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Quality of Service (QoS)-Driven Edge computing and Smart Hospitals: A Vision, Architectural Elements, and Future Directions 1

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NIELIT's International Conference on Communication, Electronics and Digital Technology, NICE-DT 2023

作者： Buyya, Rajkumar Srirama, Satish N. Mahmud, Redowan Goudarzi, Mohammad Ismail, Leila Kostakos, Vassilis Lab School of Computing and Information Systems The University of Melbourne Melbourne Australia School of Computer and Information Sciences The University of Hyderabad Hyderabad India School of Electrical Engineering Computing and Mathematical Sciences Curtin University Perth Australia Lab Department of Computer Science and Software Engineering National Water and Energy Center United Arab Emirates University Abu Dhabi United Arab Emirates

ISBN: (数字)9789819916993

ISBN: (纸本)9789819916986

The Internet of Things (IoT) paradigm is drastically changing our world by making everyday objects an integral part of the Internet. This transformation is increasingly being adopted in the healthcare sector, where Smart Hospitals are now relying on IoT technologies to track staff, patients, devices, and equipment, both within a hospital and beyond. This paradigm opens the door to new innovations for creating novel types of interactions among objects, services, and people in smarter ways to enhance the quality of patient services and the efficient utilisation of resources. However, the realisation of real-time IoT applications in health care and, ultimately, the development of Smart Hospitals are constrained by their current Cloud-based computing environment. Edge computing emerged as a new computing model that harnesses Edge-based resources alongside Clouds for real-time IoT applications. It helps to capitalise on the potential economic impact of the IoT paradigm of $11 trillion per year, with a trillion IoT devices deployed by 2025 to sense, manage, and monitor the hospital systems in real time. This vision paper proposes new algorithms and software systems to tackle important challenges in Edge computing-enabled Smart Hospitals, including how to manage and execute diverse real-time IoT applications and how to meet their diverse and strict Quality of Service (QoS) requirements in hospital settings. The vision we outline can help tackle timely challenges that hospitals increasingly face. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Quality of service

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Case-based Explanation of Classification Models for the Detection of SQL Injection Attacks 31

Case-based Explanation of Classification Models for the Dete...

引用

Workshops at the 31st International Conference on Case-Based Reasoning, ICCBR-WS 2023

作者： Recio-Garcia, Juan A. Orozco-Del-Castillo, Mauricio G. Soladrero, Jose A. Tecnológico Nacional de México IT de Mérida Department of Systems and Computing Merida Mexico Association for the Advancement of Artificial Intelligence Mexico Department of Software Engineering and Artificial Intelligence Instituto de Tecnologías del Conocimiento Universidad Complutense de Madrid Spain

This paper investigates the interpretability of various machine learning models in the context of detecting SQL injection attacks. The models under investigation include decision trees, multi-layer perceptron, random forests, support vector machines, ADA Boost, naive Bayes, and quadratic discriminant analysis. Our main objective is to gain insights into how these models make decisions when classifying SQL commands as either legitimate or potentially malicious. To achieve this, we employ a set of commonly used features from the literature to train and evaluate the models. By prioritizing explainability, our aim is to uncover the underlying factors and decision rules that drive the models’ predictions. Through this research, we seek to bridge the gap between model accuracy and human understanding, thereby facilitating the practical application of machine learning models in real-world security scenarios. The findings of this study contribute to the development of a case-based explanation system that provides valuable insights for cybersecurity practitioners and researchers. © 2023 CEUR-WS. All rights reserved.

关键词： Decision trees

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AmgR: Algebraic Multigrid Accelerated on ReRAM

AmgR: Algebraic Multigrid Accelerated on ReRAM

引用

Design Automation Conference

作者： Mingjia Fan Xiaotian Tian Yintao He Junxian Li Yiru Duan Xiaozhe Hu Ying Wang Zhou Jin Weifeng Liu Super Scientific Software Laboratory China University of Petroleum Beijing Chinese Academy of Sciences Institute of Computing Technology SKLP Institute of Computing Technology CAS Tufts University USA Research Center for Intelligent Computing Systems

Solving systems of linear equations is a fundamental problem in scientific computing, which has been extensively researched for decades. One of the most well-known solvers is Algebraic Multigrid (AMG), which is widely used in high performance computing due to its good scalability. But currently accelerating AMG relies on the traditional von Neumann architecture of storage and computation separation, which leads to a large data transmission overhead. In this work, we propose a ReRAM-based processing-in-memory (PIM) architecture named AmgR, which overcomes the limitations of the traditional von Neumann architecture for AMG ***, accelerating AMG on ReRAM is non-trivial, because (1) AMG has many computing kernels of various types; (2) there are irregular operations that cannot be directly performed using matrix-vector multiplication suitable for ReRAM, i.e., aggregation operation; (3) ReRAM has poor write endurance, and a lot of data during AMG acceleration needs to be rewritten into ReRAM, resulting in high write cost. To address these issues, firstly, we propose a flexible architecture, which can realize each kernel of AMG and is reused by many kernels to improve resource utilization. Secondly, we propose a dedicated unit to realize the aggregation operation. Finally, we present a new mapping strategy to greatly reduce the number of data handling and writes. The experimental results show that the performance of AmgR is improved by an average of one and two orders of magnitude compared to HYPRE on the CPU and AmgX on the GPU, respectively, while the energy consumption is reduced by an average of two and three orders of magnitude.

