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3rd International Conference on Advances in Information and Communication technology, ICTA 2024

作者： Duong, Ngoc-Son Nguyen, Thu-Trang Vu-Thi, Lan-Nhi Lam, Sinh-Cong Dinh-Thi, Thai-Mai Department of Telecommunications Systems Faculty of Electronics and Telecommunications VNU University of Engineering and Technology Hanoi Viet Nam

ISBN: (纸本)9783031809422

In this paper, we tackle the problem of multiple-input multiple-output (MIMO) mmWave channel estimation in a hybrid analog digital architecture by exploiting the structure of the mmWave channel and the physical constraints of paths therein. We accomplish this by applying a novel Orthogonal Matching Pursuit (OMP) algorithm to the beamspace channel. The proposed OMP method leverages two properties of beamspace channel, which are i) relatively sparse structure, and ii) uniqueness of angle values of each path. Simulation results show that our proposed OMP method outperforms standard OMP in terms of probability of successful recovery and mean square error. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Mean square error

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Analysis of the performance of robotic assembly systems considering the usage of tools or jigs for the task-board task in the WRS 2018

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Advanced Robotics 2023年第20期37卷 1329-1346页

作者： Dobashi, Hiroki Ogawa, Koki Shibata, Mizuho Uemura, Wataru Yokokohji, Yasuyoshi Faculty of Systems Engineering Wakayama University Wakayama Japan Graduate School of Systems Engineering Wakayama University Wakayama Japan Department of Robotics Faculty of Engineering Kindai University Higashi-Hiroshima Japan Electronics Information and Communication Engineering Course Faculty of Advanced Science and Technology Ryukoku University Otsu Japan Department of Mechanical Engineering Graduate School of Engineering Kobe University Kobe Japan

A task-board task is a task in which robots perform a set of fundamental assembly operations related to the assembly of a specific product such as inserting a part into another part, tightening bolts and nuts, attaching flexible parts, etc. In the task-board task competition in the industrial robotics category of the World Robot Summit (WRS) 2018, 15 teams from around the world performed the task. In our previous work, we observed recorded videos of the competition frame by frame and manually investigated the performance of robotic systems of the top four teams, focusing only on whether robots contact target parts. In this paper, we introduce frame sets to represent mainly contact states between robots, tools, or jigs and target parts to be handled for such a frame-by-frame analysis of the recorded videos, and based on the frame sets, we analyze the performance of robotic assembly systems of other teams as well as the top four teams in the task-board task competition in the WRS 2018, considering the usage of tools or jigs. © 2023 Informa UK Limited, trading as Taylor & Francis Group and The Robotics Society of Japan.

关键词： Robotic assembly

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CSV Alliance Model of SMEs Considering Local Clusters in Japan 1

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8th Asia Conference on Environment and Sustainable Development, ACESD 2023

作者： Shirasawa, Naoto Seo, Yuna Department of Industrial and Systems Engineering Faculty of Science and Technology Tokyo University of Science Noda Japan

ISBN: (数字)9789819733200

ISBN: (纸本)9789819733194

In recent years, Creating Shared Value (CSV), a management strategy based on the concept of creating both economic and social value for a company, has been attracting attention, and companies are trying to put it into practice. In Japan, one of the CSV approaches is also developing clusters, which in some cases create both value for companies. However, there are only a few empirical studies about CSV alliances in local industrial clusters in the context of inter-organizational networks. Especially in Japan, where SMEs comprise the majority of the supply chain, it is important for SMEs to seek and expand CSV alliances with other companies and organizations within the cluster. This study aims to propose CSV alliance models of SMEs among local clusters in Japan by using structural equation modeling. Then we target SMEs in local industrial clusters and construct the CSV alliance with regard to intra- and inter- organizational alliance management and local resources. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Supply chains

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Simulation of Discovering Market Opportunities Using AI Methods 25

Simulation of Discovering Market Opportunities Using AI Meth...

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25th European Conference on Knowledge Management, ECKM 2024

作者： Trzcielinski, Stefan Pawlowski, Grzegorz Department od Management Systems Faculty of Engineering Management Poznan University of Technology Poznan Poland

ISBN: (纸本)9781917204101

Due to the strong turbulence that exists in the business environment, the view is sometimes articulated that the time horizon of decisions is no longer a hallmark of strategic management. Opposing views argue that a turbulent environment changes the trajectory of reaching future objectives determined by strategic decisions. Such trajectories require the company to be agile, which is manifested by seizing opportunities. Opportunities arise because the environment is volatile. An example of market opportunity is the unsatisfied demand for products. Buyers are driven by different motives when choosing between products that are alternative to them. From the producer's point of view, the purchase is therefore random. As a consequence, the alignment of the offered product portfolio with the actual purchasing decisions of customers is undetermined. In this article, we address the problem of determining the product portfolio structure expected by customers, i.e. one that is consistent with their future purchasing decisions. We hypothesise that this problem can be represented by a model of flows between alternative resources. Problems of this type are solved using Markov Chain Monte Carlo (MCMC) methods. In order to discover the expected demand (opportunity), we simulated the flow model we developed using the Metropolis-Hastings algorithm, which is a special case of the MCMC method used in AI. Due to operating on numerical data, such simulations fall under quantitative research. In the article, we present a model of customer flows between alternative products and then the simulation result, which is the expected value of these flows (stationary point). We convert this value into the structure of the product portfolio using a model of customer purchasing decisions that we have developed. The obtained results confirm the effectiveness of our method and have significant practical value, especially for SMEs. It also enables the assessment of the company's product strategy based

