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IEEE Instrumentation and Measurement technology Conference

作者： Herti Miawarni Tri Arief Sardjono Eko Setijadi Wijayanti Mauridhi Hery Purnomo Dept. of Electrical Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember Surabaya Indonesia Dept. of Electrical Engineering Dept. of Biomedical Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember Surabaya Indonesia Dept. of Architecture Faculty of Engineering Universitas Diponegoro Semarang Indonesia Dept. of Electrical Engineering Dept. of Computer Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember University Center of Excellence on Artificial Intelligence for Healthcare and Society (UCE AIHeS) Surabaya Indonesia

Recently, many countries have been dealing with an increasing amount of elderly who are living alone. Unfortunately, fall incidents in the elderly tend to happen, and without proper dependable care would lead to fatal injuries. The elderly must be closely monitored under constant observation. Accidental falls are a leading cause of injury, mortality, and mobility limitations in the elderly. The expenses of national healthcare systems are also significantly impacted by accidental falls. These findings highlight the importance of investing heavily in the study and advancement of fall detection and intervention technologies. It is essential to recognize them early and provide fast assistance by developing technologies that can simultaneously improve the standard and the safety of the elderly's living environment. In this paper, we present a computer vision algorithm for falling incident detection using a low-cost camera and deep learning model. Ultimately, this algorithm can be used for the cases of elderly, in which falling risk is high and fatal. Furthermore, one self-developed dataset was used to validate the suggested approach experimentally. We used an OpenPose-based feature using a low-cost camera input and then classified each event or activity as either fall or non-fall. Classification tasks are carried out by Long Short-Term Memory (LSTM) with multiple validation metrics. The LSTM in this work is also optimized using Bayesian method. Finally, our approach to recognize falls has accuracy of 99.5%, which is distinct from other past works.

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Reliability assurance in early-life-failure test through improved nearest neighbor regression

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IEICE Electronics Express 2020年第2期17卷

作者： Song, Tai Liang, Huaguo Huang, Zhengfeng Hou, Jie Dept. of Electronic Science and Applied Physics Hefei University of Technology Hefei230009 China Institute of Computer Architecture and Computer Stuttgart University StuttgartD-70569 Germany

During manufacturing test, researchers usually overlook the importance of process variation defects and marginal defects, which can seriously affect test results of Early-Life-Failure (ELF). Theoretically, machine learning classification methods can be used to identify these two defects. In fact, when features overfitting or data distribution overlap seriously, classifiers perform poorly, it will not achieve the desired results. This paper first-ever proposes a kind of data preprocessing method combines improved K-Nearest Neighbors (KNN) regression classifier, so that the classification results will be enhanced in terms of classification performance. Experiment results demonstrate that the predictive accuracy is 45% higher than the traditional logistic regression method. This proposed method will drive critical new requirements for fault modeling, test generation and test application, and implementing them effectively will require a new level of collaboration between process and product developers. © 2020 Institute of Electronics Information Communication Engineers. All rights reserved.

关键词： Defects

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Wind speed prediction and insight for generalized predictive modeling framework: a comparative study for different artificial intelligence models

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Neural Computing and Applications 2024年第23期36卷 14119-14150页

作者： Bhagat, Suraj Kumar Tiyasha, Tiyasha Shather, A.H. Jamei, Mehdi Kumar, Adarsh Al-Khafaji, Zainab Goliatt, Leonardo Shafik, Shafik S. Alawi, Omer A. Yaseen, Zaher Mundher Faculty of Civil Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam Department of Computer Engineering Technology Al Kitab University Altun Kopru Kirkuk00964 Iraq Faculty of Civil Engineering and Architecture Shahid Chamran University of Ahvaz Ahvaz Iran Canadian Centre for Climate Change and Adaptation University of Prince Edward Island St PetersPE Canada Building and Construction Techniques Engineering Department College of Engineering and Engineering Techniques Al-Mustaqbal University Hillah Babylon51001 Iraq Department of Computational and Applied Mechanics Federal University of Juiz de Fora Juiz de Fora Brazil Experimental Nuclear Radiation Research Group Scientific Research Center Al-Ayen University Thi-Qar64001 Iraq Johor Bahru Skudai81310 Malaysia Civil and Environmental Engineering Department King Fahd University of Petroleum and Minerals Dhahran31261 Saudi Arabia Department of Civil Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Dehradun India Dept of Environmental Science Gitam School of Science GITAM University Visakhapatnam India

Wind speed (WS) has played a vital role in local urban and sub-urban weather, agriculture, and ecosystem. Several meteorological parameters are influencing WS such as relative humidity (at 2 m, %), surface pressure (kPa), maximum temperature (at 2 m, °C), minimum temperature (at 2 m, °C), average temperature (at 2 m, °C), and all sky insolation incident on a horizontal surface (kW-h/m2/day). The current research was conducted to predict WS at different locations at Vietnam using the feasibility of computer aid models (i.e., multivariate adaptive regression splines (MARS), extreme gradient boosting (XGBoost) and random forest generator (Ranger)). Pearson correlation (PC) was investigated to select the high significant predictors to predict the WS at 10 m high. All inputs (maximum number, 6) are chosen by the PC approach for PhuongNinh, DaNang, and HaNoi;and for minimum number of inputs i.e four, are selected for PhuongHung, CanTho, and SaPa city;that exhibit the relationship with WS, citywise. The sequence selection of input parameters differed in each station as per the PC analysis. Based on the statistical evaluation and graphical presentation, MARS model attained the best prediction results, followed by XGBoost and Ranger. MARS predictive model remains at the top performance among others based on 95% confidence interval. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Forecasting

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Predicting directional sound-localization of human listeners in both horizontal and vertical dimensions 148

Predicting directional sound-localization of human listeners...

