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A distributed Machine Learning Approach to Tertiary Structure Prediction of Protein 15

A Distributed Machine Learning Approach to Tertiary Structur...

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15th international conference on advances in computing, Control, and Telecommunication Technologies, ACT 2024

作者： Mahoorkar, Ravi Kiran Niranjan, T.S. Dharshan, H.B. Sivagamasundari, G. Department of Computer Science and Engineering PES University Bengaluru India

ISBN: (纸本)9798331300579

This research investigates the utility of the AlphaFold technique, a deep gaining knowledge of-primarily based method, for the perfect prediction of protein tertiary structures from their corresponding amino acid sequences. The alpha-fold method is a deep learning-based approach that has been shown to accurately predict the 3D structure of proteins with a high degree of accuracy. This involve training the AlphaFold model on a large dataset of known protein structures and their corresponding amino acid sequences, and then using the trained model to predict the structures of novel proteins. The accuracy of the predictions will be evaluated using a variety of metrics, by comparing the reference and predicted structures and Global Distance Test (GDT). The advantages of using the alpha-Fold method, including its high accuracy and wide range of protein targets, as well as its limitations and challenges, such as the need for high computational resources and the limited availability of experimental validation data. The potential applications of accurate protein structure prediction are vast, including aiding in drug discovery, understanding protein function, and guiding experimental studies. The use of the alpha-fold method has the potential to significantly improve the accuracy of protein structure predictions and advance our understanding of the complex world of proteins. © Grenze Scientific Society, 2024.

关键词： Prediction models

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Comparative Analysis of Heart Disease Prediction System using Different Machine Learning Techniques in Geospatial Serverless Fog computing 14

Comparative Analysis of Heart Disease Prediction System usin...

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14th international conference on advances in computing, Control, and Telecommunication Technologies, ACT 2023

作者： Nanda, Sandeep Khandar, Punam Swain, Sarat Chandra Parida, Prasanta Kumar Kalinga Institute of Industrial Technology Deemed to be University Bhubaneswar India Shri Ramdeobaba College of Engineering and Management Nagpur India

In this modern era huge changes are occurring in our day to day routine which is putting an impact towards our health. Healthcare systems diagnose the disease during the early stage but it is being noticed that the detection occurs at the last stage where the cost of the treatment is expensive. The healthcare systems always generate huge amount of data and the growth of the data is always exponential. Basically serverless computing is the emerging cloud service model for the distributed applications and here the services are being provided on the basis of pay as you use. The healthcare systems generate large amount of data and these data grow exponentially in nature. The big data is analysed in an effective way when these data are organized in a very efficient manner. In this paper we have proposed the Geospatial Serverless Fog computing model which enables geospatial serverless fog computing platform and clusters the health records based on the medical attributes by which the heart disease is being predicted at the early stage using different classifiers and made a comparision amongst them. In this paper we have used a dataset of patients records for our framework and we have also tested using the dataset and then the basic performance of the proposed diseases prediction system is being observed in terms of accuracy and standard deviation by using them in Amazon web Services. © Grenze Scientific Society, 2023.

关键词： Diseases

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Block Chain and distributed computing Aided with Cloud Technology- A Specific Reference to Security Issues of Healthcare Industry 2

Block Chain and Distributed Computing Aided with Cloud Techn...

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2nd IEEE international conference on advances in computing, Communication and Applied Informatics, ACCAI 2023

作者： Murugamani, Chakravarthi Nadh Singh, Bhaludra R. Pravalika, Kallu Rethvikha Sri, P. Sowmya, Chennuru Sai Reddy, Mankhala Shreya Department of Information Technology Bhoj Reddy Engineering College for Women Telangana Hyderabad59 India Department of Computer Science and Engineering Bhoj Reddy Engineering College for Women Telangana Hyderabad59 India Bhoj Reddy Engineering College for Women Telangana Hyderabad59 India