关键词： Markov chains

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Understanding the Thermal Impedance of Silicone Rubber/Hexagonal Boron Nitride Composites as Thermal Interface Materials

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Chinese Journal of Polymer Science 2024年第3期42卷 352-363,I0008页

作者： Yuan Ji Shi-Da Han Hong Wu Shao-Yun Guo Feng-Shun Zhang Jian-Hui Qiu The State Key Laboratory of Polymer Materials Engineering Sichuan Provincial Engineering Laboratory of Plastic/Rubber Complex Processing TechnologyPolymer Research InstituteSichuan UniversityChengdu 610065China Institute of Chemical Materials China Academy of Engineering PhysicsMianyang 621900China Department of Mechanical Engineering Faculty of Systems Science and TechnologyAkita Prefectural UniversityAkita 015-0055Japan

Silicone rubber(SR) composites are most widely used as thermal interface materials(TIMs) for electronics heat dissipation. Thermal impedance as the main bottleneck limiting the performance of TIMs is usually neglected. Herein, the thermal impedance of SR composites loaded with different levels of hexagonal boron nitride(h-BN) as TIMs was elaborated for the first time by the ASTM D 5470 standard test and finite element analysis. It was found that elastic modulus and surface roughness of SR composites increased with the increase of h-BN content, indicating that the conformity was reduced. When the assembly pressure was 0.69 MPa, there existed an optimal h-BN content at which the contact resistance was minimum(0.39 K·cm^(2)·W^(-1)). Although the decreased bond line thickness(BLT) by increasing the assembly pressure was beneficial to reduce the thermal impedance, the proper assembly pressure should be selected to prevent the warpage of the contact surfaces and the increase in contact resistance, according to the compression properties of the SR composites. This study provides valuable insights into fabrication of high-performance TIMs for modern electronic device applications.

关键词： Thermal interface materials Hexagonal boron nitride Thermal impedance Surfaces

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Robust steganographic approach using generative adversarial network and compressive autoencoder

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Multimedia Tools and Applications 2024年 1-38页

作者： Qasaimeh, Malik Qtaish, Alaa Abu Aljawarneh, Shadi Department of Computer Information Systems Faculty of Computer and Information Technology Jordan University of Science and Technology Irbid Jordan Department of Software Engineering co-joint with the Department of Cyber Security Faculty of Computer and Information Technology Jordan University of Science and Technology Irbid Jordan

Nowadays, social media applications and websites have become a crucial part of people’s lives;for sharing their moments, contacting their families and friends, or even for their jobs. However, the fact that these valuable data are transferred via the Internet and open channels, which are vulnerable to attacks and espionage, requires using defense methods to improve the security of data transmission. Recently, the progress of Deep Learning (DL) inspired researchers to use it with security methods such as steganography, the art of hiding secret data in unrelated content. DL and steganography combined enhanced the hiding properties, especially in the Coverless Image Steganography (CIS) methods. In this paper, we propose a Compressive Coverless Image Steganography (CCIS) model, which is a generated-based CIS, to improve the capacity and robustness of Steganography. This model uses the compressive autoencoder to compress the message, thus increasing the capacity, and uses the Generative Adversarial Network (GAN) to generate a stego image from the compressed vector, thus enhancing concealment ability, besides using a regression model and optimization method to extract the data. Another version was designed to enable sending binary messages by replacing the compressive autoencoder network with a robust mapping rule. Experiments show that the proposed model could improve the characteristics of Steganography. Furthermore, the proposed model could extract binary messages with 256 bits from attacked stego images with 99% recovery accuracy. Thus, capacity and robustness were enhanced using our model with both images and text as secret messages. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Generative adversarial networks

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Prediction Of Power Demand And Factor Identification Using Sparse Modeling AI With Ensemble Learning For Improvement Of Accuracy 13

Prediction Of Power Demand And Factor Identification Using S...

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Joint 13th International Conference on Soft Computing and Intelligent systems and 25th International Symposium on Advanced Intelligent systems, SCIS and ISIS 2024

作者： Hachiya, Tatsuma Kamei, Keiji Graduate School of Life Science and Systems Engineering Kyushu Institute of Technology Fukuoka Japan Nishinippon Institute of Technology Faculty of Engineering Fukuoka Japan

ISBN: (纸本)9798350373332

We have been using sparse modeling AI to identify factors and predict in power demand. In this research, we applied ensemble learning to further improve the accuracy by integrating the results of multiple models. Experimental results showed that sparse modeling AI identified the demand factors, and ensemble learning achieved an average absolute prediction error of 7.5%. © 2024 IEEE.

