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arXiv 2021年

作者： Mhiri, Islem Nebli, Ahmed Mahjoub, Mohamed Ali Rekik, Islem Université de Sousse Ecole Nationale d’Ingénieurs de Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Sousse4023 Tunisia BASIRA Lab Faculty of Computer and Informatics Engineering Istanbul Technical University Istanbul Turkey

Brain graph synthesis marked a new era for predicting a target brain graph from a source one without incurring the high acquisition cost and processing time of neuroimaging data. However, works on recovering a brain graph in one modality (e.g., functional brain imaging) from a brain graph in another (e.g., structural brain imaging) remain largely scarce. Besides, existing multimodal graph synthesis frameworks have several limitations. First, they mainly focus on generating graphs from the same domain (intra-modality), overlooking the rich multimodal representations of brain connectivity (inter-modality). Second, they can only handle isomorphic graph generation tasks, limiting their generalizability to synthesizing target graphs with a different node size and topological structure from those of the source one. More importantly, both target and source domains might have different distributions, which causes a domain fracture between them (i.e., distribution misalignment). To address such challenges, we propose an inter-modality aligner of non-isomorphic graphs (IMANGraphNet) framework to infer a target graph modality based on a given modality. Our three core contributions lie in (i) predicting a target graph (e.g., functional) from a source graph (e.g., morphological) based on a novel graph generative adversarial network (gGAN);(ii) using non-isomorphic graphs for both source and target domains with a different number of nodes, edges and structure;and (iii) enforcing the source distribution to match that of the ground truth graphs using a graph aligner to relax the loss function to optimize. Furthermore, to handle the unstable behavior of gGAN, we design a new Ground Truth-Preserving (GT-P) loss function to guide the non-isomorphic generator in learning the topological structure of ground truth brain graphs more effectively. Our comprehensive experiments on predicting target functional brain graphs from source morphological graphs demonstrate the outperformance of IMA

关键词： Brain mapping

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An Evaluation of Augmentative and Alternative Communication Research for ASD Children in Developing Countries: Benefits and Barriers 22nd

An Evaluation of Augmentative and Alternative Communication ...

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22nd International Conference on Human-computer Interaction, HCI International 2020

作者： Farzana, Walia Sarker, Farhana Hossain, Quazi Delwar Chau, Tom Mamun, Khondaker A. Advanced Intelligent Multidisciplinary Systems Lab Department of Computer Science and Engineering United International University Dhaka Bangladesh Department of Computer Science and Engineering University of Liberal Arts Bangladesh Dhaka Bangladesh Department of Electrical & Electronic Engineering Chittagong University of Engineering & Technology Chittagong Bangladesh Institute of Biomaterials and Biomedical Engineering University of Toronto Toronto Canada

ISBN: (纸本)9783030607029

Augmentative and Alternative Communication (AAC) technology research not only enhance communication but also communal skills in verbally challenged children with Autism Spectrum Disorder (ASD). However, the research on AAC technology is mainly concentrated in developed countries and less explored in developing countries. In this study, we utilized evaluation method to analyze the prospects, existing practices and future possibilities, benefits and barriers of AAC research in developing countries. It is found that Speech Generating Devices (SGD) are mostly preferred by children and in future artificial intelligence (AI) based mobile application will augment communication skills among verbally challenged children. We conclude with general recommendation on succeeding research, collaborative approach and implementation with funding opportunities for substantial growth of AAC technology research in developing countries. This study will facilitate directions for initiating AAC research in developing countries and will accommodate researchers, developers and stakeholders to acknowledge opportunities, barriers, probable and current state of AAC research. © 2020, Springer Nature Switzerland AG.