ISBN: (纸本)9798350315905

There has been a significant uptick in the need for user-centric electronic records to save the many characteristics of a patient's medical history as they are recorded at a hospital during treatment and to make those records available as and when they are needed for future treatment, care, or invoicing. Blockchain technology allows us to save these data on a distributed ledger, allowing us to begin and enable use at breakneck speeds while still maintaining a transparent and secure system. To save records safely and in an interoperable fashion, a distributed system with ledger functionality is used. Block chain technology has the potential to revolutionize the way digital assets are transacted by removing the need for a trusted third party to authenticate data authenticity, record asset ownership, or mediate financial or data transactions. Immutability, decentralisation, and transparency are three of its defining characteristics, making it well suited to resolving pressing problems in the healthcare industry, such as the lack of comprehensive peer-to-peer files and the inability to easily access patients' medical histories. Health care systems that are efficient and successful depend on interoperability, the capacity of different health organisations and manufacturers of different software products to connect and share data in a safe and smooth manner. Many problems in modern healthcare can be traced back to a lack of interoperability, such as siloed data, sluggish communications, and different workflow tools. To address this, it is recommended to implement a system that provides secure, pseudo-anonymous access to complete, recognised longitudinal medical records stored in silos. In this article, we conducted a system overview and literature review of block chain technology in a fog computing environment, both of which are capable of processing vast amounts of data in a decentralised fashion. Our in-progress experimental study reveals weaknesses in existing systems

关键词： Interoperability

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Didal: distributed Data Library for Development of parallel Fragmented Programs 17th

Didal: Distributed Data Library for Development of Paralle...

引用

parallel computing Technologies - 17th international conference, PaCT 2023, Proceedings

作者： Malyshkin, Victor Schukin, Georgy Institute of Computational Mathematics and Mathematical Geophysics SB RAS Novosibirsk Russia Novosibirsk State Technical University Novosibirsk Russia Novosibirsk State University Novosibirsk Russia

ISBN: (纸本)9783031416729

Nowadays with rapid evolution of high-performance computing systems it’s becoming essential to have tools to simplify development of efficient portable parallel programs for these systems. Fragmented programming is a technology where parallel program is represented as a collection of pieces of data (data fragments) and computations on these pieces (computation fragments), able to be tuned to the resources of a computing system and automatically provide such facilities as dynamic load balancing. Didal is a distributed data library to support development of efficient parallel fragmented programs on distributed memory supercomputers. The library contains facilities for data partitioning, distribution and load balancing. In this paper foundations of the library are explained and applicability of the library is demonstrated with Particle-in-Cell (PIC) method implementation, which shows performance comparable to conventional parallel programming tools. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： parallel programming

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The Adaptive Fault-tolerant Routing Based on an Improved Local Security Information Model of the Exchanged Hypercube 21

The Adaptive Fault-tolerant Routing Based on an Improved Loc...

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21st IEEE international Symposium on parallel and distributed Processing with Applications, 13th IEEE international conference on Big Data and Cloud computing, 16th IEEE international conference on Social computing and Networking and 13th international conference on Sustainable computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Zhang, Yazhi Luo, Chuanwen Wang, Guijuan Zhang, Li Lv, Mengjie Yu, Jiguo Qilu University of Technology School of Computer Science and Technology Jinan China Beijing Forestry University School of Information Science and Technology Beijing China Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China Nanjing University of Posts and Telecommunications College of Computer Nanjing China Qilu University of Technology Shandong Academy of Sciences Big Data Research Institute Jinan China

ISBN: (纸本)9798350329223

With the increasing amount of computation in high-performance computing, the scale of interconnection networks is becoming larger and larger. It is inevitable that processors or links in the network become faulty. Therefore, it is very important for a processor to understand the security status of itself and neighbors, and then adaptively and reliably communicate. However, the existing security information models consider faulty processors or faulty links separately, and do not consider the situation where both processors and links fail simultaneously. The Exchanged Hypercube is an excellent interconnection network structure which achieves a balance between network functionality and hardware overhead while preserving many excellent properties of the Hypercube. In this paper, we propose an adaptive fault-tolerant routing algorithm of the Exchanged Hypercube based on an improved local security information model, which considers the faulty processors and faulty links simultaneously. This algorithm always can select suitable processors for routing based on the local security information and unsafe coefficients of processors, which greatly reduces the impact of the faulty of networks. The adaptive fault-tolerant routing algorithm of the Exchanged Hypercube network is not only suitable for regular networks but also for heterogeneous networks since the Exchanged Hypercube is a semi regular network. Sufficient experimental results show that the algorithm proposed in this paper has a lower packet loss rate, a higher success rate, and a shorter average path length. © 2023 IEEE.

