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SSVEP-BCI in Augmented Reality in Realistic Environment

SSVEP-BCI in Augmented Reality in Realistic Environment

International Conference on Electrical engineering/electronics, computer, Telecommunications and Information technology, ECTI-CON

作者： Bhuwit Chaiyarit Setha Pan-Ngum Pasin Israsena Arpa Suwannarat Apit Hemakom Department of Computer Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Biomedical Electronics and Systems Research Team National Electronics and Computer Technology Center Pathumthani Thailand

ISBN: (数字)9798350381559

ISBN: (纸本)9798350381566

This study investigates Augmented Reality-based Steady-State Visually Evoked Potentials (AR-SSVEP) in Brain-computer Interface (BCI) systems, utilizing Extended Filter Bank Canonical Correlation Analysis (Extended-FBCCA) for SSVEP recognition optimization across various frequencies. The 10 Hz stimulus consistently achieves the highest recognition accuracy. Frequency-specific variations at 12 Hz, 13 Hz, and 15 Hz highlight nuanced SSVEP responses. White stimuli yield PC-SSVEP recognition ranging from 68.32% to 81.98%, slightly outperforming AR-SSVEP-Controlled (63.59% to 73.23%). Red stimuli impact AR-SSVEP-Controlled less than PC-SSVEP, with recognition ranges of 68.65% to 76.30% and 67.97% to 76.72%, respectively. Comparisons show a general slight outperformance of PC-SSVEP, with exceptions suggesting frequency-specific outcomes. AR-SSVEP-Controlled surpasses AR-SSVEP-Static, emphasizing the impact of a controlled visual environment. AR-SSVEP-Static recognition ranges from 33.49% to 54.59% for white stimuli and 36.15% to 53.04% for red stimuli. Subjects' movement in AR-SSVEP-Walk consistently lowers accuracy, ranging from 31.74% to 47.70% for white stimuli and 26.43% to 41.67% for red stimuli, with frequency-specific exceptions. Stimulus colors' complex effects underscore the requirement for stimulus color selections. Spatial distribution analysis reveals higher accuracy in the O-region. Overall, this study navigates the complex interaction between AR-SSVEP and environmental conditions. Future research may focus on developing algorithms for automatic configuration selection in Extended-FBCCA, ensuring adaptability to varying frequencies and real-world conditions.

关键词： Visualization Accuracy Frequency modulation Correlation Navigation Signal processing algorithms Color

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A Novel Soft Clustering Approach for Gene Expression Data

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computer Systems Science & engineering 2022年第12期43卷 871-886页

作者： E.Kavitha R.Tamilarasan Arunadevi Baladhandapani M.K.Jayanthi Kannan A Constituent College of Anna University University College of EngineeringVillupuram605103India A Constituent College of Anna University University College of EngineeringPattukkottai614701India Department of Electronics and Communication Engineering Dr.N.G.P Institute of TechnologyCoimbatore641048India Department of Computer Science Engineering Faculty of Engineering and TechnologyJAIN(Deemed to be University)Bangalore562112India

Gene expression data represents a condition matrix where each rowrepresents the gene and the column shows the condition. Micro array used todetect gene expression in lab for thousands of gene at a time. Genes encode proteins which in turn will dictate the cell function. The production of messengerRNA along with processing the same are the two main stages involved in the process of gene expression. The biological networks complexity added with thevolume of data containing imprecision and outliers increases the challenges indealing with them. Clustering methods are hence essential to identify the patternspresent in massive gene data. Many techniques involve hierarchical, partitioning,grid based, density based, model based and soft clustering approaches for dealingwith the gene expression data. Understanding the gene regulation and other usefulinformation from this data can be possible only through effective clustering algorithms. Though many methods are discussed in the literature, we concentrate onproviding a soft clustering approach for analyzing the gene expression data. Thepopulation elements are grouped based on the fuzziness principle and a degree ofmembership is assigned to all the elements. An improved Fuzzy clustering byLocal Approximation of Memberships (FLAME) is proposed in this workwhich overcomes the limitations of the other approaches while dealing with thenon-linear relationships and provide better segregation of biological functions.

