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Vessels Segmentation in Angiograms Using Convolutional Neural Network: A Deep Learning Based Approach

computer Modeling in Engineering & Sciences 2023年第7期136卷 241-255页

作者： Sanjiban Sekhar Roy Ching-Hsien Hsu Akash Samaran Ranjan Goyal Arindam Pande Valentina E.Balas School of Computer Science and Engineering Vellore Institute of TechnologyVellore632014India Department of Computer Science and Information Engineering Asia UniversityTaichung41354Taiwan Department of Medical Research China Medical University HospitalChina Medical UniversityTaichung406Taiwan Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology School of Mathematics and Big DataFoshan UniversityFoshan528000China Medica Superspecialty Hospital Kolkata700099India Automation and Applied Informatics Aurel Vlaicu University of AradArad310130Romania

Coronary arterydisease(CAD)has become a significant causeof heart attack,especially amongthose 40yearsoldor *** is a need to develop new technologies andmethods to deal with this *** researchers have proposed image processing-based solutions for CADdiagnosis,but achieving highly accurate results for angiogram segmentation is still a *** different types of angiograms are adopted for CAD *** paper proposes an approach for image segmentation using ConvolutionNeuralNetworks(CNN)for diagnosing coronary artery disease to achieve state-of-the-art *** have collected the 2D X-ray images from the hospital,and the proposed model has been applied to *** augmentation has been performed in this research as it’s the most significant task required to be initiated to increase the dataset’s ***,the images have been enhanced using noise removal techniques before being fed to the CNN model for segmentation to achieve high *** the output,different settings of the network architecture undoubtedly have achieved different accuracy,among which the highest accuracy of the model is 97.61%.Compared with the other models,these results have proven to be superior to this proposed method in achieving state-of-the-art results.

关键词： Angiogram convolution neural network coronary artery disease diagnosis of CAD image segmentation

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IoT-Fog Computing Sustainable System for Smart Cities: A Queueing-based Approach 1

IoT-Fog Computing Sustainable System for Smart Cities: A Que...

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1st International Conference in Advanced Innovation on Smart City, ICAISC 2023

作者： Goswami, Veena Sharma, Bhisham Patra, Sudhansu Shekhar Chowdhury, Subrata Barik, Rabindra Kumar Dhaou, Imed Ben School of Computer Applications KIIT Deemed to Be University Bhubaneswar India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India MCA Department AP Chittoor India Dar Al-Hekma University Hekma School of Engineering Computing and Informatics Department of Computer Science Jeddah Saudi Arabia

ISBN: (纸本)9781665472753

In the current scenarios there is a lot of development in the networking sector. Additionally needed are quick operations and the capability to solve complex issues. From several technical angles, IoT is being promoted to meet these developments. Implementations of IoT confront difficulties in handling such enormous volume of data including issues with its Quality of Services (QoS) necessities, privacy with security and the variety of networking elements. In smart cities, a vast volume of data is generated through IoT devices. They need to be processed near the edge devices due to latency issues, especially in the case of critical data-sensitive applications. Fog computing, a new technological paradigm, delivers a collection of networking essential services nearer to the client than cloud computing does. Fog computing overrides the cloud computing in the areas such as networking infrastructure scalability, latency reduction, network service dependability, and network device security. The technical approach to provide the highest degree of computing service has advanced by contributing cloud-assisted network services nearer to the end user/customer level. Fog servers can malfunction in a variety of circumstances. In this study, we describe the fog system as a machine-repair problem, where repair work is performed at a certain pace as soon as the Virtual Machine (VM) malfunctions. To analyze the system, numerous numerical analyses have been conducted. © 2023 IEEE.

关键词： Fog computing

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Novel SSD-Based Models for Detection of Multidimensional Pulmonary Nodules in CT Images 7

Novel SSD-Based Models for Detection of Multidimensional Pul...

