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IEEE International Conference on Cyborg and Bionic Systems (CBS)

作者： Yuki Inoue Yuki Kuroda Yoshiko Yabuki Yusuke Yamanoi Xu Yong Xiaobei Jing Hiroshi Yokoi Department of Mechanical and Intelligent Engineering The University of Electro-Communications Chofu Tokyo JAPAN OMRON SINIC X Corporation Bunkyo-ku Tokyo JAPAN department of Electrical Engineering Faculty of Engineering Tokyo University of Science Katushika-ku Tokyo JAPAN CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology (SIAT) Chinese Academy of Sciences (CAS) and the SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen CHINA Department of Mechanical and Intelligent Engineering Center for Neuroscience and Biomedical Engineering The University of Electro-Communications Chofu Tokyo JAPAN Mu-BORG K.K. Chofu JAPAN

ISBN: (数字)9798350388039

ISBN: (纸本)9798350388046

The prosthetic socket serves as an interface between the body and the machine. If the socket is not well-fitted to the residual limb, pain can occur. The shape of the residual limb changes over time as surgical scars stabilize or the patient’s body weight fluctuates. A socket with a cutout on the side can be tightened from the outside to adjust its circumference and accommodate these changes. However, when the circumference of the rigid socket is adjusted to fit, soft skin can become trapped due to friction between the skin and the socket. This phenomenon causes pain due to pinching. Consequently, this mechanism cannot be used for myoelectric prosthetic hands, where direct contact between the socket and the skin is necessary. In this study, we developed a socket with a variable circumference that suppresses skin pinching. We applied it to participants with different residual limb shapes. A Box and Block Test (BBT) was performed using two types of sockets. The first used a conventional socket designed to fit their residual limb shape. The second used the proposed socket, which was designed to fit the residual limb’s shape of one out of two participants and adapted to the residual limb’s changing shape. The results of the BBT showed not much difference in the number of blocks moved between the conventional socket and the proposed socket. Therefore, the performance of the proposed socket was comparable to that of conventional sockets and could be applied to different residual limbs. In other words, the proposed socket was shown to adapt to changes in the residual limb without causing pain. Sockets with the proposed functionality could be used in a variety of bio-interfaces, allowing for flexible connections between the body and machines.

关键词： Limbs Shape Pain Sockets Human-machine systems Friction Surgery Skin Interviews Prosthetic hand

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Tech-Enabled Banking Revolt:The Transformational Era of IT in the Financial Sector

Tech-Enabled Banking Revolt:The Transformational Era of IT i...

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International Conference on Image Information Processing

作者： G S Pradeep Ghantasala Anjaneyulu Kunchala Pellakuri Vidyullatha Shaik Rehana Banu Amiya Bhaumik Shaik Balkhis Banu Gaurav Gupta Department of Computer Science and Engineering Alliance University Bengaluru India Department of Computer Science and engineering line 3: nKoneru Lakshmaiah Education Foundation Vaddeswaram Guntur AP India Dept of Business Management Lincoln University College Malaysia Dept of Business Management Faculty of Busniess and Accountancy Lincoln University College Malaysia Dept of Physiotherapy Fatima College of Heaith Sciences Al Ain UAE Yogananda School of Artificial Intelligence Computers and Data science Shoolini University of Biotechnology and Management Sciences Solan HP India

ISBN: (数字)9798350371406

ISBN: (纸本)9798350371413

Information technology is been widely spread all over the world. The benefits that the IT sector provides are unmeasurable. Though there are numerous benefits there are scams going around with the software developed under IT. The growing need for IT has made IT one of the necessary systems that need to be provided in an organization to enhance productivity and progress. The developed countries are making full use of IT in all sectors. The banking sector plays a vital role in the growth of the nation’s economy working along the side of IT will only result in the enhancement of the banking sector in many perspectives. The present paper views on the impact of IT on the banking sector.

