballing was applied, evaluating/analyzing 8.460 articles, totaling 21 articles approved following the proposed criteria. As a result of the data analysis, 76 good practices and 37 challenges in carrying out the IAC were described. As well, practical collaborative models for the application of the IAC were detailed. © 2022 IEEE computer Society. All rights reserved.

关键词： Application programs

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Metasurfaces for next-generation wireless communication systems

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National Science Review 2023年第8期10卷 17-19页

作者： Younes Ra'di Nikita Nefedkin Petar Popovski Andrea Alù Department of Electrical Engineering and Computer Science Syracuse University Photonics Initiative Advanced Science Research Center City University of New York Department of Electronic Systems Aalborg University Physics Program Graduate Center City University of New York

The pace of development in the world of 5G communication systems has proven to be much more demanding than previous generations, with 5G-Advanced seemingly around the corner [1]. Extensive research is already underway to structure the next generation of wireless systems(i.e. 6G), which may potentially enable an unprecedented level of human–machine interaction [2].

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