关键词： Reinforcement membership centroid threshold statistics bioinformatics gene expression data

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Global scale solar energy harnessing: An advanced intra-hourly diffuse solar irradiance predicting framework for solar energy projects

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Neural Computing and Applications 2024年第18期36卷 10585-10598页

作者： El-kenawy, El-Sayed M. Bailek, Nadjem Bouchouicha, Kada Zerouali, Bilel Hassan, Muhammed A. Kuriqi, Alban Jamil, Basharat Colak, Ilhami Khalil, Adel Ibrahim, Abdelhameed Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Mansoura35111 Egypt Laboratory of Mathematics Modeling and Applications Department of Mathematics and Computer Science Faculty of Sciences and Technology Ahmed Draia University of Adrar Adrar01000 Algeria Energies and Materials Research Laboratory Faculty of Sciences and Technology University of Tamanghasset Tamanrasset10034 Algeria MEU Research Unit Middle East University Amman Jordan Adrar01000 Algeria Vegetal Chemistry-Water-Energy Laboratory Faculty of Civil Engineering and Architecture Department of Hydraulic Hassiba Benbouali University of Chlef Ouled Fares Chlef02180 Algeria Mechanical Power Engineering Department Faculty of Engineering Cairo University Giza12613 Egypt School of Architecture University of Waterloo 7 Melville St S CambridgeONN1S 2H4 Canada CERIS Instituto Superior Tecnico Universidade de Lisboa Lisbon Portugal Civil Engineering Department University for Business and Technology PristinaKosovo10000 High Temperature Processes Unit IMDEA Energy Institute Av. Ramón de La Sagra 3 Móstoles Madrid28935 Spain Faculty of Engineering and Architectures Nisantasi University Istanbul Turkey Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura35516 Egypt

Diffuse horizontal irradiance (DHI) forecasts are critical for adopting solar photovoltaic technology. Yet, they can lack reliability given the limited and uncertain meteorological data available for desert areas. This research develops a new sine cosine dipper throated optimization (SCDTO) technique, targeting DHI prediction even given such data constraints. SCDTO uniquely hybridizes sine cosine metaheuristics, adept at exploration, with dipper throat optimization, providing focused exploitation. This hybridization aims to create a robust ensemble model capable of delivering reliable DHI predictions despite climatic uncertainty. The ensemble model, employing various input combinations, was rigorously evaluated across multiple meteorological stations. The SCDTO algorithm exhibited remarkable performance improvements, yielding substantial reductions exceeding 93% in root mean squared error and 98% in mean absolute error at key stations in Morocco, including Tan-Tan, Zagora, Erfoud, and Oujda. Comparative analyses against established optimization algorithms consistently underscored the superior predictive capabilities of SCDTO. Visualizations, including box plots and histograms, demonstrated SCDTO’s efficacy in minimizing prediction errors, particularly for Tan-Tan, Zagora, and Erfoud stations. Also, statistical validation through one-way analysis of variance (ANOVA) further affirmed the significance of the proposed SCDTO method. Therefore, this hybrid metaheuristic optimization enables more accurate DHI predictions from limited meteorological data. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Solar energy

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Data Completeness-aware Transmission Control for Large Spatio-Temporal Data Retention

Data Completeness-aware Transmission Control for Large Spati...

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2022 IEEE International Conference on Consumer electronics, ICCE 2022

作者： Kaneyasu, Hotaka Nobayashi, Daiki Tsukamoto, Kazuya Ikenaga, Takeshi Lee, Myung Graduate School of Engineering Kyushu Institute of Technology Fukuoka Japan Kyushu Institute of Technology Faculty of Engineering Department of Electrical and Electronics Engineering Fukuoka Japan Kyushu Institute of Technology Faculty of Computer Science and Systems Engineering Department of Computer Science and Networks Fukuoka Japan City College of New York Department of Electrical and Computer Engineering New York United States

ISBN: (纸本)9781665441544

With the development of IoT technology, various kinds of data are generated by IoT devices. Some of this data contains information on geographical location and time. We refer to such data as spatio-temporal data (STD). Since the 'local production and consumption' of STD is effective for location-dependent applications, we have proposed an STD retention system that utilizes vehicles as data sources. STD sources ranges from simple sensory data to large video data. However, since previous methods assumed to retain an STD consisting of only one packet, retention of large STD sources may suffer from frequent packet collisions due to the increase in the number of packet transmissions. In this paper, we propose a data completeness-aware transmission control mechanism for large STD retention. Our simulation results showed that the proposed scheme reduces channel collision by suppressing the forwarding of incomplete data, and achieved a nearly 100% coverage rate. © 2022 IEEE.

关键词： Internet of things

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Effectiveness of Brief Mindfulness-based Intervention among Students with High Neuroticism based on Peripheral Physiological Data: A Preliminary Study 5

Effectiveness of Brief Mindfulness-based Intervention among ...

