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Smart AmbuBag: A Cloud-Based Automated Respiratory Ventilator 13

Smart AmbuBag: A Cloud-Based Automated Respiratory Ventilato...

引用

13th international conference on Information and Communication technology convergence, ICTC 2022

作者： Sampedro, Gabriel Avelino Cobar, Jose Mari Abaja, Keith Daniel Baluis, Ronnie Huyo-A, Shekinah Lor Abisado, Mideth University of the Philippines - Open University Faculty of Information and Communication Studies Los Baños Philippines Research and Development Center Philippine Coding Camp Manila Philippines Technological Institute of the Philippines Computer Engineering Department Quezon City Philippines College of Computing and Information Technologies National University Manila Philippines

ISBN: (数字)9781665499392

ISBN: (纸本)9781665499392

With the Bag-Valve-Mask (commonly known as an AmbuBag or BVM) being widely used to provide emergency ventilation to patients, it is one of the most critical instruments used in the medical industry. As was emphasized in some studies, there is an urgency to implement a resolution to the human error-induced risks posed by the manual BVM. Hence, this study explores how an IoT-Based Automated Valve Mask can aid in resolving accidents born from the use of the manual counterpart. This device aims to propose a solution to the potential root causes of such adverse events in the field. It uses an GSM-based technology to gather the patient's vital signs and the quality of the air. After being tested on both Child and Adult groups, it was remarked that the accuracy rate of the device surpassed 95%. © 2022 IEEE.

关键词： Internet of things

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Interpersonal Communication Analysis Model of Privacy Protection System in the Era of Artificial Intelligence (AI) 14th

Interpersonal Communication Analysis Model of Privacy Protec...

引用

14th international conference on Frontier computing, FC 2024

作者： Wang, Yiming Wu, Wei School of Art Design and Media Shanghai Sanda University Shanghai China Media Convergence Center Youth Daily Shanghai China

ISBN: (纸本)9789819627974

Nowadays, artificial intelligence technology has been widely used, and the way of information dissemination has also undergone revolutionary changes. Personal information is also spreading rapidly under the background of big data, cloud computing and other technologies, which makes privacy protection face new challenges. Based on the above background, this paper puts forward an interpersonal communication analysis model of privacy protection system in the era of artificial intelligence, aiming to understand and improve privacy protection system more deeply. In this model, the source and destination of information dissemination can be accurately and clearly distinguished by constructing interpersonal network;Analyzing the speed of information dissemination can help to determine the speed of information dissemination and provide clues for people to take corresponding measures in an emergency;Analyzing the specific path of information dissemination can enable people to grasp how information is disseminated in the network and the possible risks in the process of dissemination;By considering the factor of privacy sensitivity, different levels of privacy protection can be adopted for different information. By integrating the above elements into the analysis model, a more intelligent and personalized method is provided for the privacy protection system, so as to meet the challenges of privacy protection in the era of artificial intelligence, protect the privacy of users and avoid privacy leakage. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Differential privacy

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Spontaneous Driver Fatigue Discernment System Using Artificial Intelligence 7

Spontaneous Driver Fatigue Discernment System Using Artifici...

引用

7th IEEE international conference for convergence in technology, I2CT 2022

作者： Kumar, Rishabh Agrawal, Meghna Narayan Das, Nripendra Manipal University Jaipur School of Computing and Information Technology Department of Information Technology Rajasthan Jaipur303007 India

ISBN: (纸本)9781665421683

Distracted driving accounts for a large number of road accidents. After drunk driving, drowsiness and distraction is the leading cause for accidents. The motive of this paper is to contribute to a system which uses computer vision techniques of detecting drowsiness in drivers in automobile vehicles to alerting them when they show signs of tiredness for them to avoid falling asleep resulting in prevention of a possible road accident. Facial features are aimed to be monitored for signs of drowsiness, in particular, shutting of eyes. This paper aims draw comparison between different classification models to find the best performing models which can detect drowsy and alert states in humans. Classifiers Logistic Regression, Naïve Bayes, KNN, MLP, Decision Tree, Random Forest, CNN and XGBoost algorithms to classify the test data into either drowsy or normal. The data is split into 20 by 80 ratio where 20% of the dataset is used for testing and the rest 80% for training. Each of the classifiers are then compared for their accuracy in classifying the dataset and the classifier providing us with the highest accuracy is declared. © 2022 IEEE.