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Automatic contradiction detection in Spanish

Automatic contradiction detection in Spanish

引用

2021 Doctoral Symposium on Natural Language Processing from the PLN.net Network, PLNnet-DS-2021

作者： Sepúlveda-Torres, Robiert Department of Software and Computing Systems University of Alicante Apdo. de Correos 99 AlicanteE-03080 Spain

This paper addresses the lack of automated contradiction detection systems for the Spanish language. The ES-Contradiction dataset was created and contains examples with two pieces of information classified as Compatible, Contradiction, or Unrelated. To the author’s knowledge, a Spanish-language contradiction dataset is non-existent and therefore, the ES-Contradiction dataset fills an important research gap, given Spanish being one of the most widely spoken languages. Moreover, the dataset built includes a fine-grained annotation of the different types of contradictions in the dataset. A baseline system was designed to validate the effectiveness of the dataset. The BETO transformer model was used to build this baseline system, which obtained a good result to detect the three class labels Compatible, Contradiction, or Unrelated. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Deep learning

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GPLSI team at CheckThat! 2021: Fine-tuning BETO and RoBERTa

GPLSI team at CheckThat! 2021: Fine-tuning BETO and RoBERTa

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2021 Working Notes of CLEF - Conference and Labs of the Evaluation Forum, CLEF-WN 2021

作者： Sepúlveda-Torres, Robiert Saquete, Estela Department of Software and Computing Systems University of Alicante Apdo. de Correos 99 AlicanteE-03080 Spain

CheckThat! Lab is a challenging lab aimed at tackling the disinformation problem. The GPLSI team from the University of Alicante (Spain) has participated in two tasks of the CheckThat! Lab namely, Task 1 (Check-Worthiness Estimation) and Task 3 (Fake News Detection). We attained second and fifth place in the Spanish-version and English-version of Subtask 1A. Our systems use models based on transfer learning such as RoBERTa and BETO. The best results were achieved by fine-tuning these models. However, our results for Subtask 3A are low compared to the team that achieved the best result. We included some external features in the models for Subtask 1A and 3A, but we could not improve the results. In future work, we will experiment by incorporating other external features into the models with the aim of improving the results of the tasks. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Learning systems

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SUPPLYDECK - A Blockchain-Based Pharmaceutical Supply Chain Management 4

SUPPLYDECK - A Blockchain-Based Pharmaceutical Supply Chain ...

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4th International Conference on Advancements in computing, ICAC 2022

作者： Amarasinghe, A.A.B.G. Gamagedara, G.M.H.S. Pitigala, K.K. Subawickrama, H.D.A.E. Abeywardena, Kavinga Yapa Yapa, Kanishka Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Systems Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

With the rising competition among pharmaceutical companies, the current drug supply chain market has become more competitive with high-quality product segments. The rapid growth of internet pharmacies has made it more difficult to standardize drug safety throughout in complex distributed supply chain networks. There is a high chance of introducing counterfeit drugs which are almost the same as the original pharmaceuticals. Due to the lack of transparency the possibility of tampering with drugs in the current manual and web-based pharmaceutical systems is extremely high. Throughout the past recent years, these counterfeit drugs were recognized as the one of major worldwide problems. This situation is worse in developing countries. The unavailability of verifying the legitimacy of drug suppliers and poor mechanisms to trace the drugs were identified as critical points that need to be resolved. SUPPLYDECK comes as a solution for the critical scenario mentioned. This solution addresses the above problems using blockchain technology, as a distributed digital ledger that ensures transparency, traceability, and security. This can show promise for solving some global supply chain management problems using smart contracts and user authentication along with IoT technology and machine learning concepts that are critically examined with this potential application. © 2022 IEEE.

关键词： Smart contract

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Smart Advertising Based on Customer Preferences and Manage the Supermarket 4

Smart Advertising Based on Customer Preferences and Manage t...

引用

4th International Conference on Advancements in computing, ICAC 2022

作者： Eishan Dinuka, W.H.A. Wickramasinghe, A.Y.S.W. Weerasinghe, W.S.H. Karunaratne, K.P.G. Liyanapathirana, Chethana Rupasinghe, Lakmal Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Systems Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

As a developing country, Sri Lanka needs to go along with cutting-edge technologies. In the beginning phase of this digital advertising, multiple advertisements were displayed on the users' feeds, including advertisements despite their preferences. This was a terrible user experience for the users. However, smart advertising based on customer preferences can manage the flow of advertisements on the feed as per the users' preferences. This same technique can be used in handling advertisements while shopping at supermarkets. These advertisements can be directed based on demographic characteristics like face and gender and previous customer transactions. Additionally, providing the nearest supermarket they can reach based on their current location. Queue management is the next most crucial facility that needs to be provided to a supermarket. However, the manual system of queue management is not effective. But with a modernized queue management system, overcrowded supermarkets can be managed effectively. This proposed system also considers providing a chatbot service to manage customer inquiries in a reliable strategy. In this system, we mainly used the Keras model called VGGFace for face detection, the Conventional Neural Network and Keras-based model for gender detection, the TensorFlow model called Single Shot MultiBox Detection MobileNet for queue and crowd detection, the Apriori algorithm base model for predicting the buying pattern, a Keras-based model for Artificial Intelligence chatbot and finally, google map Application Programming Interface for the nearest supermarket finding are models and technology. This system was developed to manage a supermarket properly. © 2022 IEEE.