关键词： Developing countries

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Optical properties of chiral three-dimensional photonic crystals

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Physical Review B 2023年第16期107卷 165307-165307页

作者： Shun Takahashi Takeyoshi Tajiri Yasuhiko Arakawa Satoshi Iwamoto Willem L. Vos Kyoto Institute of Technology Matsugasaki Sakyo-ku Kyoto 606-8585 Japan Department of Computer and Network Engineering The University of Electro-Communications 1-5-1 Chofugaoka Chofu Tokyo 182-8585 Japan Institute for Nano Quantum Information Electronics The University of Tokyo 4-6-1 Komaba Meguro-ku Tokyo 153-8505 Japan Research Center for Advanced Science and Technology The University of Tokyo 4-6-1 Komaba Meguro-ku Tokyo 153-8505 Japan Institute of Industrial Science The University of Tokyo 4-6-1 Komaba Meguro-ku Tokyo 153-8505 Japan Complex Photonic Systems (COPS) MESA+ Institute for Nanotechnology University of Twente P.O. Box 217 7500 AE Enschede The Netherlands

We perform a theoretical and numerical study of the optical properties of both direct and inverse three-dimensional (3D) chiral woodpile structures and a corresponding chiral Bragg stack, also known as a Reusch pile. We compute transmission spectra in the helical direction for finite crystals and photonic band structures, where we ensure the effective index of all structures to be the same. We find that both 3D structures show dual-band circular dichroism, where light with a particular circular polarization state—either left- or right-handed—reveals a broad stop band with major attenuation, whereas the other polarization state is transmitted nearly unimpeded. We observe such gaps in different frequency ranges with alternating handedness. The appearance of the circular-polarized gaps is successfully interpreted with a physical model wherein the circular polarization either corotates or counterrotates with the chiral structure, thereby effectively leading to a spatially dependent or a constant refractive index, and thus to the presence or absence of a gap. We find that the presence or absence of circularly polarized gaps is tuned by the transverse periods perpendicular to the chiral axis in both the 3D direct and inverse chiral woodpile crystal structures. The tunability of circular dichroism may find applications as on-chip sensors for circularly polarized light and in the on-chip detection of chiral molecules.

关键词： Photonic crystals Nanostructures Chiral symmetry Band structure methods Finite-difference time-domain method

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CM-MLP: Cascade Multi-scale MLP with Axial Context Relation Encoder for Edge Segmentation of Medical Image

CM-MLP: Cascade Multi-scale MLP with Axial Context Relation ...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Jinkai Lv Yuyong Hu Quanshui Fu Zhiwang Zhang Yuqiang Hu Lin Lv Guoqing Yang Jinpeng Li Yi Zhao Henan Institute of Advanced Technology Zhengzhou University Zhengzhou China Suining Central Hospital Suining China School of Electrical and Information Engineering The University of Sydney Sydney Australia School of Mathematics and Computer Sciences NanChang University Nanchang China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China Hwa Mei Hospital University of Chinese Academy of Sciences Ningbo China The Research Center for Ubiquitous Computing Systems Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

The convolutional-based methods provide good segmentation performance in the medical image segmentation task. However, those methods have the following challenges when dealing with the edges of the medical images: (1) Previous convolutional-based methods do not focus on the boundary relationship between foreground and background around the segmentation edge, which leads to the degradation of segmentation performance when the edge changes complexly. (2) The inductive bias of the convolutional layer cannot be adapted to complex edge changes and the aggregation of multiple-segmented areas, resulting in its performance improvement mostly limited to segmenting the body of segmented areas instead of the edge. To address these challenges, we propose the CM-MLP framework on MFI (Multiscale Feature Interaction) block and ACRE (axial context relation encoder) block for accurate segmentation of the edge of medical image. In the MFI block, we propose the cascade multi-scale MLP (Cascade MLP) to process all local information from the deeper layers of the network simultaneously and utilize a cascade multiscale mechanism to fuse discrete local information gradually. Then, the ACRE block is used to make the deep supervision focus on exploring the boundary relationship between foreground and background to modify the edge of the medical image. The segmentation accuracy (Dice) of our proposed CM-MLP framework reaches 96.96%, 96.76%, and 82.54% on three benchmark datasets: CVC-ClinicDB dataset, sub-Kvasir dataset, and our inhouse dataset, respectively, which significantly outperform the state-of-the-art method. The source code and trained models will be available at https://***/ProgrammerHyy/CM-MLP.

