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Multi-layer network modelling of genomic and transcriptomic data to investigate the response to checkpoint inhibitors in NSCLC

Multi-layer network modelling of genomic and transcriptomic ...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Mascolo, Davide Farina, Lorenzo Petti, Manuela Sapienza University of Rome Program in Data Science Rome Italy Sapienza University of Rome Dept. of Computer Control and Management Engineering Rome Italy

ISBN: (纸本)9798350337488

Recent innovations and developments in molecular biology and biotechnology have made it possible to acquire and store large omics datasets. In particular genomics, transcriptomics and the study of their relationship represent the key elements to understand how genotype influences phenotype. In this work we investigate the potential of multi-layer network modeling in integrating genomic and transcriptomic data of 152 advanced non-small cell lung cancer (NSCLC) patients treated with anti-PD-(L)1 therapy. For the transcriptomic layer, we performed differential expression and differential co-expression analyses in order to identify a subset of key genes in differentiating responder patients from non-responders. Adding to the genomic-transcriptomic model other three layers related to immune, myeloid and curated immunotherapy-based literature signatures we obtained a 5-layer Patient Similarity Network. The application of Similarity Network Fusion algorithm revealed a statistically significant stratification of patients (p-value ≤ 0.05) which allows the identification of two clusters characterized by patients responding and not responding to immunotherapy. © 2023 IEEE.

关键词： immunotherapy multi-layer network Network-based omics integration non-small cell lung cancer patient Stratification

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Scalable, Cost Effective IoT Based Medical Oxygen Monitoring System for Resource Constrained Hospital Environment 6

Scalable, Cost Effective IoT Based Medical Oxygen Monitoring...

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6th IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2022

作者： Rodrigues, Joel Chandra Shekar, R.K. School of Engineering Dept. of Computer Science and Engg. Bengaluru India BITS Pilani Pilani Campus Dept. of Computer Science and Information Systems India

ISBN: (数字)9781665487160

ISBN: (纸本)9781665487160

Oxygen therapy is one of the critical treatments employed in epidemics, pandemics, and natural calamities. Recent covid pandemic worldwide witnessed many deaths due to improper management, delayed delivery, and wastage of medical oxygen. Therefore, efficient utilization of available oxygen is very important. To monitor and manage oxygen, several hospitals employ IoT-based systems. Scalability is an essential feature in such monitoring systems in order to cater to the needs of a sudden surge in the number of patients requiring oxygen. The most commonly employed technique to monitor and manage an oxygen cylinder uses a pressure sensor where scaling up is an issue. Therefore, in this paper, a scalable solution that efficiently measures and monitors the available oxygen in the cylinder is proposed. The approach measures oxygen level using a weight sensor module and raises alerts during critical conditions such as low oxygen level and blockage or leakage of oxygen. The proposed system is a cost-effective, plug-and-play system that aids rapid deployment thereby providing timely care to the patients. Also, it does not require any change in the existing infrastructure making it suitable for a resource-constrained environment. The proposed system supports a web-based dashboard and mobile app that can be remotely accessed. © 2022 IEEE.

关键词： Oxygen

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COLLABORATIVE LEARNING IN STEAM TEACHING FOR STUDENTS IN THE CENTRAL AMAZON 21

COLLABORATIVE LEARNING IN STEAM TEACHING FOR STUDENTS IN THE...

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21st International Conference on e-Society, ES 2023 and 19th International Conference on Mobile Learning, ML 2023

作者： Rodrigues, Juliana Gisele Corrêa de Medeiros Silva, Adan Sady da Silva Junior, Jucimar Maia Post-graduation program in Biodiversity and Biotechnology from BIONORTE Amazonas State University Brazil Dept. of Meteorology Amazonas State University Brazil Dept. of Computer Engineering Amazonas State University Brazil

ISBN: (纸本)9789898704474

The State of Amazonas has one of the most modern industrial and technological centers in Latin America. As a result, the search for skilled professionals for this job market is constantly growing. It is believed that STEAM teaching is an important tool to improve engagement, creativity, innovation, problem-solving skills, and other cognitive benefits generating more skilled professionals in the technology market. One approach that can be applied to STEAM teaching in schools is collaborative learning through maker culture. From mobile labs the STEM Academy Project takes STEAM teaching to high school students in public schools in the state of Amazonas. In the courses taught, collaborative learning is also applied in order for students to understand topics such as basic electronics, robotics, and programming, thus stimulating students' social skills and shared mutual learning, and attracting them to degree courses in STEAM fields. © 2023 Proceedings of the International Conferences on e-Society 2023, ES 2023 and Mobile Learning 2023, ML 2023. All rights reserved.

关键词： Students

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Deep Learning Approach Based on Generative Adversarial Network for Automatic Diagnosis of Sucker-Rod Pump Operational Conditions

Deep Learning Approach Based on Generative Adversarial Netwo...