关键词： Decision trees

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Next-Generation Technologies Empowered Future IoV 7

Next-Generation Technologies Empowered Future IoV

引用

7th IEEE international conference for convergence in technology, I2CT 2022

作者： Rajasekhar, Kodingari Kumar, Rahul Kiran, M. Rammohana Reddy, G. National Institute of Technology Surathkal Department of Information Technology Karnataka India

ISBN: (纸本)9781665421683

The Internet of Vehicles is a network of connected automobiles that can communicate with one another. In the IoV environment, vehicles and sensors, pedestrians, mobile devices, and networking devices are the primary components;improving road safety, proper guidance while driving, autonomous driving, traffic management, infotainment, and entertainment. But with rapid growth in the number of automobiles, high vehicle mobility and networking devices;it isn't easy to achieve the requirements needed for the operation and management of IoV. Next-generation technologies such as 5th Generation (5G) and Software Defined Network (SDN) technologies can significantly address these challenges. These technologies will provide potential solutions for efficient management, enhance the performance of IoV. In this paper, we performed simulation with these technologies in the real world vehicular network along with performance evaluation. In comparison to traditional vehicle networks, our findings show that 5G and software-defined vehicular networks have a lower transmission delay and higher throughput. © 2022 IEEE.

关键词： Mobile edge computing

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Robust Sub-Kelvin Simulations of Quantum Dot Charge Sensing

Robust Sub-Kelvin Simulations of Quantum Dot Charge Sensing

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international conference on Simulation of Semiconductor Processes and Devices (SISPAD)

作者： Prentki, Raphael J. Fehse, Felix Philippopoulos, Pericles Zhou, Chenyi Guo, Hong Korkusinski, Marek Beaudoin, Felix Nanoacad Technol Inc Montreal PQ Canada McGill Univ Dept Phys Montreal PQ Canada CNR Secur & Disrupt Technol Res Ctr Ottawa ON Canada

ISBN: (纸本)9784863488038

Spin-qubit-based quantum computing technologies commonly involve quantum point contacts (QPCs). Indeed, the conductance quantization exhibited by QPCs may be harnessed for the sensing of the charge in a quantum dot (QD) which may, in turn, be harnessed for spin-qubit characterization and readout. In this work, we report a self-consistent finite-element method (FEM) simulation scheme for QD charge sensing by a QPC in planar semiconductor heterostructures. This scheme fully accounts for the electrostatics, quantum confinement, and quantum transport phenomena that are relevant in semiconductor quantum wells (QWs). Robust sub-Kelvin convergence is achieved partly thanks to an adaptive meshing algorithm for Poisson's equation and partly thanks to the uncertainty principle, which leads to diffuse charge density profiles. To minimize computational burden, we leverage the quasi-separability of the Schrodinger equation in the QW, turning a 3D problem into a set of 1D problems;furthermore, we leverage the subKelvin temperature to reduce the calculation of the QPC's conductance to a single Green's function evaluation. Finally, we report: (A) simulations of the hole density in an AlGaAs-GaAs QW accurately matching experimental data and (B) charge sensing in simulations of realistic QD and QPC devices, thereby demonstrating our simulation scheme's relevance to the modeling of spin qubit technologies.

关键词： Finite-element method (FEM) technology computer-aided design (TCAD) nonequilibrium Green's function (NEGF) formalism sub-Kelvin temperature quantum computing spin qubit quantum dot quantum point contact (QPC)

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Abundance Mapping of Commercial Fisheries Production using K-Means and Forecasting Algorithm in Manila Bay, Philippines 8

Abundance Mapping of Commercial Fisheries Production using K...

