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IEEE International Conference on Civil Aviation Safety and Information Technology (ICCASIT)

作者： Keqin Li Jiajing Chen Dezhi Yu Tao Dajun Xinyu Qiu Jieting Lian Ryan Ji Shengyuan Zhang Zhenyu Wan Baiwei Sun Bo Hong Fanghao Ni Jiaqi Han Department of Computer Science AMA University Quezon Philippines Courant Institute New York University 251 Mercer St New York NY USA School of Information University of California Berkeley University Avenue and Oxford St Berkeley CA United States Master of Science in Mechanical Engineering School of Engineering Carnegie Mellon University 5000 Forbes Avenue Pittsburgh PA USA College of Engineering Northeastern University Seattle USA Master of Science in Database Technology School of Professional Studies New York University 50 West 4th Street New York NY USA College of Engineering Cornell University 616 Thurston Ave Ithaca NY US Master of Professional Science in Applied Statistics-Data Science College of Computing and Information Science Cornell University 616 Thurston Ave Ithaca NY USA Independent Researcher Beijing China Master of Computer Science Donald Bren School of Information and Computer Sciences University of California Irvine 510 Aldrich Hall Irvine CA USA School of Informatics Computing and Cyber Systems Northern Arizona University Flagstaff AZ USA Shanghai Institute of Technology Shanghai China

ISBN: (数字)9798350389418

ISBN: (纸本)9798350389425

This paper proposes a deep reinforcement learning based on the warehouse environment, the mobile robot obstacle avoidance Algorithm. Firstly, the value function network is improved based on the pedestrian interaction. We can learn to obtain the relative importance of the current state and the historical trajectory state as well as the joint impact on the robot’s obstacle avoidance strategy. Secondly, the reward function of reinforcement learning is designed based on the spatial behaviour of pedestrians, and the robot is punished for the state where the angle changes too much, so as to achieve the requirement of comfortable obstacle avoidance. Finally, the feasibility and effectiveness of the deep reinforcement learning-based mobile robot obstacle avoidance algorithm in the warehouse environment in the complex environment of the warehouse are verified through simulation experiments.

关键词： Legged locomotion Pedestrians Heuristic algorithms Robot sensing systems Feature extraction Trajectory Safety Data mining Collision avoidance Information technology

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The Effect of Music and Light-Color as a Machine Empathic Response on Stress in Occupational Health

The Effect of Music and Light-Color as a Machine Empathic Re...

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： André s Felipe Dorado Karl Daher Elena Mugellini Denis Lalanne Omar Abou Khaled Master in Computer Science BeNeFri program University of Bern Switzerland University of Applied Sciences of Western Switzerland Fribourg Switzerland Human-IST University of Fribourg Fribourg Switzerland

In a world where technological advancements are progressing at a vertiginous pace, social networks, online games, virtual worlds, streaming services, and remote work are part of everyday life. This is the case for the work environment, with the use of technological tools and home offices. In contrast, harmful aspects have been amplified, such as stress that affects occupational health. Lately, considerable interest has been gained in the affective domain in improving the occupational situation using empathic responses. In this work, we study the effect of machine empathic responses such as blue light, relaxing music, and the combination of light and music on people performing stressful tasks in an occupational environment. Thirty five participants tested different stimuli, eleven tested the music condition, twelve the light effect, and another twelve the combination of light and music. The monitoring of the heart rate variability along with psychological measures show that empathic responses can help reduce humans stress levels.

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Robustface Recognition by Fusing Fuzzy Type 2 Induced Multiple Facial Fused Image 4

Robustface Recognition by Fusing Fuzzy Type 2 Induced Multip...