关键词： Productivity Costs Digital transformation Banking Organizations Information processing Software

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Metallic product recognition with dual attention and multi-branch residual blocks-based convolutional neural networks

Circular Economy

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Circular Economy 2022年第2期1卷

作者： Han, Honggui Zhang, Qiyu Li, Fangyu Du, Yongping Gu, Yifan Wu, Yufeng Faculty of Information Technology Beijing University of Technology Beijing100124 China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing University of Technology Beijing100124 China Engineering Research Center of Digital Community Ministry of Education Beijing University of Technology Beijing100124 China Beijing Artificial Intelligence Institute and Beijing Laboratory for Intelligent Environmental Protection Beijing100124 China College of Materials Science and Engineering Beijing University of Technology Beijing100124 China Institute of Circular Economy Beijing University of Technology Beijing100021 China

Visual recognition technologies based on deep learning have been gradually playing an important role in various resource recovery fields. However, in the field of metal resource recycling, there is still a lack of intelligent and accurate recognition of metallic products, which seriously hinders the operation of the metal resource recycling industry chain. In this article, a convolutional neural network with dual attention mechanism and multi-branch residual blocks is proposed to realize the recognition of metallic products with a high accuracy. First, a channel-spatial dual attention mechanism is introduced to enhance the model sensitivity on key features. The model can focus on key features even when extracting features of metallic products with too much confusing information. Second, a deep convolutional network with multi-branch residual blocks as the backbone while embedding a dual-attention mechanism module is designed to satisfy deeper and more effective feature extraction for metallic products with complex characteristic features. To evaluate the proposed model, a waste electrical and electronic equipment (WEEE) dataset containing 9266 images in 18 categories and a waste household metal appliance (WHMA) dataset containing 11,757 images in 23 categories are built. The experimental results show that the accuracy reaches 94.31% and 95.88% in WEEE and WHMA, respectively, achieving high accuracy and high quality recycling. © 2022 The Author(s)

关键词： Recycling

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NEURAL TOPIC MODEL VIA OPTIMAL TRANSPORT

arXiv

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arXiv 2020年

作者： Zhao, He Phung, Dinh Huynh, Viet Le, Trung Buntine, Wray Department of Data Science and Artificial Intelligence Faculty of Information Technology Monash University Australia

Recently, Neural Topic Models (NTMs) inspired by variational autoencoders have obtained increasingly research interest due to their promising results on text analysis. However, it is usually hard for existing NTMs to achieve good document representation and coherent/diverse topics at the same time. Moreover, they often degrade their performance severely on short documents. The requirement of reparameterisation could also comprise their training quality and model flexibility. To address these shortcomings, we present a new neural topic model via the theory of optimal transport (OT). Specifically, we propose to learn the topic distribution of a document by directly minimising its OT distance to the document’s word distributions. Importantly, the cost matrix of the OT distance models the weights between topics and words, which is constructed by the distances between topics and words in an embedding space. Our proposed model can be trained efficiently with a differentiable loss. Extensive experiments show that our framework significantly outperforms the state-of-the-art NTMs on discovering more coherent and diverse topics and deriving better document representations for both regular and short texts. © 2020, CC BY-NC-SA.

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Bridging the gaps in statistical models of protein alignment

arXiv

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arXiv 2020年

作者： Sumanaweera, Dinithi Allison, Lloyd Konagurthu, Arun S. Department of Data Science and Artificial Intelligence Faculty of Information Technology Monash University Australia

This work demonstrates how a complete statistical model quantifying the evolution of pairs of aligned proteins can be constructed from a time-parameterised substitution matrix and a time-parameterised 3-state alignment machine. All parameters of such a model can be inferred from any benchmark data-set of aligned protein sequences. This allows us to examine nine well-known substitution matrices on six benchmarks curated using various structural alignment methods;any matrix that does not explicitly model a "time"-dependent Markov process is converted to a corresponding base-matrix that does. In addition, a new optimal matrix is inferred for each of the six benchmarks. Using Minimum Message Length (MML) inference, all 15 matrices are compared in terms of measuring the Shannon information content of each benchmark. This has resulted in a new and clear overall best performed time-dependent Markov matrix, MMLSUM, and its associated 3-state machine, whose properties we have analysed in this work. For standard use, the MMLSUM series of (log-odds) scoring matrices derived from the above Markov matrix, are available at https://***/mmlsum. Copyright © 2020, The Authors. All rights reserved.