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2024 Mediterranean Offshore Conference, MOCE 2024

作者： Moussa, Ahmed Darweesh, Mohamed Zamel, Amr A. El Hadi Nabih Ahmed, Abd Agiba Petroleum Company Cairo Egypt Computer and Systems Engineering Department Faculty of Engineering Zagazig University Egypt Department of Mathematical Statistics Dept. Faculty of Graduate Studies for Statistical Research Cairo University Egypt

ISBN: (纸本)9781959025702

Early and accurate detection of operational anomalies in sucker-rod pumping wells is crucial. Maximizing production while minimizing downtime is essential. Traditionally, dynamometer (dyno) card classification has been labor-intensive and inefficient, especially with increasing high-frequency sensor data. To address this, a Semi-supervised Generative Adversarial Network (SSGAN) is proposed. It classifies sucker-rod pump conditions. The model uses both labeled and unlabeled dyno card data. It learns the underlying data distribution. Synthetic data is generated to improve the training set. This significantly enhances classification accuracy compared to traditional supervised Convolutional Neural Networks (CNNs), especially with limited data. SSGAN achieves an accuracy of 86% with limited labeled data and surpasses 92% accuracy with increased labeled data, outperforming the CNN model in both cases. By reducing the reliance on extensive manual labeling, this method offers a promising solution for improving the efficiency and effectiveness of sucker-rod pump monitoring and maintenance. Copyright 2024, Society of Petroleum Engineers.

关键词： Gasoline

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Current-limiting control of interlinking converter to maintain power balance in hybrid microgrids

Current-limiting control of interlinking converter to mainta...

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2022 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2022

作者： Skentzos, Panagiotis Konstantopoulos, George C. The University of Sheffield Dept. of Automatic Control and Systems Engineering Sheffield United Kingdom University of Patras Dept. of Electrical and Computer Engineering Patra Greece

ISBN: (数字)9781665480321

ISBN: (纸本)9781665480321

In this paper, a novel nonlinear current-limiting controller that maintains the desired power balance in a hybrid microgrid, is proposed for interlinking converters (ICs). The RMS value of the IC current is analytically proven to remain below a desired maximum value at all times using nonlinear ultimate boundedness theory, without limiting separately the d- and q-axis current components and without using adaptive saturation units, as done in conventional approaches. Furthermore, the stability of the closed loop system is investigated through root locus analysis for different values of the controller gain. Finally, the performance of the proposed control scheme is validated through detailed simulation results of an interlinking converter connected to both an AC and a DC subgrid. © 2022 IEEE.

关键词： Controllers

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iSFA: Intelligent SF Allocation Approach for LoRa-Based Mobile and Static End Devices

iSFA: Intelligent SF Allocation Approach for LoRa-Based Mobi...

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IEEE Conference on Wireless Communications and Networking

作者： Anakhi Hazarika Nikumani Choudhury Dept. of Electrical & Electronics Engineering India Dept. of Computer Science & Information Systems India

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

LoRaWAN (Long Range Wide Area Network) is a low-power, wide-area wireless communication protocol designed specifically for the Internet of Things (IoT) and machine-to-machine (M2M) applications that enable long-range, bidirectional communication between low-power devices. Lo-RaWAN employs Adaptive Data Rate (ADR) technology to dynamically adjust the data rate for each device based on its signal quality and distance from the gateway. ADR enables improved network performance, extends device battery life, and simplifies network management, making LoRaWAN suitable for various IoT deployments. However, the end devices' inefficient utilization of radio resources (e.g., spreading factor and transmission power) significantly degrades network performance, device battery life, and adaptability to changing network conditions. Machine Learning (ML) algorithms analyze and optimize the real-time network conditions to enhance network performance. This work aims to develop an ML-based approach that adaptively selects the most suitable Spreading Factor (SF) for end devices (ED). Two independent ML algorithms such as K-means and Reinforcement Learning (RL) have been applied to EDs and Gateways, respectively, to dynamically allocate SF for both static and mobile EDs. Through simulations, the performance of the proposed mechanism is analyzed in terms of packet success rate, convergence time, energy consumption, latency, and throughput.

关键词： Performance evaluation Wireless communication Wide area networks Machine learning algorithms Reinforcement learning Logic gates Throughput

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Controlled Dropout for Uncertainty Estimation

Controlled Dropout for Uncertainty Estimation

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Hasan, Mehedi Hossain, Ibrahim Rahman, Ashikur Nahavandi, Saeid Institute for Intelligent Systems Research and Innovation Deakin University GeelongVIC3220 Australia Bangladesh University of Engineering and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350337020

Uncertainty quantification in a neural network is one of the most discussed topics for safety-critical applications. Though Neural Networks (NNs) have achieved state-of-the-art performance for many applications, they still provide unreliable point predictions, which lack information about uncertainty estimates. Among various methods to enable neural networks to estimate uncertainty, Monte Carlo (MC) dropout has gained much popularity in a short period due to its simplicity. In this study, we present a new version of the traditional dropout layer where we are able to fix the number of dropout configurations. As such, each layer can take and apply the new dropout layer in the MC method to quantify the uncertainty associated with NN predictions. We conduct experiments on both toy and realistic datasets and compare the results with the MC method using the traditional dropout layer. Performance analysis utilizing uncertainty evaluation metrics corroborates that our dropout layer offers better performance in most cases. © 2023 IEEE.