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7th International Conference on Signal Processing and Information Security, ICSPIS 2024

作者： Ji, Zhanlin Hao, Shengnan Pang, Jianhua Ganchev, Ivan Zhejiang A&F University College of Mathematics and Computer Science Hangzhou China North China University of Science and Technology Department of Artificial Intelligence Tangshan China University of Plovdiv 'Paisii Hilendarski' Department of Computer Systems Plovdiv Bulgaria Institute of Mathematics and Informatics Bulgarian Academy of Sciences Sofia Bulgaria University of Limerick Telecommunications Research Centre Limerick Ireland

ISBN: (纸本)9798350368673

Lung cancer, as one of the diseases with the highest incidence and mortality rates in the world, has always been a big challenge that humans are constantly striving to address. Pulmonary nodules, as one of the early manifestations of lung cancer, constitute a breakthrough in early detection of this disease and its prompt treatment. Currently, significant progress has been made in object detection models based on deep learning in the context of increasingly scarce medical resources. To make pulmonary nodule detection more efficient and accurate, this paper proposes two novel models, based on the Single Shot MultiBox Detector (SSD) model. The proposed models adapt to the detection of small pulmonary nodules by changing the size of the feature map of the input prediction module. In addition, the prediction frame is modified to make greater use of the shallow feature layer. A group of up-sampling modules is added by increasing asymmetric convolution and a feature pyramid network (FPN) mechanism is used for improving the detection performance. The experimental results, obtained on the LUNA16 dataset, demonstrate that the proposed models achieve great performance improvement compared to the baseline (SSD). © 2024 IEEE.

关键词： Lung cancer

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Eliminating Crossings in Ordered Graphs 19

Eliminating Crossings in Ordered Graphs

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19th Scandinavian Symposium on Algorithm Theory, SWAT 2024

作者： Agrawal, Akanksha Cabello, Sergio Kaufmann, Michael Saurabh, Saket Sharma, Roohani Uno, Yushi Wolff, Alexander Indian Institute of Technology Madras Chennai India Faculty of Mathematics and Physics University of Ljubljana Slovenia Institute of Mathematics Physics and Mechanics Ljubljana Slovenia Department of Computer Science Tübingen University Germany Institute of Mathematical Sciences Chennai India University of Bergen Norway Graduate School of Informatics Osaka Metropolitan University Sakai Japan Universität Würzburg Germany

ISBN: (纸本)9783959773188

Drawing a graph in the plane with as few crossings as possible is one of the central problems in graph drawing and computational geometry. Another option is to remove the smallest number of vertices or edges such that the remaining graph can be drawn without crossings. We study both problems in a book-embedding setting for ordered graphs, that is, graphs with a fixed vertex order. In this setting, the vertices lie on a straight line, called the spine, in the given order, and each edge must be drawn on one of several pages of a book such that every edge has at most a fixed number of crossings. In book embeddings, there is another way to reduce or avoid crossings;namely by using more pages. The minimum number of pages needed to draw an ordered graph without any crossings is its (fixed-vertex-order) page number. We show that the page number of an ordered graph with n vertices and m edges can be computed in 2m · nO(1) time. An O(log n)-approximation of this number can be computed efficiently. We can decide in 2O(d√k log(d+k)) · nO(1) time whether it suffices to delete k edges of an ordered graph to obtain a d-planar layout (where every edge crosses at most d other edges) on one page. As an additional parameter, we consider the size h of a hitting set, that is, a set of points on the spine such that every edge, seen as an open interval, contains at least one of the points. For h = 1, we can efficiently compute the minimum number of edges whose deletion yields fixed-vertex-order page number p. For h > 1, we give an XP algorithm with respect to h + p. Finally, we consider spine+t-track drawings, where some but not all vertices lie on the spine. The vertex order on the spine is given;we must map every vertex that does not lie on the spine to one of t tracks, each of which is a straight line on a separate page, parallel to the spine. In this setting, we can minimize in 2n · nO(1) time either the number of crossings or, if we disallow crossings, the number of tracks. © Akanks

关键词： Computational geometry

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Predicting Chemical Reaction Product by Graph Transformer

Predicting Chemical Reaction Product by Graph Transformer

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computer Science, computer Engineering, & Applied Computing (CSCE), Congress in

作者： Shunya Makino Nobuaki Yasuo Masakazu Sekijima Department of Computer Science Tokyo Institute of Technology Yokohama Japan Academy for Convergence of Materials and Informatics (TAC-MI) Tokyo Institute of Technology Yokohama Japan

The substantial cost and prolonged duration associ-ated with drug discovery present significant challenges within the pharmaceutical industry. A potential solution to alleviate these issues is molecular translation, a process where an input molecule is converted into another molecule following specific rules or conditions. In this study, we introduce a novel machine learning technique for predicting chemical reaction outcomes: the molecular graph translation method, employing a transformer architecture designed for efficient chemical reaction product prediction. We assessed the performance of our proposed method using the USPTO dataset for chemical reaction product prediction. Our results demonstrated an accuracy of 86.5%. Although this accuracy was slightly lower than that of the Molecular Transformer (a string-based method using a similar architecture), our approach surpassed both the Seq2Seq and other graph-based methods in terms of performance.