关键词： Convolutional codes Degradation Image segmentation Fuses Convolution Image edge detection Source coding

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CM-MLP: Cascade Multi-scale MLP with Axial Context Relation Encoder for Edge Segmentation of Medical Image

arXiv

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arXiv 2022年

作者： Lv, Jinkai Hu, Yuyong Fu, Quanshui Zhang, Zhiwang Hu, Yuqiang Lv, Lin Yang, Guoqing Li, Jinpeng Zhao, Yi Henan Institute of Advanced Technology Zhengzhou University Zhengzhou China The Research Center for Ubiquitous Computing Systems Institute of Computing Technology Chinese Academy of Sciences Beijing China Suining Central Hospital Suining China Hwa Mei Hospital University of Chinese Academy of Sciences Ningbo China School of Electrical and Information Engineering The University of Sydney Sydney Australia School of Mathematics and Computer Sciences NanChang University Nanchang China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China

The convolutional-based methods provide good segmentation performance in the medical image segmentation task. However, those methods have the following challenges when dealing with the edges of the medical images: (1) Previous convolutional-based methods do not focus on the boundary relationship between foreground and background around the segmentation edge, which leads to the degradation of segmentation performance when the edge changes complexly. (2) The inductive bias of the convolutional layer cannot be adapted to complex edge changes and the aggregation of multiple-segmented areas, resulting in its performance improvement mostly limited to segmenting the body of segmented areas instead of the edge. To address these challenges, we propose the CM-MLP framework on MFI (Multi-scale Feature Interaction) block and ACRE (axial context relation encoder) block for accurate segmentation of the edge of medical image. In the MFI block, we propose the cascade multi-scale MLP (Cascade MLP) to process all local information from the deeper layers of the network simultaneously and utilize a cascade multiscale mechanism to fuse discrete local information gradually. Then, the ACRE block is used to make the deep supervision focus on exploring the boundary relationship between foreground and background to modify the edge of the medical image. The segmentation accuracy (Dice) of our proposed CM-MLP framework reaches 96.96%, 96.76%, and 82.54% on three benchmark datasets: CVC-ClinicDB dataset, sub-Kvasir dataset, and our in-house dataset, respectively, which significantly outperform the state-of-the-art method. The source code and trained models will be available at https://***/ProgrammerHyy/CM-MLP. Copyright © 2022, The Authors. All rights reserved.

关键词： Semantic Segmentation

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Simulation and Field Testing of Multiple Vehicles Collision Avoidance Algorithms

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IEEE/CAA Journal of Automatica Sinica 2020年第4期7卷 1045-1063页

作者： Chaoyue Zu Chao Yang Jian Wang Wenbin Gao Dongpu Cao Fei-Yue Wang the College of Computer Science and Technology Jilin UniversityChangchun 130012China Jiangsu XCMG Construction Machinery Research Institute Ltd. Xuzhou 221004China the College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of EducationJilin UniversityChangchun 130012 Chongqing Xibu Automobile Proving Ground Management Co.Ltd. Chongqing 404100China the State Grid JIBEI Electric Power Company Limited Management Training Center China the Advanced Vehicle Engineering Center Cranfield UniversityCranfield MK430ALUK the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