关键词： Markov processes

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A Multiscale Orchestrated Computational Framework to Reveal Emergent Phenomena in Neuroblastoma

SSRN

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SSRN 2023年

作者： Carlos, Borau Wertheim, K.Y. Hervas-Raluy, S. Sainz-DeMena, D. Walker, D. Chisholm, R. Richmond, P. Varella, V. Viceconti, M. Montero, A. Gregori-Puigjané, E. Mestres, J. Kasztelnik, M. García-Aznar, J.M. Mechanical Engineering Dept University of Zaragoza Zaragoza Spain Department of Computer Science Insigneo Institute for In Silico Medicine University of Sheffield Sheffield United Kingdom Department of Industrial Engineering Alma Mater Studiorum University of Bologna Italy Medical Technology Lab IRCCS Istituto Ortopedico Rizzoli Bologna Italy Baldiri Reixac 4 Barcelona Spain ACC Cyfronet AGH University of Science and Technology Kraków Poland Centre of Excellence for Data Science Artificial Intelligence and Modelling and School of Computer Science University of Hull Kingston upon Hull United Kingdom

Neuroblastoma is a complex and aggressive type of cancer that affects children. Current treatments involve a combination of surgery, chemotherapy, radiotherapy, and stem cell transplantation. However, treatment outcomes vary due to the heterogeneous nature of the disease. Computational models have been used to analyse data, simulate biological processes, and predict disease progression and treatment outcomes. While continuum cancer models capture the overall behaviour of tumors, and agent-based models represent the complex behaviour of individual cells, multiscale models represent interactions at different organisational levels, providing a more comprehensive understanding of the system. In 2018, the PRIMAGE consortium was formed to build a cloud-based decision support system for neuroblastoma, including a multi-scale model for patient-specific simulations of disease progression. This model, integrated into an online platform, will allow clinicians to optimise treatment regimens and reduce the number of costly and time-consuming clinical trials. This work outlines the challenging framework's model architecture, data workflow, hypothesis, and resources employed in its development. © 2023, The Authors. All rights reserved.

关键词： Decision support systems

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LMVD: A Large-Scale Multimodal Vlog dataset for Depression Detection in the Wild

arXiv

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arXiv 2024年

作者： He, Lang Chen, Kai Zhao, Junnan Wang, Yimeng Pei, Ercheng Chen, Haifeng Jiang, Jiewei Zhang, Shiqing Zhang, Jie Wang, Zhongmin He, Tao Tiwari, Prayag The School of Computer Science and Technology Xi’an University of Posts and Telecommunications Shaanxi Xi’an710121 China The Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Shaanxi Xi’an710121 China The Xi’an Key Laboratory of Big Data and Intelligent Computing Shaanxi Xi’an710121 China The School of Electronic Engineering Xi’an University of Posts and Telecommunications Xi’an710121 China The College of Electronic Information and Artificial Intelligence Shaanxi University of Science and Technology Xi’an710016 China The Institute of Intelligent Information Processing Taizhou University Zhejiang Taizhou318000 China The School of Education Shenzhen University Shenzhen518060 China The School of Information Technology Halmstad University Halmstad Sweden

Depression can significantly impact many aspects of an individual’s life, including their personal and social functioning, academic and work performance, and overall quality of life. Many researchers within the field of affective computing are adopting deep learning technology to explore potential patterns related to the detection of depression. However, because of subjects’ privacy protection concerns, that data in this area is still scarce, presenting a challenge for the deep discriminative models used in detecting depression. To navigate these obstacles, a large-scale multimodal vlog dataset (LMVD), for depression recognition in the wild is built. In LMVD, which has 1823 samples with 214 hours of the 1475 participants captured from four multimedia platforms (Sina Weibo, Bilibili, Tiktok, and YouTube). A novel architecture termed MDDformer to learn the non-verbal behaviors of individuals is proposed. Extensive validations are performed on the LMVD dataset, demonstrating superior performance for depression detection. We anticipate that the LMVD will contribute a valuable function to the depression detection community. The data and code will released at the link: https://***/helang818/LMVD/. © 2024, CC BY-NC-ND.

关键词： Deep learning

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Social engineering attack types and prevention techniques- A survey

Social engineering attack types and prevention techniques- A...