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148th Audio Engineering Society International Convention 2020

作者： Barumerli, Roberto Majdak, Piotr Reijniers, Jonas Baumgartner, Robert Geronazzo, Michele Avanzini, Federico Dept. of Information Engineering University of Padova Italy Acoustics Research Institute Austrian Academy of Sciences Austria Dept. of Engineering Management University of Antwerp Belgium Dept. of Architecture Design and Media Technology Aalborg University Denmark Dept. of Computer Science University of Milano Italy

Measuring and understanding spatial hearing is a fundamental step to create effective virtual auditory displays (VADs). The evaluation of such auralization systems often requires psychoacoustic experiments. This process can be time consuming and error prone, resulting in a bottleneck for the evaluation complexity. In this work we evaluated a probabilistic auditory model for sound localization intended as a tool to assess VAD's abilities to provide static sound-localization cues to listeners. The outcome of the model, compared with actual results of psychoacoustic experiments, shows the advantages and limitations of this systematic evaluation. © 2020 148th Audio Engineering Society International Convention. All rights reserved.

关键词： Audition

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JKinect: A new Java Software for Designing and Assessing Gross Motor Activities in children with autism based on JFML

JKinect: A new Java Software for Designing and Assessing Gro...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Juan Carlos Gámez-Granados Francisco Javier Rodriguez-Lozano Giovanni Acampora Chang-Shing Lee Jose Manuel Soto-Hidalgo Dept. Electr. & Computer Engineering University of Córdoba Spain Dept. Physics Ettore Pancini University of Naples Federico II Italy Dept. Computer Science & Information Engineering National University of Tainan Taiwan Dept. Computer Architecture and Computer Technology University of Granada Spain

ISBN: (数字)9781728169323

ISBN: (纸本)9781728169330

Motor therapies can be considered as one of the social challenges that have a great impact in children with autism. Traditionally, exercises and activities as therapies have been used to mitigate and to rehabilitate problems related to gross motor skills. Nevertheless, from the perspective of children, these therapies are often repetitive, boring and they need an extra motivation aspect due to the target: children with autism. From the point of interaction with the target population, the use of technology is a key issue in these therapies. In this scenario, a new software named JKinect which is based on RGB-D sensors and computer based games. JKinect helps children with gross motor problems and presents great flexibility in the therapy design and game sharing among specialists. Additionally, a new module for linking JKinect with both fuzzy systems based on the IEEE std 1855-2016 and the JFML library to support experts' decision making in therapies on the basis of fuzzy rules is also included.

关键词： Medical treatment Libraries Games Autism XML Fuzzy logic IEEE Standards

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A Double Layer Frequency Selective Surface using Interdigital Split Ring Resonators and Applications

A Double Layer Frequency Selective Surface using Interdigita...

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2020 International Conference on Power, Energy and Innovations, ICPEI 2020

作者： Archevapanich, Tuanjai Chomtong, Pongsathorn Akkaraekthalin, Prayoot Rajamagala University of Technology Suvarnabhumi Faculty of Engineering and Architecture Dept. of Electronics and Communication Engineering Nonthaburi Thailand King Mongkut's University of Technology North Bangkok Faculty of Technical Education Dept. of Teacher Training in Electrical Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Dept. of Electrical and Computer Engineering Bangkok Thailand

ISBN: (纸本)9781728172408

This paper proposes a split ring resonator unit cell using interdigital structure. The size can be reduced from λ/2 to about λ/4 caused by the slow wave effect. An array of 14×14 unit cells can be formed to act as a frequency selective surface (FSS). The proposed FSS is designed at frequency of 1.8 GHz, which the length of unit cell is 11.48 mm and the length of FSS is 172.50 mm. Using double layer FSS, the effect of coupling between layers will result in a larger bandwidth from 1.8 GHz to 2.45 GHz. The simulation results when applying a dipole antenna over the double layer FSS show that the high antenna gains of 8.34 dB and 9.75 dB are obtained at 1.8 GHz to 2.45 GHz, respectively. The proposed double layer FSS with a dipole can be applied for modern communication systems including LTE and WLAN. © 2020 IEEE.

关键词： Frequency selective surfaces

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A Dual Band Split Ring Electromagnetic Band Gap using Interdigital Technique and its Applications

A Dual Band Split Ring Electromagnetic Band Gap using Interd...