关键词： Demand response

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Challenge-Response Emotion Authentication Algorithm Using Modified Horizontal Deep Learning

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Intelligent Automation & Soft Computing 2023年第3期35卷 3659-3675页

作者： Mohamed Ezz Ayman Mohamed Mostafa Ayman Elshenawy College of Computer and Information Sciences Jouf UniversitySakaka72314Saudi Arabia Systems and Computers Engineering DEPT Faculty of EngineeringAl-Azhar UniversityCairo11651Egypt Software Engineering&Information Technology Faculty of Engineering&TechnologyEgyptian Chinese UniversityEgypt

Face authentication is an important biometric authentication method commonly used in security *** is vulnerable to different types of attacks that use authorized users’facial images and videos captured from social media to perform spooﬁng attacks and dynamic movements for penetrating secur-ity *** paper presents an innovative challenge-response emotions authentication model based on the horizontal ensemble *** proposed model provides high accurate face authentication process by challenging the authorized user using a random sequence of emotions to provide a speciﬁc response for every authentication trial with a different sequence of *** proposed model is applied to the KDEF dataset using 10-fold *** improvements are made to the proposed ***,the VGG16 model is applied to the seven common ***,the system usability is enhanced by analyzing and selecting only the four common and easy-to-use ***,the horizontal ensemble technique is applied to enhance the emotion recognition accuracy and minimize the error during authen-tication ***,the Horizontal Ensemble Best N-Losses(HEBNL)is applied using challenge-response emotion to improve the authentication efﬁ-ciency and minimize the computational *** successive improvements implemented on the proposed model led to an improvement in the accuracy from 92.1%to 99.27%.

关键词： Face authentication challenge-response authentication transfer learning and horizontal ensemble technique

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Uncertainty propagation in the internet of things

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Discover Internet of Things 2024年第1期4卷 1-20页

作者： Pal, Shantanu Khalifa, Sara Miller, Dimity Dedeoglu, Volkan Dorri, Ali Ramachandran, Gowri Moghadam, Peyman Kusy, Brano Jurdak, Raja The School of Information Technology Faculty of Science Engineering and Built Environment Deakin University MelbourneVIC 3125 Australia The School of Information Systems Faculty of Science Queensland University of Technology BrisbaneQLD4000 Australia The School of Electrical Engineering and Robotics Faculty of Engineering Queensland University of Technology BrisbaneQLD4000 Australia The Distributed Sensing Systems Group Data61 CSIRO PullenvaleQLD 4069 Australia The School of Computer Science Faculty of Science Queensland University of Technology BrisbaneQLD 4000 Australia The CSIRO Robotics Data61 CSIRO PullenvaleQLD 4069 Australia

The Internet of Things (IoT) detects context through sensors capturing data from dynamic physical environments, in order to inform automation decisions within cyber physical systems (CPS). Diverse types of uncertainty in the IoT pipeline can propagate within and across nodes, involving complex interactions with security, privacy, and trust that remain largely unexplored. This paper conducts an in-depth analysis of the types of uncertainties in IoT and how they propagate within IoT nodes and networks. We consider adversarial uncertainty in the context of distributed IoT networks to capture perturbations due to malicious actors in the network that can influence IoT security, privacy and trust. We examine the propagation of adversarial uncertainty and well-known uncertainty types, namely aleatoric and epistemic uncertainty, within the five distinct stages of sensing, communication, storage, processing and decision-making in an IoT pipeline, across network layer boundaries, and across nodes within an IoT network. Using this mapping, we analyse the interactions between the uncertainty types and their propagation, and security, privacy, and trust in IoT. Based on this analysis, we discuss guidelines and considerations for mitigating uncertainty in IoT through a smart grid use case study. © The Author(s) 2024.

关键词： Differential privacy

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Improved YOLOv8 for Complex Environmental Fish Detection 7

Improved YOLOv8 for Complex Environmental Fish Detection

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7th IEEE Advanced Information technology, Electronic and Automation Control Conference, IAEAC 2024

作者： Cheng, Tonglin Li, Juan Luo, Jintao Li, Zhihui Beijing University of Technology Faculty of Information Technology China Beijing Engineering Research Center for LoT Software and Systems China

ISBN: (纸本)9798350339161

With the rapid development of computer vision and deep learning technologies, object detection plays a crucial role in various fields. Due to the complexity and diversity of underwater environments, underwater vision tasks face great challenges. In this paper, we improved the YOLOv8 detection model for the fish detection task in complex environments. Specifically, we proposed a multi-scale feature fusion method (MFANet) that combines multiscale weighted feature fusion with multiscale attention to efficiently capture multilevel features of fishes in complex environments. We designed a multiscale weighted feature fusion module that combines feature maps at different scales to enhance the model's representation of the target. By introducing a multi-scale attention mechanism, the model is able to pay more attention to important feature regions. We conducted experiments on real underwater complex environment datasets. The results show that our proposed improved method significantly enhances the performance of the YOLOv8 model in fish detection tasks and lays a good foundation for subsequent underwater detection tasks. © 2024 IEEE.

关键词： Fish

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