引用

8th IEEE international conference for convergence in technology, I2CT 2023

作者： Rasdas, Sherrlyn M. Costales, Jefferson A. Fajardo, Arnel C. Limbago, Jomel S. Technological Institute of the Philippines Manila Manila Philippines National University College of Computing and Information Technologies Manila Philippines Isabela State University-Cauayan Isabela Philippines Cavite State University Naic Cavite Philippines

ISBN: (纸本)9798350334012

Manila Bay is an important aquatic resource in the Philippines. However, the bay's resources have been overfished, polluted, and damaged in recent decades. In this study, the commercial fish species production data in Manila Bay from 2018-2021 were mapped and clustered using the K-Means technique. Moreover, seasonal production and fish production forecasts were performed using the decomposition time series analysis technique and the ARIMA forecasting algorithm, respectively. The results revealed that the top four abundant species in Manila Bay were large head hairtail Trichiurus sp., Devi's anchovy Encrasicholina devisi, Squid, and Common ponyfish Leiognathus equula. The abundance of pelagic fish indicates trophic cascades and overfishing in Manila Bay. Meanwhile, the ARIMA forecast results indicate that there are no significant relationships between the production of different species over time. The findings of this study can be used to inform policy decisions regarding closed and open fishing seasons in Manila Bay. To our knowledge, this is the first study to employ ICT-based solutions for fishery management in the Philippines. © 2023 IEEE.

关键词： Python

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An optimized particle swarm optimization algorithm for turbine torque and generator load parameter identification 19

An optimized particle swarm optimization algorithm for turbi...

引用

19th international conference on Future Networks and Communications, FNC 2024 / 21st international conference on Mobile Systems and Pervasive computing, MobiSPC 2024 / 14th international conference on Sustainable Energy Information technology, SEIT 2024

作者： Yang, Zhangbin Li, Xiaokun Liao, Xiang Peng, Daixiao Cai, Hang He, Xuemin China Three Gorges Construction Engineering Corporation Chengdu610095 China Three Gorges Intelligent Industrial Control Technology Co. Ltd Wuhan430070 China

Hydraulic turbine control system is a complex system with strong nonlinearity and multiple variables. Therefore, in order to better control the turbine system, it is necessary to obtain the parameters of key components. Aiming at the limitation of the traditional particle swarm optimization algorithm in global search ability, mutation operator and dynamic inertia weight coefficient are introduced to enhance the search ability of the algorithm. In addition, in order to further improve the global search performance of the algorithm, this paper combines the optimized particle swarm optimization algorithm with genetic algorithm to form a hybrid parameter identification algorithm. The hybrid algorithm not only uses the fast convergence of particle swarm optimization (PSO), but also uses the global search advantage of genetic algorithm (GA) to realize efficient and accurate identification of turbine torque and load parameters. Through MATLAB2021a/Simulink simulation experiments, the application effect of the algorithm in the identification of turbine torque and generator load parameters is verified. The simulation results show that the optimized particle swarm optimization algorithm has significant advantages in the accuracy and robustness of parameter identification, and the identified parameters have a high degree of fitting with the actual measured torque and speed. This study not only provides a new optimization strategy for the parameter identification of turbine regulation system, but also provides an effective intelligent algorithm solution for the parameter identification of nonlinear system. © 2024 The Authors. Published by Elsevier B.V.

关键词： Genetic algorithms

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Multi-Access Edge computing Implemention On Tower Ecosystem Indonesia: Challenges And Visibility 13

Multi-Access Edge Computing Implemention On Tower Ecosystem ...

引用

13th international conference on Information and Communication technology convergence, ICTC 2022

作者： Budiman, Pratignyo Arif Marfani Sari, Detriana Margita Pt Dayamitra Telekomunikasi Operation and Construction Directorate Jakarta Indonesia Pt Telkomsel Network Architecture and Design Department Jakarta Indonesia Pt Dayamitra Telekomunikasi Operation Support Department Jakarta Indonesia