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Efficient Resource Management in IoTs Using Evolutionary and Swarm Intelligence Algorithms 7

Efficient Resource Management in IoTs Using Evolutionary and...

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7th International Symposium on Innovative Approaches in Smart Technologies, ISAS 2023

作者： Gupta, Keshav Dev Cengiz, Korhan Awasthi, Charu Ramini, Siva Akash Chatterjee, Shyamapriya Pavithra, M. Poornima College of Engineering Department of Computer Science Engineering Jaipur India University of Fujairah College of Information Technology United Arab Emirates Istinye University Department of Computer Engineering Istanbul Turkey University of Hradec Kralove Faculty of Informatics and Management Department of Information Technologies Hradec Kralove500 03 Czech Republic JSS Academy of Technical Education Department of Information Technology Noida India Andhra Pradesh Amaravati India Narula Institute of Technology Department of Information Technology West Bengal Kolkata India Jansons Institute of Technology Karumathampatti Department of Computer Science and Engineering Coimbatore641659 India

ISBN: (纸本)9798350383065

The proliferation of the Internet of Things (IoT) has ushered in a transformative era of connected devices, emphasizing the critical need for effective resource management. This study introduces an innovative approach that harnesses Evolutionary and Swarm Intelligence algorithms for IoT Task Scheduling, addressing resource optimization challenges. The approach offers superior resource utilization through advanced optimization techniques, reducing energy consumption and enhancing efficiency. Furthermore, it significantly reduces task scheduling execution time, enabling prompt decision-making in dynamic IoT environments. This results in improved task allocation quality, meeting application-specific requirements, and prioritizing critical tasks. Notably, the approach excels in minimizing completion time, making it particularly advantageous for real-time IoT applications. This research contributes to the advancement of IoT resource management, offering an adaptive, efficient, and intelligent solution with broad applicability. In the evolving landscape of IoT, the findings presented here lay a solid foundation for future research and practical implementations, ultimately promoting more responsive, sustainable, and intelligent IoT ecosystems. © 2023 IEEE.

关键词： Swarm intelligence

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What do European Stakeholders think about Open Social Innovation?

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IFAC-PapersOnLine 2024年第3期58卷 55-60页

作者： Eleni N. Arvaniti Chrysostomos D. Stylios Agapi Dima Computer Technology Institute and Press “Diophantus” GR 26504 Patras Greece Industrial Systems Institute Athena RC GR 26504 Patras Greece Department of Informatics and Telecommunications University of Ioannina GR 47100 Arta Greece

Open Social Innovation (OSI) is a new fast-growing discipline of Open Innovation that is mainly focused on tackling societal matters and challenges under the auspices of co-creation, collaboration, and co-working. This work presents a research study that analyses the state and potential of applying OSI at the European level by investigating the views of various European stakeholders coming from several countries and regions. As the contributors come from various and different organizations, regions and countries, questions arose, as to how all these participants could successfully co-create and perform in an OSI environment. The investigated methodology used a specially designed questionnaire to analyze and compare stakeholders’ performance and potential for applying OSI in their region. Evaluating the answers provides several insights into the participants’ nature, how their characteristics can be an asset or a deterrent for OSI implementation, and the similar issues and problems they faced. Suggestions and recommendations for the further adoption and promotion of OSI are discussed and concluded.

关键词： Co-creation European regional assessment Open Social Innovation Regional Innovation

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An Artificial Intelligence (AI) Based X-AODV Routing Protocol in Wireless Networks 4

An Artificial Intelligence (AI) Based X-AODV Routing Protoco...