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2020 International Conference on Power, Energy and Innovations, ICPEI 2020

ISBN: (纸本)9781728172408

This paper proposes the electromagnetic band gap (EBG) reflector using split ring resonator with interdigital technique. The capacitive value between split ring gaps has the results of slow-wave effect in transmission line, that can reduce the size of split ring resonator unit cell from λ/2 to about λ/4. Moreover, it can control the second harmonics to resonance at the required frequency for the second band operation. The unit cell will be designed at the fundamental frequency of 1.8 GHz and the second resonance frequency of 2.4 GHZ, which are the frequency bands of LTE and WLAN systems. The unit cells are arranged in an array to act as a reflector for a dipole antenna. The simulation results at both operating frequency bands show the antenna gains of 8.17 dB and 8.29 dB at 1.8 GHz (460 MHz bandwidth) and 2.4 GHz (470 MHz bandwidth), respectively. © 2020 IEEE.

关键词： Dipole antennas

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A Machine Vision-Based Person Detection Under Low-Illuminance Conditions Using High Dynamic Range Imagery for Visual Surveillance System

A Machine Vision-Based Person Detection Under Low-Illuminanc...

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Smart Technologies in Computing, Electrical and Electronics (ICSTCEE), International Conference on

作者： Julie Ann B. Susa Sammy V. Militante Aimee G. Acoba Ryan Soriente Evangelista Luisito Lolong Lacatan Charlemagne G. Laviňa Bartolome T. Tanguilig Dept. of Computer Engineering Southern Luzon State University Lucban Quezon Philippines College of Engineering and Architecture University of Antique Antique Philippines Electronics Eng'g Technology Department Technological University of the Philippines Manila Philippines School of Graduate Studies Sulu State College Sulu Philippines College of Computing and Engineering Pamantasan ng Cabuyao Laguna Philippines

The most difficult component of any computer vision application objects recognition and tracking. Video surveillance is a major study subject in computer vision in a dynamic environment, especially for security purposes. Video surveillance technology is critical in preventing crime, terrorism, and other threats. Several existing technologies can accurately monitor a person's mobility in interior environments. As well as regulated outdoor settings, object recognition and tracking at night, on the other hand, remain significant challenges for visual surveillance. The objects are usually farther away, inconspicuous, and have low brightness against the background. In this paper, detecting objects specifically people under low lighting conditions with the help of deep learning algorithms was used. For applications like in-car cameras and surveillance systems that operate in low light, these algorithms might improve picture identification performance.

关键词： Deep learning Training Visualization computer vision Heuristic algorithms Computational modeling Lighting

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On robot compliance. A cerebellar control approach

arXiv

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arXiv 2020年

作者： Abadía, Ignacio Naveros, Francisco Garrido, Jesús A. Ros, Eduardo Luque, Niceto R. Research Centre for Information and Communication Technologies Dept. Computer Architecture and Technology U. Granada Granada18014 Spain

The work presented here is a novel biological approach for the compliant control of a robotic arm in real time (RT). We integrate a spiking cerebellar network at the core of a feedback control loop performing torque driven control. The spiking cerebellar controller provides torque commands allowing for accurate and coordinated arm movements. To compute these output motor commands, the spiking cerebellar controller receives the robot’s sensorial signals, the robot’s goal behaviour, and an instructive signal. These input signals are translated into a set of evolving spiking patterns, representing univocally a specific system state at every point of time. Spike Timing-Dependent Plasticity (STDP) is then supported, allowing for building adaptive control. The spiking cerebellar controller continuously adapts the torque commands provided to the robot from experience as STDP is deployed. Adaptive torque commands, in turn, help the spiking cerebellar controller to cope with built-in elastic elements within the robot’s actuators mimicking human muscles (inherently elastic). We propose a natural integration of a bio-inspired control scheme, based on the cerebellum, with a compliant robot. We prove that our compliant approach outperforms the accuracy of the default factory-installed position control in a set of tasks used for addressing cerebellar motor behaviour: controlling six degrees of freedom (DoF) in (i) smooth movements, (ii) fast ballistic movements and (iii) unstructured scenario compliant movements. Copyright © 2020, The Authors. All rights reserved.

关键词： Brain

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Improving evolution of service configurations for moving target defense

Improving evolution of service configurations for moving tar...

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Congress on Evolutionary Computation

作者： Ernesto Serrano-Collado Mario García-Valdez Juan J. Merelo-Guervós University of Granada Granada Spain Instituto Tecnológico de Tijuana Dept. of Computer Architecture and Technology University of Granada Granada Spain

ISBN: (数字)9781728169293

ISBN: (纸本)9781728169309

The term moving target defense or MTD describes a series of techniques that change the configuration of an Internet-facing system; in general, the technique consists of changing the visible configuration to avoid offering a fixed target to service profiling techniques. Additionally, configurations need to be as secure as possible and, since change needs to be frequent, to generate also as many as possible. We previously introduced a proof of concept where we used a simplified evolutionary algorithm for generating these configurations. In this paper we improve this algorithm, trying to adapt it to the specific characteristics of the fitness landscape, and also looking at finding as many solutions as possible.

关键词： Servers Security Evolutionary computation Software Browsers Cloud computing Tools

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