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4th IEEE International Conference on Computing, Power and Communication Technologies, GUCON 2021

作者： Ghosh, Manas Dey, Aniruddha Shaw, Rabindra Nath Ghosh, Ankush RCCIIT Department of Master of Computer Application Kolkata India MAKAUT Department of Information Technology Kolkata India Galgotias University Department of EC and Communication Engineering India School of Engineering and Applied Science Neotia University Kolkata India

ISBN: (纸本)9781728199511

This paper projects a new decision making model for face recognition from the original image fused with their true and partial diagonal images by integrating the type-2 fuzzy set based approach to mitigate the factors that pretend the face recognition accuracy. The G2DFLD based feature vectors corresponding to a test image are given input to neural network based classifier trained with the feature vectors of the fused images to generate the merit weights with respect to different classes (subjects) under consideration. A new scheme has been introduced in the present approach to generate a score by employing a fuzzy type-2 set based treatment. These scores with respect to each of the classes under consideration are rendered from the feature vectors of the test image and those of the diagonally fused training samples. For each class, the score is fused weighted by the corresponding merit weights to generate the concluding score. These class-wise concluding scores are deliberated in recognizing the test face image. Faces from the well-known databases (gallery) with varied pose, illumination and occlusion are used to evaluate the performance of the model. It has been found that our model exhibits more accurate classification performance than existing similar kind of image level fusion method. © 2021 IEEE.

关键词： Face recognition

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Graph Convolutional Networks for Improved Motor Imagery Recognition in Brain-computer Interfaces 1st

Graph Convolutional Networks for Improved Motor Imagery Reco...

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1st International Conference on Advanced Network Technologies and Computational Intelligence, ICANTCI 2024

作者： Raina, Vikas Maaliw Iii, Renato R. Arislanbekovna, Kurbaniyazova Malohat Keshta, Ismail Byeon, Haewon Kaushal, Chetna CSE SET Mody University of Science and Technology NH-52 Lakshmangarh Rajasthan Sikar India College of Engineering Southern Luzon State University Quezon Lucban Philippines Master of Urganch State University Urgench Uzbekistan Computer Science and Information Systems Department College of Applied Sciences AlMaarefa University Riyadh Saudi Arabia Department of Digital Anti-Aging Healthcare Inje University Gimhae Korea Republic of Institute of Engineering and Technology Chitkara University Chitkara University Punjab India

ISBN: (纸本)9783031860683

An important field of research in brain-computer interfaces is motor imagery recognition, which translates neural activity inputs from the brain into encoding outputs for intention control. The applications of deep learning algorithm have increased the precision of motor imagery recognition in recent years. Nevertheless, multi-channel electroencephalogram (EEG) inputs are typically treated as two-dimensional matrix signals in deep learning-based motor imagery analysis, which ignores spatial correlation information between distinct nodes. In order to overcome this problem, graph convolutional networks are used for node feature aggregation in motor imagery analysis, wherein spectral domain properties can be learned. Ultimately, fully connected layers are used to produce the categorization results. This approach learns temporal, frequency, and spectral domain information effectively, outperforming other methods with an accuracy of 80.9% and a kappa coefficient of 0.7 on Dataset 2a of BCI Competition IV. It offers a fresh viewpoint and method for BCI motor imagery recognition. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

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Chimney Height, a Determining Factor in the Dispersion of Pollutants and Their Concentration

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World Journal of Engineering and Technology 2021年第1期9卷 173-193页

作者： Neyva Maria Lopes Romeiro Eliandro Rodrigues Cirilo Paulo Laerte Natti Letícia Mayumi Doy Okamoto Tainá Julianotti Department of Mathematics State University of Londrina and Member of the Simulation and Numerical Analysis Laboratory—LabSan Paraná Brazil Graduated in Computer Science State University of Londrina Paraná Brazil Master’s Student Applied and Computational Mathematics—PGMAC State University of Londrina Paraná Brazil

This work proposes a way of modelling two-dimensional complex meshes using elliptic equations, which the computational grid coincides with the problem geometry, making computational processing more suitable. A multiblock technique was used in order to achieve a better representation of the problem domain. In this way, numerical simulations of the movement and dispersion of pollutant emissions in the atmosphere are presented in the generated domains, using the Navier-Stokes pollutant transport equations. The curvilinear coordinates and the finite difference method are used for the discretization. The model was verified in two tests. In the first test, three cases were proposed, with geometries containing a chimney followed by an obstacle, using different chimney heights, and the obstacle height was fixed. The test aims to verify the vortices appearance, in the blocks, to obtain agreement with as presented in the literature. In the second test, the geometry is described by a chimney and an obstacle that represents one of the mountains in the valley. The performed tests made possible to verify that the height of the chimney can be considered a determining factor to describe the dispersion of pollutants, as well as their concentration in the proximity of industrial areas.