关键词： Hypercube networks

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Advancing Cloud Security Frameworks Implementing distributed Ledger Technology for Robust Data Protection and Decentralized Security Management in Cloud computing Environments 2

Advancing Cloud Security Frameworks Implementing Distributed...

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2nd IEEE international conference on advances in Information Technology, ICAIT 2024

作者： Rajasekar, P. Kalaiselvi, K. Shanmugam, Raju Tamilselvan, S. Pandian, A. Pasumpon Department of ECE Sri Krishna College of Technology Kovaipudur Tamil Nadu Coimbatore India Department of Electronics and Communication Engineering Hindusthan College of Engineering and Technology Tamil Nadu Coimbatore India Unitedworld School of Computational Intelligence Karnavati University Gujarat India Department of Computer Science and Engineering Saveetha School of Engineering SIMATS Saveetha University Tamil Nadu Chennai India Department of Computer Science and Engineering CARE College of Engineering Tamilnadu Trichy India

ISBN: (纸本)9798350383867

Cloud computing caused the paradigm shift in business performance, from scalability to flexibility as well as affordability in the management of computing resources. Nevertheless, ensuring security of the data remains a key issue in the cloud due to the centralized interactions between service provider and a single vulnerability in the network can put rest of the data at risk. Consequently, the application of DLT, in addition to other solutions such as DLT, demonstrates a big step towards the improvement of cloud security frameworks. This article focuses on the implementation of DLT for data protection applications that are based on a solid dataset and decentralized security procedures in cloud environments. DLT utilization, like blockchain, provides an organization with integrity data, transparency, and fitness to counter cyber threats. Architecture stacks up sponsors such as cloud providers, users, and applications and DLT is responsible for the security of the transaction and the security policy enforcement. Customers use those services via desktop based application with transparent security policy arisen from DLT. Moreover, DLT also does identity management in the way that is decentralized, data sharing in the manner that it is secure, and the compliance to regulatory frameworks, which in addition reduces the trust and privacy risks in the cloud ecosystems. The proposed architecture is genuinely a big jump toward protecting cloud security from centralized control interruptions and thus, enhancing resilience and stability in cloud computing. © 2024 IEEE.

关键词： Cloud security

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Large-Scale Deep Learning Medical Image Methodology and Applications Using Multiple GPUs 7

Large-Scale Deep Learning Medical Image Methodology and Appl...

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7th international conference on advances in Biomedical Engineering, ICABME 2023

作者： Krishnasamy, Ezhilmathi Boudisa, Selma Kanli, Georgia Marzal-Abarca, Francesc Xavier Keunen, Oliver Bouvry, Pascal University of Luxembourg Parallel Computing and Optimization Group Fstm Belval Luxembourg Luxembourg Institute of Health Translational Radiomics Belval Luxembourg

ISBN: (纸本)9798350325850

Digitalization of medical images has become firmly established in research labs and clinical settings worldwide, and its numerous benefits have helped drive its rapid expansion, which is predicted to continue momentum over the coming years. Its advantages of cutting costs, improving analysis, productivity and patient outcomes, reducing errors, and enhancing imaging and innovation will likely propel its widespread adoption. In recent years digitalization of medical images especially relied on high performance computing. This work illustrates how a large volume of digital radiology data can be analysed in a parallel heterogeneous architecture. We have used TensorFlow (including Keras) and the Horovod API to speed up the learning of Deep Learning models, particularly using GPUs in single and multiple compute nodes. We conclude that using Horovod API with data parallelism shows tremendous speed gains compared to traditional CPU when training the 2D UNet model. © 2023 IEEE.

关键词： Graphics processing unit

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Using the Compute Continuum for Data Analysis: Edge-cloud Integration for Urban Mobility 31

Using the Compute Continuum for Data Analysis: Edge-cloud In...