A global planning algorithm for intelligent vehicles is designed based on the A* algorithm, which provides intelligent vehicles with a global path towards their destinations. A distributed real-time multiple vehicle collision avoidance(MVCA)algorithm is proposed by extending the reciprocal n-body collision avoidance method. MVCA enables the intelligent vehicles to choose their destinations and control inputs independently,without needing to negotiate with each other or with the coordinator. Compared to the centralized trajectory-planning algorithm, MVCA reduces computation costs and greatly improves the robustness of the system. Because the destination of each intelligent vehicle can be regarded as private, which can be protected by MVCA, at the same time MVCA can provide a real-time trajectory planning for intelligent vehicles. Therefore,MVCA can better improve the safety of intelligent vehicles. The simulation was conducted in MATLAB, including crossroads scene simulation and circular exchange position simulation. The results show that MVCA behaves safely and reliably. The effects of latency and packet loss on MVCA are also statistically investigated through theoretically formulating broadcasting process based on one-dimensional Markov chain. The results uncover that the tolerant delay should not exceed the half of deciding cycle of trajectory planning, and shortening the sending interval could alleviate the negative effects caused by the packet loss to an extent. The cases of short delay(< 100100 ms) and low packet loss(< 5%) can bring little influence to those trajectory planning algorithms that only depend on V2 V to sense the context, but the unpredictable collision may occur if the delay and packet loss are further worsened. The MVCA was also tested by a real intelligent vehicle, the test results prove the operability of MVCA.

关键词： Collision avoidance intelligent vehicles intervehicle communication simulation testing trajectory planning

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An Exploration of K-Mer Ranges for Megahit in the Context of Microbial Community-Wide Identification of Antimicrobial Resistance Genes and Biosynthetic Gene Clusters

An Exploration of K-Mer Ranges for Megahit in the Context of...

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Alina Cărunta Alexandru Eugeniu Mizeranschi Cristina Cărunta Horia Leonard Banciu Oana Teodora Moldovan Daniela Zaharie Viorel Negru Faculty of Mathematics and Computer Science West University of Timişoara Timişoara Romania Institute for Advanced Environmental Research West University of Timişoara Timişoara Romania Research and Development Station for Bovine Arad Arad Romania Department of Computers and Information Technology Politehnica University of Timişoara Timişoara Romania Department of Molecular Biology and Biotechnology Babeş-Bolyai University Cluj-Napoca Romania Centre for Systems Biology Biodiversity and Bioresources Babeş-Bolyai University Cluj-Napoca Romania Cluj-Napoca Department Emil Racoviţă Institute of Speleology Cluj-Napoca Romania

ISBN: (数字)9798331518622

ISBN: (纸本)9798331518639

With the advent of genomics and next generation sequencing, metagenomics has become a discipline in its own right, enabling for the first time the study of complex microbial ecosystems containing species that cannot be cultured in the lab. Sequencing and characterizing these microbial genomes enables the identification of novel antimicrobial resistance genes (ARGs) and biosynthetic gene clusters (BGCs), with potential applications in industry. De novo sequence assembly, as a crucial step in metagenomics, is currently being implemented with tools such as MEGAHIT, which employ a multiple $k$ -mer approach, where several intermediate assemblies are built from k-mers from a range of sizes and merged at the end. The objective of this study was to investigate the impact that this range of k-mer sizes could have on a range of quality metrics, including the number of identified ARGs and BGCs, using a series of assembly scenarios involving 7 samples collected from the Movile Cave in Romania We found that larger k-mer sizes and more fine-grained ranges of intermediate steps were associated with increased metrics, including larger numbers of identified BGCs. Future studies are required in order to better understand the role of the range of k-mer sizes in MEGAHIT in the context of microbial communitywide identification of ARGs and BGCs.

关键词： Measurement Industries Sequential analysis Metagenomics Ecosystems Object recognition Bioinformatics Assembly Next generation networking Immune system

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Reference-Plane Invariant Free Space Dielectric Material Characterization up to 330 GHz

Reference-Plane Invariant Free Space Dielectric Material Cha...

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URSI Atlantic Radio Science Conference (URSI AT-RASC)

作者： Salvador Moreno-Rodríguez Mario Pérez-Escribano Sergio Ortiz-Ruiz Antonio Alex-Amor Borja Plaza-Gallardo Francisco G. Ruiz Carlos Molero Department of Signal Theory Telematics and Communications Research Centre for Information and Communication Technologies (CITIC-UGR) University of Granada Granada Spain Telecommunication Research Institute (TELMA) Universidad de Málaga E.T.S. Ingeniería de Telecomunicación Málaga Spain Department of Electronics and Computer Science Pervasive Electronics Advanced Research Laboratory (PEARL) University of Granada Granada Spain Department of Electrical and Systems Engineering University of Pennsylvania Philadelphia Pennsylvania United States Radiofrequency Area National Institute for Aerospace Technology (INTA) Madrid Spain