关键词： Atmosphere Valley Multiblock Navier-Stokes Transport Equation

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How to design the biofeedback training for the rehabilitation of PTSD patients?

How to design the biofeedback training for the rehabilitatio...

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2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive science, Genomics and Biomedicine, CSGB 2023

作者： Bazanova, Olga Zakharov, Alexander Larkova, Irina Maryanovskaya, Tatiana Melnikov, Andrey Ermolaeva, Sargylana Nikolenko, Ekaterina Shirolapov, Igor The Research Institute of Molecular Biology and Biophysics Laboratory of Computer Systems of Biofeedback Dolgoprudny Russia The Moscow Institute of Physics and Technology Educational and Scientific Center for Humanities and Social Science Novosibirsk Russia Research Institute of Neurosciences Samara State Medical University Samara Russia Lugansk Republican Center for Emergency Medical Care and Disaster Medicine Laboratory of Psychophysiological Support Lugansk Russia Novosibirsk National Research State University Mechanic-Mathematic Department Novosibirsk Russia The Russian University of Sport «gtsolifk» Department of Physiology Moscow Russia The Moscow Institute of Physics and Technology Master's Degree in Applied Data Analysis in the Medical Field Dolgoprudny Russia Federal State Budgetary Scientific Institution Scientific Research Institute of Neurosciences and Medicine Department of Clinical Neuroscience Behavior and Neurotechnology Novosibirsk Russia

ISBN: (纸本)9798350307979

Rationale for this review is the pressing medical and social problem of the posttraumatic stress disorder (PTSD) treatment. It is known that biofeedback technology is one of the most effective methods of treatment and rehabilitation for emotional profile disorders. In order to develop biofeedback aimed to PTSD rehabilitation, we conducted a literature search on this problem. However, it appears that at the moment there is not enough unambiguous data on this type of biofeedback design. The pathogenesis of PTSD is closely related to impaired efficiency of sensorimotor integration (SMI). The effectiveness of therapy for psychosomatic disorders in patients with PTSD can be increased by restoring normal sensorimotor integration. The review examines various autonomic, electrophysiological and postural markers of destroyed sensorimotor integration (SMI) in individuals with PTSD. We have found that the most informative indicators of SMI in norm include: an increase in EEG power in the individually determined high-frequency alpha subrange, a decrease in the speed of body sway and energy demands to maintain a vertical posture, and a decrease in EMG activity of muscles not involved in cognitive or psychomotor performance. We intend to use these indicators in diagnostic purposes and to develop neurofeedback technology for SMI recovery in patients with PTSD. © 2023 IEEE.

关键词： Electroencephalography

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Empathic Flower Companion to Increase Productivity- EFC

Empathic Flower Companion to Increase Productivity- EFC

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Karl Daher Zeno Bardelli Matteo Badaracco Elena Mugellini Denis Lalanne Omar Abou Khaled HumanTech institute University of Applied Sciences and Arts of Western Switzerland Fribourg Swiss Joint Master of Science in Computer Science University of Fribourg Fribourg Switzerland

ISBN: (数字)9781728159539

ISBN: (纸本)9781728159546

Humans nowadays are tending to spend too much time in front of their screens. Direct interaction between humans is falling in numbers and people are losing their empathic behaviour. By integrating empathy and emotions in everyday objects researchers can address this problem. In addition we can have a positive effect on our lives, from physical and mental health through tackling many issues, like productivity, time wasting, stress and other problems. In this article, we tackle the productivity problem by presenting the Empathic Flower Companion (EFC) that will be using the expression of emotions to help the human through their working day. It will be monitoring their time and at the same time analysing the websites they will be surfing. The concept proposed will reduce the time wasted on unproductive websites. The results show an increase of 15% in the productivity of the testers, which shows that EFC was effective in reducing the amount of time wasted.