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5th IEEE International Symposium in Robotics and Manufacturing Automation, ROMA 2022

作者： Nik Rashidi, Nik Amalia Nadirah Binti Izhar, Lila Iznita Sebastian, Patrick Elamvazuthi, Irraivan Al Idris, Syahril Anuar Universiti Teknologi Petronas Electrical and Electronics Engineering Perak Malaysia University Malaysia of Computer Science and Engineering Faculty of Engineering and Frontier Technology Selangor Cyberjaya Malaysia

ISBN: (数字)9781665459327

ISBN: (纸本)9781665459327

Stress is a major problem among university students due to the circumstances from internal as well as external such as relationship problems, low self-confidence, and academic pressure. We administered self-report questionnaires and acquired peripheral physiological signals to observe the effectiveness of a brief mindfulness-based intervention (MI) in improving relaxation and thus reducing stress. It was found that skin conductance (SC) showed significant change with p=0.0016 after MI unlike blood volume pulse (BVP) and respiratory rate (RR), even though both were found to be slightly better than that before MI during the resting states and Stroop Task. SC can thus be a potential indicator for the effectiveness of MI in helping the student subjects to cope with stress better and to improve their relaxation and attention levels. © 2022 IEEE.

关键词： Students

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Identification of Magnetorheological Damper Model for Off-Road Vehicle Suspension 21st

Identification of Magnetorheological Damper Model for Off-Ro...

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21st Polish Control Conference, PCC 2023

作者： Krauze, Piotr Placzek, Marek Zmudka, Zbigniew Bauke, Dawid Olszowka, Przemyslaw Turek, Jakub Wycislok, Artur Ziaja, Maciej Zosgornik, Szymon Janusz, Wojciech Przybyla, Grzegorz Wychowanski, Michal Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Akademicka 16 Gliwice44-100 Poland Silesian University of Technology Faculty of Mechanical Engineering Konarskiego 18A Gliwice44-100 Poland Silesian University of Technology Faculty of Energy and Environmental Engineering Konarskiego 18 Gliwice44-100 Poland Engineering Office Ozarow27-530 Poland Gliwice Poland

ISBN: (纸本)9783031351693

The article presents results of experimental identification of MR (magnetorheological) damper model for an off-road vehicle. Original shock-absorbers of the vehicle were replaced by suspension MR dampers supplied by a dedicated measurement and control system. The vehicle includes several sensors which allow to observe electric currents controlling MR dampers, forces generated in the front vehicle suspension columns and other sensors which measure deflection of these suspension parts. The front part of the semi-active suspension was tested using laboratory setup with vibration mechanical exciters generating sinusoidally variable excitation at frequency equal to 12 Hz. MR dampers were directly controlled by peripheral electronic units generating different constant currents equal to 0, 0.11 and 0.37 A. As a result, evaluated force-velocity characteristics and analysis of MR damper behaviour in the target vehicle were carried out. Further steps of analysis included mathematical description of the selected MR damper using several types of MR damper models, i.e.: Bingham and hyperbolic tangent function models as well as their variants including first-order output dynamics. It was shown that the dynamic model based on hyperbolic tangent function offers the best fitness to the response of the actual MR damper with respect to the mean-squared error. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Off road vehicles

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Motion Detection System for Recognition of Early Sign of Depression 6

Motion Detection System for Recognition of Early Sign of Dep...

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6th IEEE International Conference on Recent Advances and Innovations in engineering, ICRAIE 2021

作者： Aliza Ya'Kob, Nor Aina Mohamed Farook, Rohani S Abdul Halim, Aznor Hanah Muhammad Fadzil, Mohd Fairuz Abdul Rejab, Mohamad Rizal Elias, Shamsul Jamel Universiti Malaysia Perlis Faculty of Electronics Engineering Technology Perlis Malaysia Universiti Teknologi MARA Campus Faculty of Computer and Mathematical Sciences Kedah Malaysia

ISBN: (纸本)9781665434027

Depression is one of the mental health disorders that affect many humans, especially campus students. In certain cases, people with depression-prone to commit suicide without any warning signs and symptoms observed by family and friends. There is a need to be able to identify and proceed for treatment from the professionals as soon as possible. There is a lack of tools to identify students' depression behavior through quantified motion characteristics. The advancement of algorithms could be used in detecting such behaviors. This research is motivated to classify depression among students using artificial intelligence. The motion characteristics are quantified using accelerometer and GPS data and trained using neural networks to enable human activity prediction. Once predicted the prone to depression behavior notification will be sent to alert the user on their mental health condition. The user should react and respond to the alert and meet their doctors for further treatment. © 2021 IEEE.

关键词： Students

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A Gradient Boosting Algorithm to Predict Energy Consumption for Home Applications 2

A Gradient Boosting Algorithm to Predict Energy Consumption ...