关键词： dropout Monte Carlo dropout neural network Uncertainty estimation

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Multi-objective optimization for cloud provisioning: A case study in large-scale microservice notification applications 9

Multi-objective optimization for cloud provisioning: A case ...

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9th International Conference on Future Internet of Things and Cloud, FiCloud 2022

作者： Vrbaski, Mira Bolic, Miodrag Majumdar, Shikharesh University of Ottawa School of Electrical Engineering and Computer Science Ottawa Canada Carleton University Dept. of Systems and Computer Engineering Ottawa Canada

ISBN: (数字)9781665493505

ISBN: (纸本)9781665493505

An approach to optimizing a large-scale microservice deployment for a critical notification system is presented. This paper addresses optimization for three objectives: cloud service cost, cloud resource utilization of CPU, RAM and storage, and meeting the system notification deadlines. To the best of our knowledge, this is the first work dealing with multi-objective optimization for microservice notification applications where the notification load is variable and depends on other priorly executed microservice in request processes. Furthermore, best of our knowledge, this is the first work that is based on multi-objective optimization, analyzing and proposing a Pareto front and optimal list from preselected VM candidates. First, the paper formulates multi-objective optimization problems for microservice-based large-scale notification system applications and provides the mathematical deployment model. Then, based on the expected workload and required multi-objective criteria, the paper proposes a set of algorithms that provide the Pareto front optimal solution for preselecting a Cloud Service provider's VM type. In the end, the paper presents a case study that demonstrates the use of the proposed technique. © 2022 IEEE.

关键词： Multiobjective optimization

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Reliable Data Storage and Sharing using Block chain Technology and Two Fish Encryption 4

Reliable Data Storage and Sharing using Block chain Technolo...

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4th International Conference on Inventive Research in Computing Applications, ICIRCA 2022

作者： Sivanantham, S. Sakthivel, M. Krishnamoorthy, V. Balakrishna, N. Akshaya, V. Sree Vidyanikethan Engineering College Dept. of Computer Science and Systems Engineering Andhra Pradesh Tirupati India Sree Vidyanikethan Engineering College Dept. of Computer Science and Engineering Andhra Pradesh Tirupati India Bannari Amman Institute of Technology Dept. of Computer Science and Engineering Tamilnadu Sathyamangalam India

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

Digital data that has been certified by a respected institution is valuable and can be saved or transmitted over the internet. However, the issues are ensuring the security and reliability of stored and shared data, as well as ensuring a secure, transparent, and fair data sharing process. As a result, The schemas for data production, storage, and sharing is suggested. A group signature scheme in the data production schema for a collection of respected organisations that provide similar services is used. A member of the group develops precious digital data from RD (raw data) provided by a DO (data owner) and then provides a certification based on the encipher of that data. The system saves the data's access address in the database after data owner uploading his or her data to the system in the data storage schema. Before submitting a data sharing proposal to the DO, every person on the system might validate the quality of shared data. The data sharing mechanism is carried out via a smart contract to incentivize honesty. The schemas assure the security properties of data storage and exchange, which include confidentiality, integrity, privacy, and non-repudiation. © 2022 IEEE.

关键词： Fish

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Underwater and In-Air IPT-CPT Wireless Power Transfer Performance Comparison: A Simulation Study

Underwater and In-Air IPT-CPT Wireless Power Transfer Perfor...

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2023 IEEE International Conference on Environment and Electrical engineering and 2023 IEEE Industrial and Commercial Power systems Europe, EEEIC / I and CPS Europe 2023

作者： Shafiei, Sadjad Yazdi, Seyed Saeid Heidari Kermani, Mostafa Saukhimov, Almaz Hekmati, Arsalan Bagheri, Mehdi Nazarbayev University Dept. of Electrical and Computer Engineering Astana Kazakhstan Sapienza University of Rome Dept. of Electrical Engineering Rome Italy Almaty University of Power Engineering and Telecommunications Dept. of Electrical Systems and Networks Almaty Kazakhstan Revterra Company HoustonTXTX77004 United States

ISBN: (纸本)9798350347432

In this study, an inductive-capacitive coupling wireless power transmission (IC-UWPT) system in the seawater environment is discussed. It is revealed that the conductive characteristic of seawater medium will change the eddy current flow as compared to the air medium, and in higher frequency ranges, will increase power dissipation and affect the total efficiency and ultimately the system's performance. A new equivalent circuit is provided to precisely model the seawater WPT, where the eddy current losses are referred to as an additional term coil's parameter in the circuit model. Using Ansys Electronics, simulation studies are carried out in both air and water environment. The eddy current and electrostatic solutions are adopted for IPT and CPT system analysis. Moreover, Ansys Simplorer is utilized to couple the proposed IPT-CPT combined system. The simulation results validate the introduced model for the underwater IPT -CPT system and its performance. © 2023 IEEE.

关键词： Energy transfer

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