关键词： Productivity Monitoring Faces Chatbot Media Information technology Shape

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Location embedding based pairwise distance learning for fine-grained diagnosis of urinary stones

arXiv

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arXiv 2024年

作者： Jin, Qiangguo Huang, Jiapeng Sun, Changming Cui, Hui Xuan, Ping Su, Ran Wei, Leyi Wu, Yu-Jie Wu, Chia-An Duh, Henry B.L. Lu, Yueh-Hsun School of Software Northwestern Polytechnical University Shaanxi China Yangtze River Delta Research Institute of NPU Suzhou China CSIRO Data61 Sydney Australia Department of Computer Science and Information Technology La Trobe University Melbourne Australia School of Engineering Shantou University Guangdong China College of Intelligence and Computing Tianjin University Tianjin China School of Information Xiamen University Xiamen China AIDD Faculty of Applied Science Macao Polytechnic University China Department of Radiology Shuang-Ho Hospital Taipei Medical University Taipei Taiwan Master of Public Health Program National Yang Ming Chiao Tung University Taipei Taiwan School of Design The Hong Kong Polytechnic University Hong Kong Department of Radiology School of Medicine College of Medicine Taipei Medical University Taipei Taiwan

The precise diagnosis of urinary stones is crucial for devising effective treatment strategies. The diagnostic process, however, is often complicated by the low contrast between stones and surrounding tissues, as well as the variability in stone locations across different patients. To address this issue, we propose a novel location embedding based pairwise distance learning network (LEPD-Net) that leverages low-dose abdominal X-ray imaging combined with location information for the fine-grained diagnosis of urinary stones. LEPD-Net enhances the representation of stone-related features through context-aware region enhancement, incorporates critical location knowledge via stone location embedding, and achieves recognition of fine-grained objects with our innovative fine-grained pairwise distance learning. Additionally, we have established an in-house dataset on urinary tract stones to demonstrate the effectiveness of our proposed approach. Comprehensive experiments conducted on this dataset reveal that our framework significantly surpasses existing state-of-the-art methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Embeddings

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How to design the biofeedback training for the rehabilitation of PTSD patients?

How to design the biofeedback training for the rehabilitatio...

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Cognitive sciences, Genomics and Bioinformatics (CSGB)

作者： Olga Bazanova Alexander Zakharov Irina Larkova Tatiana Maryanovskaya Andrey Melnikov Sargylana Ermolaeva Ekaterina Nikolenko Igor Shirolapov Laboratory of Computer systems of Biofeedback The Research Institute of Molecular Biology and Biophysics Dolgoprudny Russia Educational and Scientific Center for Humanities and Social Science The Moscow Institute of Physics and Technology Novosibirsk Russia Research Institute of Neurosciences Samara State Medical University Samara Russia Laboratory of psychophysiological support Lugansk Republican Center for Emergency Medical Care and Disaster Medicine Lugansk Russia Mechanic-Mathematic Department Novosibirsk National Research State University Novosibirsk Russia Department of Physiology The Russian University of Sport «GTSOLIFK» Moscow Russia Master's Degree in Applied Data Analysis in the Medical Field The Moscow Institute of Physics and Technology Dolgoprudny Russia Department of Clinical Neuroscience Behavior and Neurotechnology Federal State Budgetary Scientific Institution “Scientific Research Institute of Neurosciences and Medicine” Novosibirsk Russia

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Efficient authenticated key establishment protocol for telecare medicine information systems

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AIP Conference Proceedings 2022年第1期2519卷

作者： Mahalakshmi R. Lokesh Kumar K. S. Ranjini S. Sindhu R. Udhayakumar 1Department of Mathematics School of Applied Sciences REVA University Bangalore Karnataka India 2Department of Analytics School of Computer Science and EngineeringVellore Institute of Technology Vellore -632014 Tamilnadu India 3Department of Computer Applications Dayanand Sagar college of Arts Science and Commerce Bangalore Karnataka India 4Department of Master of Computer Applications Cambridge Institute of Technology(VTU) Bengaluru India 5Department of Mathematics School of Advanced Sciences Vellore Institute of Technology Vellore -632014 Tamilnadu India

Secure checked based three person affirmation plot for records trade telecare remedy facts structures permits two customers simply store their verifiers prepared from their certifiable thriller state in approval verifiers informational index. By then the confirmation professional can test the clients’ verifiers and help them to exchange electronic medical records or electronic prosperity statistics securely and favorably. In this work, we must suggested protocol based on SPSD.

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