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31st Euromicro international conference on parallel, distributed and Network-Based Processing, PDP 2023

作者： Belcastro, Loris Marozzo, Fabrizio Orsino, Alessio Talia, Domenico Trunfio, Paolo University of Calabria Rende Italy

ISBN: (纸本)9798350337631

More and more in recent years, IT companies have adopted edge-cloud continuum solutions to efficiently perform analysis tasks on data generated by IoT devices. As an example, in the context of urban mobility, the use of edge solutions can be extremely effective in managing tasks that require real-time analysis and low response times, such as driver assistance, collision avoidance and traffic sign recognition. On the other hand, the integration with cloud systems can be convenient for tasks that require a lot of computing resources for accessing and analyzing big data collections, such as route calculations and targeted advertising. Designing and testing such hybrid edge-cloud architectures are still open issues due to their novelty, large scale, heterogeneity, and complexity. In this paper, we analyze how the compute continuum can be exploited for efficiently managing urban mobility tasks. In particular, we focus on a case study related to taxi fleets that need to find locations where they are more likely to find new passengers. Through a simulation-based approach, we demonstrate that these solutions turn out to be effective for this class of problems, especially as the number of connected vehicles increases. © 2023 IEEE.

关键词： Cloud computing architecture

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Leveraging the Compute Power of Two HPC Systems for Higher-Dimensional Grid-Based Simulations with the Widely-distributed Sparse Grid Combination Technique 23

Leveraging the Compute Power of Two HPC Systems for Higher-D...

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2023 international conference for High Performance computing, Networking, Storage and Analysis, SC 2023

作者： Pollinger, Theresa Van Craen, Alexander Niethammer, Christoph Breyer, Marcel Pflüger, Dirk Institute for Parallel and Distributed Systems Universität Stuttgart Stuttgart Germany High Performance Computing Center Universität Stuttgart Stuttgart Germany

ISBN: (纸本)9798400701092

Grid-based simulations of hot fusion plasmas are often severely limited by computational and memory resources;the grids live in four- to six-dimensional space and thus suffer the curse of dimensionality. However, high resolutions are required to fully capture the physics of interest. The sparse grid combination technique is a multi-scale method in which many anisotropically coarse resolved grids are used to approximate a fine-scale solution - -and it alleviates the curse of *** paper presents the core concepts of the widely-distributed combination technique, which allows us to use the compute power and memory of more than one HPC system for the same simulation. We apply the sparse grid combination technique to a six-dimensional advection problem serving as a proxy for plasma simulations. The full-grid solution approximated by the combination technique would contain ≈ 5 ZB if computed with conventional grid-based methods. Even the combination technique simulation operates on ≈ 1 × 1011 double-precision degrees of freedom, or 988 GB, plus the supporting sparse grid data structures. We propose a new approach to divide the compute load between the two HPC systems, requiring only 76 GB to be exchanged. Based on this, we have realized the first synchronous combination technique simulation using two HPC systems, in our case the two German Tier-0 supercomputers HAWK and SuperMUC-NG. On two systems, the simulation can be computed at an average overhead of ≈ 35 % (108 s per combination step) for file I/O and transfer. The presented concepts apply to any pair of HPC systems if high-speed data transfer is possible. © 2023 ACM.

关键词： Supercomputers

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Intelligent Scheduling Strategy for Heterogeneous Multi-terminal Access Tasks for Complex Cloud-Edge Collaborative computing 4

Intelligent Scheduling Strategy for Heterogeneous Multi-term...

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4th international conference on Information Science, parallel and distributed Systems, ISPDS 2023

作者： Wang, Haotian College of Software Nankai University Tianjin China

ISBN: (纸本)9798350337181

With the rapid development of network and mobile devices, the era of ten thousands households interconnection is gradually coming. The variety of applications is endless, putting higher demands on computing resources as well as latency. As a result, the task scheduling model of cloud-edge collaboration has emerged. In the current environment, due to the limited resources of edge nodes and the expanding volume of users and user data, how to allocate tasks to the best nodes becomes the most critical issue. To address this problem, this paper proposes the use of ant colony algorithm to optimize the cloud-edge collaborative task scheduling. The pheromone cumulative positive feedback method is mainly used to reflect the tendency of tasks to select processing devices. First, the probability of a processing device being selected by a task is calculated by pheromones. Then, a random number is used to determine the allocation strategy for each round of the cycle. Finally, the pheromone concentration of the processing device is updated and the minimum resource consumption as well as the optimal task assignment strategy is derived. The implementation results show that the ant colony algorithm can improve the response time, reduce the resource consumption, and improve the efficiency of multi-objective task scheduling. © 2023 IEEE.

关键词： Ant colony optimization

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