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2nd International Conference on computer, Communication and Control, IC4 2024

作者： Sivakumar, V.G. Arunfred, N. Anusha, N. Balakrishnan, C. Meenakshi, B. Sujatha, S. Vidya Jyothi Institute of Technology Department of Electronics and Communication Engineering Telangana Hyderabad India Srm Institute of Science and Technology Faculty of Management Studies Kattankulathur Chengalpattu Tamil Nadu Chennai India Vellore Institute of Technology School School of Computer Science and Engineering Department of IoT Tamil Nadu Vellore India S.A.Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Sri Sairam Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Biomedical Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350387933

Energy-efficient solutions are in high demand in today's fast-developing technological environment, necessitating the use of sophisticated predictive modeling methods. Conventional forecasting systems have problems given the particular aspects related to home demand for energy. As a consequence, new strategies are constantly being created for more accurately foreseeing future occurrences. Weather, user habits, and advancements in technology interfere with precise forecasts even more. This study provides a novel application of the Gradient Boosting approach to solve such obstacles and enhance energy use prediction for residential applications. Through utilising the electrical energy of Extreme Gradient Boosting (XGBoost) and Light Gradient Boosting Machine (LightGBM), the suggested method takes into account prior use patterns, appliance-specific data, and external factors like as climate. The model's response to changes in the actual world provides exact estimates, providing homeowners with the information they require to make energy-saving decisions. This method also investigates the comprehending of Gradient Boosting models, showing key characteristics that affect energy usage patterns. Stakeholders focus heavily on interpretability to make informed decisions with regard to ways to save energy and resource allocation. © 2024 IEEE.

关键词： Machine learning

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Suppression of Conducted Emissions in Three-Phase Adjustable Drive Systems 14

Suppression of Conducted Emissions in Three-Phase Adjustable...

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14th International Conference on Electrical and electronics engineering, ELECO 2023

作者： Genc, Secil Sarma, Nur Gundogdu, Burcu Ozgonenel, Okan Gezegin, Cenk Terzi, Umit Kemalettin Ondokuz Mayis University Electrical Electronics Engineering Department Samsun Turkey Duzce University Electrical Electronics Engineering Department Duzce Turkey Durham University Department of Engineering Durham United Kingdom Hakkari University Colemerik Vhs Computer Technologies Hakkari Turkey Marmara University Faculty of Technology Department of Electrical and Electronics Engineering Istanbul Turkey

ISBN: (纸本)9798350360493

The fundamental issue with high switching power converters is electromagnetic interference. The converter design must be electromagnetically compliant for an operation to be secure. Filters play a crucial role in mitigating electromagnetic interference (EMI) within three-phase systems. This paper presents examining the electromagnetic interference associated with a three-phase inverter interconnected to the grid. The reported measurements were taken after the filter and applied with three-phase adjustable drive system for 9-150kHz frequency ranges. Therefore, experimental evidence supports the EMI filter's noise attenuation. In conclusion, the presented study fills in the gaps measuring uncertainties for three-phase emissions, assisting engineers in the design of three-phase converters. © 2023 IEEE.

关键词： Signal interference

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A New, Reconfigurable Circuit Offering Functionality of AND and OR Logic Gates for Use in Algorithms Implemented in Hardware 33

A New, Reconfigurable Circuit Offering Functionality of AND ...

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33rd IEEE International Conference on Microelectronics, MIEL 2023

作者： Talaska, Tomasz Dlugosz, Rafal Nikolic, Tatjana Nikolic, Goran Stefanski, Tomasz Dlugosz, Michal Talaska, Michal Bydgoszcz University of Science and Technology Faculty of Telecommunication Computer Science and Electrical Engineering Bydgoszcz85-796 Poland Aptiv Services Poland Kraków30-399 Poland University of Niš Faculty of Electronic Engineering Niš18000 Serbia Gdanśk Univeristy of Technology Faculty of Electronics Telecommunications and Informatics Gdanśk80-233 Poland Poznan University of Technology Faculty of Control Robotics and Electrical Engineering Poznan60-965 Poland Complex of Electronics Schools Bydgoszcz85-092 Poland

ISBN: (纸本)9798350347760

The paper presents a programmable (using a 1-bit signal) digital gate that can operate in one of two OR or AND modes. A circuit of this type can also be implemented using conventional logic gates. However, in the case of the proposed circuit, compared to conventional solutions, the advantage is a much smaller number of transistors necessary for its implementation. Circuit is also much faster than its conventional counterpart. The logic gate was implemented in the 180nm CMOS technology and verified using Hspice simulations. There are many possible applications for this gate, mostly in artificial intelligence and pattern recognition algorithms implemented at the transistor level. © 2023 IEEE.

关键词： Logic gates

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