ISBN: (数字)9789463968102

ISBN: (纸本)9798350360257

This paper describes the process followed to implement a system to characterize the complex permittivity of materials in the 10-330 GHz frequency band. Firstly, the method used and the system’s calibration process are shown, consisting of a double calibration TRL (Thru-Reflect-Line) and GRL (Gated-Reflect-Line). Subsequently, a smoothing technique is used to improve the accuracy of the results. Finally, a test is performed on quartz and glass fiber samples, showing that the results are quite reliable over the entire measured bandwidth.

关键词： Accuracy Smoothing methods Permittivity measurement Glass Bandwidth Position measurement Reflection

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Multi-Resolution Localization of Individual Logs in Wooden Piles Utilizing YOLO with Tiling on Client/Server Architectures 33

Multi-Resolution Localization of Individual Logs in Wooden P...

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33rd European Modeling and Simulation Symposium, EMSS 2021

作者： Praschl, Christoph Auersperg-Castell, Philipp Forster-Heinlein, Brigitte Zwettler, Gerald Adam Research Group Advanced Information Systems and Technology Research and Development Department University of Applied Sciences Upper Austria Softwarepark 11 Hagenberg4232 Austria Department of Software Engineering School of Informatics Communications and Media University of Applied Sciences Upper Austria Softwarepark 11 Hagenberg4232 Austria Bluedynamics Auersperg-Castell KG Kritzing 31 Freinberg4785 Austria Faculty of Computer Science and Mathematics University of Passau Innstraße 43 Passau94032 Germany

In industrial domains with time and cost intensive manual or semi-automated inspection the demand for automation is high. Utilizing state of the art deep learning models for localization in vision-based domains such as wood log analysis, the precision can be increased while reducing the demand for manual inspection. In this paper a YOLO network is trained on wood log images to allow for detection of single wood piles in images with hundreds and thousands instances. Due to the high variability in scale and large amount of wood logs within the images, common YOLO architectures are not applicable. Thus, tiling is necessitated to implicitly form a multi-resolution image pyramid. Due to lack in training data, besides common data augmentation modelling of different seasonal and weather conditions is applied. The wood log detection process can be run on a client/server architecture to allow for both, preview and refined results. Evaluation on real-world data sets shows an log detection accuracy of 82,9% utilizing a tiny YOLO model and 94,1% with a fully connected YOLO model, respectively. © 2021 The Authors.

关键词： Deep learning

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A Segmentation Algorithm for Cerebral Hematoma Based on Spatial and Multi-scale Positional Attention Mechanism and Unet

A Segmentation Algorithm for Cerebral Hematoma Based on Spat...

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Networking, Communications and Information technology (NetCIT), International Conference on

作者： Hongyu Deng Taipeng Guo Linbo Gong Wentao Wang Yaohui Liu School of Computer and Artificial Intelligence Xiangnan University Chenzhou Hunan China Chenzhou Stroke Artificial Intelligence Technology Research and Development Center Hunan China Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems Hunan China

ISBN: (纸本)9781665400718

For segmenting the target lesions accurately in CT images of cerebral hematoma, this paper proposes a spatial and multi-scale neural network segmentation model (MSHA-Unet). The model fuses the semantic information of the top and bottom layers of images in the same level by multi-kernel convolution, and fuses the attention mechanism in multi-scale feature images by jumping connection, so as to accurately locate and segment cerebral hematoma in medical CT images. To verify the effectiveness of the model, the experiment was carried out on 3716 CT images of 81 cases of cerebral hemorrhage, and the model was compared with six neural network models. The experimental results were measured by various evaluation standards, and showed that the model was superior to other network models.

关键词： Image segmentation Fuses Convolution Computed tomography Neural networks Semantics Information and communication technology

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