关键词： Sales

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True Rays Model Integration in OMNeT++ for IIoT Network Planning in Underground Mines

True Rays Model Integration in OMNeT++ for IIoT Network Plan...

引用

Antennas and Propagation (LACAP), IEEE Latin American Conference on

作者： Cristian Suancha Oscar Montanez Fabian Medina Eduardo Avendano Fernandez Sandra Cespedes Systems and Computing Engineering School UPTC Sogamoso Colombia Electronic Engineering School UPTC Sogamoso Colombia Computer Science and Software Engineering Concordia University Montreal Canada

ISBN: (数字)9798331527587

ISBN: (纸本)9798331527594

This work develops a new module in the OMNeT++ simulator incorporating and validating the True Rays propagation model for underground environments. The integration enables the planning and evaluation of Industrial Internet of Things deployments of wireless sensor networks (WSNs) in mining scenarios. The tool can read the mine blueprints and deploy nodes at specified locations. It also defined the environment and network communication parameters for network coverage and performance analysis, allowing an understanding of how the WSN behaves in the underground mine before its deployment. The simulation predicts variables such as received power and path losses, optimizing sensing coverage and connectivity while reducing the need for site surveys. A large number of simulations using blueprints from real mines show that the signal propagation measurements are consistent with the theoretical models proposed in the state of the art. Experimental results were compared with a simulation WSN using LoRa, the maximum range obtained in simulation was 47 m, the measurements under real conditions in the underground only achieved 25 m of reach, but were limited at a threshold of -100 dBm to ensure connectivity and reliability of transmission among the nodes. As a result, the simulations and measurements performed better at the 433 MHz frequency, and the main contribution is a simulation tool simplifying planning IIoT networks in mining tunnels.

关键词： Surveys Wireless sensor networks Visualization Sensitivity Prototypes Planning Frequency measurement Sensors Reliability Industrial Internet of Things

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Optimizing Quality and Energy Efficiency in Webrtc with ML-Powered Adaptive FEC

Optimizing Quality and Energy Efficiency in Webrtc with ML-P...

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IEEE International Conference on Multimedia and Expo Workshops (ICMEW)

作者： Jason Gerard David C. Bonilla Abdelhak Bentaleb Sandra Céspedes Department of Computer Science & Software Eng. Concordia University Montreal Canada Department of Systems & Computing Eng. Universidad de Los Andes Bogotá Colombia

ISBN: (数字)9798350379815

ISBN: (纸本)9798350379822

Video and audio communication on mobile devices involves dynamic channels with fluctuating error rates along with the added constraints of battery efficiency and resource-limited hardware. Forward error correction (FEC) is a common method for error recovery but introduces computational and bandwidth overhead. To enhance FEC efficiency, machine learning (ML) can adapt error correction based on current channel dynamics. Existing solutions often use complex models, leading to performance issues and inefficiency. Our proposed solution prioritizes energy efficiency and practical deployment by combining Reed-Solomon coding and supervised learning. This approach corrects up to 60% of errors and achieves 2.5 times better energy efficiency than standard WebRTC and 1.7 times better efficiency than non-adaptive Reed-Solomon coding.

关键词： Adaptation models Analytical models Error analysis Supervised learning Forward error correction Predictive models Streaming media

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Analysis of Bitcoin Fork by Colored Petri Nets

Analysis of Bitcoin Fork by Colored Petri Nets

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IEEE International Conference on systems, Man and Cybernetics

作者： Zeyu Zhou Ding Liu Tatiana R. Shmeleva Dmitry A. Zaitsev School of Mechano-Electronic Engineering Xidian University Xi'an China Max Planck Institute for Software Systems Kaiserslautern and Saarbruecken Germany School of Computing University of Derby UK

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

Bitcoin is under the threat of fork since it operates with a distributed ledger. Predicting the fork probability in advance is beneficial for taking early action to avoid malicious attacks. In this study, we compose a colored Petri net model of Bitcoin. Our model consists of a given number of nodes, and each node has five subpages representing the node structure: proof of work, broadcast blocks, verify blocks, and the process of adding blocks to blockchain, respectively. Simulation results of fork probability can be easily obtained and analyzed by observing the data in the measuring components of subpages. The results show that our model correctly simulates the fork probability: on recent Bitcoin data, compared with the results of the wide-known SimBlock simulator, a difference of some 4.3% has been obtained. Thus, taking into account vivid graphical representation, our model has certain advantages for the developing techniques of attack avoidance.

关键词： Network topology Distributed ledger Simulation Petri nets Bitcoin Probability Proof of Work Topology Security Propagation delay

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