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4th International Conference on Emerging Trends in Networks and computer Communications, ETNCC 2024

作者： Hussain, Khalid Ullah Sheikh, Md Amin Jazri, Husin Bin Muzzaffar, Saira Chowdhury, Sohini Kavita School of Computing and Informatics Albukhary International University Kedah Alor Setar Malaysia School of Computer Science Taylor's University Faculty of Innovation and Technology Subang Jaya Malaysia Lovely Professional University Division of Research and Development Phagwara144411 India KKR and KSR Institute of Technology and Sciences Andhra Pradesh Guntur India Chandigarh Group of Colleges Jhanjeri Department of Computer Science and Engineering Punjab Mohali140307 India

ISBN: (纸本)9798350353266

The multi-hopping mechanism features in the wireless network environment, in which all nodes contain the information of link and connectivity in any infrastructure less manner. When mobile devices either jump from their original network or change their location without describing any fashion, it is named mobile ad hoc network MANET. To ensure the up to date information related to the location and to provide the routing traffic of the node, numerous protocols have been used to remain efficient in achieving this for instance, AODV, DSR, DSDV etc. While we, the peer-to-peer networking, have challenges in many places, security is something that warrants attention more than any other things. The signal corruption hampers data transmission in bedwire networks when the attacks take place. This kind of activity can touch anyone including the layers lying above the physical and below the network layer. In the current discussion we developed, proposition of diversified, efficient and secure AI-based X-AODV routing protocol. We have investigated our proposed protocol against the recent modified two protocols which are SAODV and ARAN. The outcome of simulation reveals that our proposed routing protocol takes place in successfully performing of attack detection and is also the best when it comes to providing security and performance. The Simulation outcomes exhibit the Networks' performance improvement. © 2024 IEEE.

关键词： Network layers

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TSO-DSO Interaction: Privacy-Preserving Optimal Power Flow with Distributed Generators Using a Machine Learning-Based Approach

TSO-DSO Interaction: Privacy-Preserving Optimal Power Flow w...

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IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)

作者： Burak Dindar Can Berk Saner Hüseyin Kemal Çakmak Veit Hagenmeyer Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Germany Department of Electrical and Computer Engineering National University of Singapore Singapore

ISBN: (数字)9798350318098

ISBN: (纸本)9798350318104

The integration of distributed generators (DGs) into the electrical grid has introduced new dimensions in power system management: Enhancing efficiency and operational flexibility of the grid requires taking into account the DGs located at the distribution level in dispatch decisions, while also considering the operational constraints of both distribution and transmission levels. However, the centralization of cooperation between transmission system operators (TSOs) and distribution system operators (DSOs) is troublesome due to privacy concerns of both parties. In present paper, we introduce a Machine Learning-Based Privacy-Preserving Optimal Power Flow (MLB-PP-OPF) framework. This method enables the seamless inclusion of DGs at the distribution level in optimal power flow calculations, all while adhering to the operational limits of both systems and maintaining data privacy. The proposed approach leverages three machine learning models to map the distribution system variables to active and reactive power flows at the point of common coupling, and to determine the feasible operating region of the distribution system in a privacy-preserving manner. Comparative case studies, performed on the coupled IEEE 30-bus transmission and 33-bus distribution test systems, demonstrate that the results achieved using MLB-PP-OPF align almost perfectly with those obtained through classical OPF, while maintaining data privacy.

关键词： Couplings Data privacy Reactive power Privacy Machine learning Generators Data models

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Transformer-Based Embeddings for Greek Language Categorization

Transformer-Based Embeddings for Greek Language Categorizati...

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International Conference on computer and Information Science (ACIS)

作者： Charalampos M. Liapis Konstantinos Kyritsis Isidoros Perikos Michael Paraskevas Mathematics Dept. University of Patras Computer Technology Institute & Press “Diophantus” Patras Greece Electrical and Computer Engineering Dept. University of Peloponnese Patras Greece Computer Engineering and Informatics Department Electrical and Computer Engineering Dept. University of Patras University of Peloponnese Computer Technology Institute and Press “Diophantus” Patras Greece Electrical and Computer Engineering Dept. University of Peloponnese Computer Technology Institute and Press “Diophantus” Patras Greece

ISBN: (数字)9798350376647

ISBN: (纸本)9798350376654

The Greek School Network (GSN) provides support to students, teachers, and school units in secondary education across Greece. Handling numerous user queries manually can be challenging, necessitating the development of an automated system for accurate categorization of these queries. This paper presents a comparative study of various transformer-based models for multi-class text categorization of Greek language queries submitted to the GSN helpdesk. We introduce a new experimental balanced dataset and extract vector representations from eleven transformer-based models. These representations are evaluated using ten classic machine learning classifiers. Our findings highlight the superior performance of the Multilingual E5 Text Embeddings model, particularly when paired with the extreme gradient-boosting classifier. This combination demonstrates a clear advantage in accurately categorizing user queries, paving the way for more efficient automated helpdesk systems.

关键词： Information science Accuracy Computational modeling Text categorization Education Machine learning Transformers Vectors

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