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Computational intelligence, Communication technology and Networking (CICTN), International Conference on

作者： Ramiz Salama Fadi Al-Turjman Shruti Bhatla Satya Prakash Yadav Department of Computer Engineering AI and Robotics Institute Research Center for AI and IoT Near East University Nicosia Turkey Artificial Intelligence Engineering Dept. AI and Robotics Institute Near East University Nicosia Turkey Research Center for AI and IoT Faculty of Engineering University of Kyrenia Kyrenia Turkey Department of Computer Science and Engineering Graphic Era Hill University Dehradun Department of Computer Science and Engineering G.L. Bajaj Institute of Technology and Management (GLBITM) Greater Noida India

The term "Cyber Security" is getting more and more popular and important over the last few years. Since computers and most of the devices are connected to the internet, they are likely to be hacked by the hackers. In the past, this issue was not a big problem, because not every device is required to be connected to the internet or the internet was not popular as today. But the case has changed over the years. All the changes in the technology area also changed the cyber-attack models as well. With the development of technology and the change of usage of the internet over the last years cyber-attacks have become more common and popular by the hackers. Hackers have discovered that they have an opportunity to steal or earn money in a short time without having to spend too much effort. These days, the type of cyber-attacks is not the same as the ones in the past. As time passes, the cyber-attack methods are also changing and evolving. Today, hackers are using more advanced and effective cyber-attack methods compared to past years. There are many methods that are impossible to cover all of them in this article. Our main focus will be on social engineering attacks in this article. Social engineering attacks use different approaches to cyber attacking. Unlike trying to explode a victim’s social media password etc. using advanced exporting programs, algorithms or techniques, social engineering attacks focus on fooling victims into providing their data to hackers by themselves without using or implementing any password cracking, exploiting techniques etc. We will go over what social media engineering is, type of social engineering methods, what countermeasures can be used to protect from social engineering and more in this article.

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A Model Transformation Approach for Converting a Trait-based Model to a Markov Chain Model

A Model Transformation Approach for Converting a Trait-based...

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Recent Advances and Innovations in engineering (ICRAIE)

作者： Nur Diana Madinah Binti Ab Hadi Azlan Ismail Norizan Mat Diah Mastura Md Saad School of IT Faculty of Engineering Built Environment & Information Technology SEGI University & Colleges Petaling Jaya Selangor Malaysia School of Computing Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA (UiTM) Shah Alam Selangor Malaysia Informatics and Mathematics Institute for Big Data Analytics and Artificial Intelligence (IBDAAI)) University Teknologi MARA (UiTM) Shah Alam Selangor Malaysia

This paper discusses the difficulty of transforming a trait-based model to a Markov Chain Model when the source model is a behavioral model. Therefore, we propose an innovative approach aimed at transforming trait-based models into Markov Chain Models. Our method hinges on the utilization of the Trait Component Ensemble Language (TCOEL) and the establishment of a unified model transformation specification at the meta-model level. Through this approach, we facilitate the seamless conversion of trait-based models into Markov Chain Models, thereby enhancing the adaptability and scope of the original models. The trait-based model presents quite challenging for transforming the behavioral traits directly into verification language. To overcome this difficulty, we analyzed the language behaviors using the fire brigade case study. Then, we used the description to identify and map the appropriate component in order to develop a CTMC model. Finally, we used PRISM model checker to undertake verification.

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Design of a Fuzzy Type-2 Controller for 1-DOF Pitch Axis Twin Rotor System

Design of a Fuzzy Type-2 Controller for 1-DOF Pitch Axis Twi...

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International Conference on Control, Automation and Diagnosis (ICCAD)

作者： Abdelrahman Sayed Sayed Walid K. Shaker Hossam Hassan Ammar Ahmad Taher Azar Chakib Ben Njima Department of Marine Technology Norwegian University of Science and Technology (NTNU) Trondheim Norway Université de Toulon Toulon France School of Engineering and Applied Science Nile University Giza Egypt Hosted by Global Academic Foundation new administrative capital School of Engineering and Computer Sciences University of Hertfordshire Egypt College of Computer and Information Sciences Prince Sultan University Riyadh Saudi Arabia Faculty of Computers and Artificial intelligence Benha University Benha Egypt University of Sousse Tunisia

This paper presents the design, manufacturing, modeling, and control of a novel 1-DOF pitch axis Twin Rotor system. An IMU sensor is used to precisely access the desired pitch angle of the system. A type-2 fuzzy controller is designed and implemented to achieve fast rise time and low overshoot, which are the desired response specifications for the system. In terms of overshoot and settling time, the performance of the type-2 fuzzy-PID controller is compared to that of the type-l fuzzy-PID controller and the conventional PID controller. The type-2 fuzzy-PID controller's performance is promising when compared to that of the other controllers, proving that it is useful for taming the Twin Rotor system's non-linearities.

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