ISBN: (数字)9781665499392

ISBN: (纸本)9781665499392

Edge computing has emerged as a hot topic in recent years, coinciding with the advancement of 5G implementation. Utilizing multi-access edge computing (MEC), the transmission of mobile data will occur in real time and ultra low latency. Edge computing is required to deliver 5G service. MEC is a cloud computing evolution that moves applications from centralized data centers to the network edge, bringing technology resources closer to end users and their devices. Mitratel, the largest tower provider in one of the most attractive market in the world - Indonesia. It provides nationwide coverage in highly attractive across the country. Moreover, it has aspiration to become the leading operator of mission critical infrastructure to enhance Indonesia's digital future. Now it is expanding to provide full suite of digital infrastructure solution. In the tower ecosystem, Mitratel also offers various support services, such as edge infra solution, tower fiberization, small cell, power-to-tower, and other technologies to help accelerating 5G development and provide access and convenience to cellular service providers throughout Indonesia. Telkomsel is the largest mobile operator in Indonesia with varieties of mobile services and more than 170 million subscribers. Both of them are subsidiaries of Telkom, an Indonesian multinational telecommunication holding group. Mitratel, Telkomsel, and Telkom works together to conduct proof of concept (PoC) of MEC on tower ecosystem Indonesia. Mitratel utilize its BTS Room which functions as a micro edge data center to provide edge infra solution which consist of conditioned room, power, connectivity, Network Monitoring System (NMS) and others supported infrastructures. While, Telkomsel brings mobile virtual networks, edge servers and use cases. Mitratel, Telkomsel, and Telkom have successfully completed the MEC PoC at the Mitratel BTS Room in the GBK (Gelora Bung Karno), Jakarta. This PoC shows that tower ecosystem of Mitratel is reliable to

关键词： 5G mobile communication systems

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Fall Detection based on Interpretation of Important Features with Wrist-Wearable Sensors 22

Fall Detection based on Interpretation of Important Features...

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28th Annual international conference on Mobile computing and Networking (ACM MobiCom)

作者： Kim, Jeong-Kyun Oh, Da-Som Lee, Kangbok Hong, Sang Gi Elect & Telecommun Res Inst Intelligent Convergence Res Lab Daejeon South Korea

ISBN: (纸本)9781450391818

Smartwatches are attracting great industrial attention, and the demand for daily monitoring is increasing. Thus, a method for high fall detection with the smallest data is required to minimize the load on telecommunication. It is difficult to run machine learning on a smartwatch for fall detection, and the data must be transmitted to a mobile phone. Therefore, we propose a method for detecting a fall with few features by detecting important features in the inertial signal acquired from the wristband sensor. We used the FallAllD dataset for evaluation and detected 60 descriptive statistical features from each of the three-axis acceleration and angular velocity. Additionally, important features were detected through SHapley additive exPlanations. The sampling frequency of the inertial signal obtained the highest accuracy of 94% at 120 Hz, with at least 14 important features.

关键词： Fall Wearable SHAP XAI Fall Detection

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An Intelligent Congestion Control Algorithm for computing Power Network 14th

An Intelligent Congestion Control Algorithm for Computing Po...

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14th international conference on Computer Engineering and Networks, CENet 2024

作者： Jin, Ming Li, Yuting Hao, Jiakai Piao, Tiangao Yang, Jing Chen, Jinqian State Grid Beijing Electric Power Company Beijing100031 China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9789819649624

Due to the randomness of traffic in the computing power network and the diversity of paths, congestion is inevitable. When network congestion occurs, it will cause increased queuing delay, low network utilization, resulting in deterioration of application performance. Nowadays, there are many congestion control methods. By continuously adjusting the transmission rate of the end side, the capacity of the incoming network is finally approached as close as possible to the carrying capacity of the network to solve the congestion problem in the network. However, the current mainstream method has the disadvantages of insufficient control precision and is incapable of self-adaptive adjustment. Therefore, it is necessary to propose a new type of intelligent congestion control algorithm based on deep reinforcement learning to achieve more active control capabilities and more precise rate regulation, and to achieve the goals of full bandwidth, low latency, fast convergence, and excellent fairness. Thereby effectively improving the transmission efficiency of the computing power network and ensuring the efficient completion of large-scale distributed computing tasks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Reinforcement learning

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