A Wireless sensor Network (WSN) is a network of devices that transfer all the data collected from the monitoring area via a wireless connection. Data is transmitted over multiple nodes, and the portal connects the nod...
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Despite our commitment and endeavors, vehicle accidents remain one of the biggest causes of death, disability, and hospitalization in the country. India is top among all 199 nations in terms of traffic-related deaths,...
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Biometric identification using smart wearable devices is becoming more popular. They will, however, continue to provide authentication services to the fitness and medical industries. If someone claims to be who they s...
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The proceedings contain 6 papers. The topics discussed include: assessing the performance impact of using an active global address space in HPX: a case for AGAS;sequential codelet model of program execution - a super-...
ISBN:
(纸本)9781728159935
The proceedings contain 6 papers. The topics discussed include: assessing the performance impact of using an active global address space in HPX: a case for AGAS;sequential codelet model of program execution - a super-codelet model based on the hierarchical turing machine;ADVERT: an asynchronous runtime for fine-grained network systems;design and evaluation of shared memory communication benchmarks on emerging architectures using MVAPICH2;characterizing the performance of executing many-tasks on summit;and leveraging network-level parallelism with multiple process-endpoints for MPI broadcast.
Loosely Coupled architectures based on Micro Electromechanical systems (MEMS) Inertial Navigation systems (INS), and multi-band GNSS are widely adopted to improve the availability of the integrated solution under diff...
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ISBN:
(纸本)9798350321876
Loosely Coupled architectures based on Micro Electromechanical systems (MEMS) Inertial Navigation systems (INS), and multi-band GNSS are widely adopted to improve the availability of the integrated solution under difficult conditions, characterized by frequent obscurations of the GNSS signal. Typical scenarios include automotive urban tracks or open sky under dynamics, in presence of bridges and short tunnels. Low Earth Orbit (LEO) satellites also fall in this scope, as their lower altitude results in a Doppler curve with stronger rate variations, which sum up to receiver dynamics and are more challenging to track than traditional GNSS. In this paper, a hybrid solution is presented, where a classic loosely coupled scheme is complemented by deep integration. The INSaided solution combines with GNSS satellites velocities and accelerations to derive code, Doppler, and Doppler rate observables predictions. Validation and performance assessment are conducted on a compact two-chip hardware platform, based on the state-of-the-art multi-band GNSS receiver STA8135 (TeseoV) and the MEMS IMU ASM330LHH from STMicroelectronics. Deep aiding has the potential to broaden the applicability of loosely coupled INS integration to the cases where signal weakness and the combined user to satellites dynamics exceed the tracking loops capability. Partially obscured automotive scenarios, reception of attenuated signals under high dynamics and assisted LEO satellites acquisition and tracking are among the applications that can benefit from the proposed scheme.
The sensor Sharing Marketplace (SenShaMart) enables IoT applications to find IoT sensors, which are owned and managed by other parties, integrate them, and pay for using their data. To provide corresponding services t...
The sensor Sharing Marketplace (SenShaMart) enables IoT applications to find IoT sensors, which are owned and managed by other parties, integrate them, and pay for using their data. To provide corresponding services that implement that FAIR (Findable, Accessible, Interoperable, Reusable) principles of IoT, SenShaMart incorporates a specialized blockchain that manages all the information its services need to allow different parties in IoT to describe, query, integrate, pay for, and use IoT sensors and their data. The paper presents the SenShaMart's architecture, implementation, evaluation, and demonstration.
The rise of the internet-of-things and distributedsensor nodes with machine-learning and edge processing are driving the need for low-power, high-precision ADCs. These highly digital systems are best implemented in a...
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The proceedings contain 16 papers. The topics discussed include: microgrid energy management strategy based on mas;individual thermal comfort prediction based on upper body thermal imaging and computer vision;enhanced...
ISBN:
(纸本)9781665463218
The proceedings contain 16 papers. The topics discussed include: microgrid energy management strategy based on mas;individual thermal comfort prediction based on upper body thermal imaging and computer vision;enhanced whale optimization algorithm for mesh routers placement problem in wireless mesh networks;an efficient genetic algorithm for solving spectrum assignment problem in elastic optical networks;manta ray foraging optimization algorithm for solving the LEDs placement problem in indoor VLC systems;reference design model for a patient-centric data exchange healthcare environment;toward implementing interoperability in pervasive healthcare systems for chronic diseases by decentralization and modularity;eldercare smart home sensor based system: approach, deployment and insights;and machine learning models to predict cardiovascular events from heart rate variability data.
Power factor improvement in Radial Distribution systems (rdS) is done by placing distributed Generation (DG) in the best possible location, this study compares two optimization algorithms: the innovative Fruit Fly Alg...
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ISBN:
(数字)9798331532420
ISBN:
(纸本)9798331532437
Power factor improvement in Radial Distribution systems (rdS) is done by placing distributed Generation (DG) in the best possible location, this study compares two optimization algorithms: the innovative Fruit Fly Algorithm (FFA) and the Bat Algorithm (BA). Materials and Methods: To ascertain the ideal location and size of distributed generators (DGs) inside radial distribution power networks, the Fruit Fly Algorithm and Bat Algorithm are utilized. With a power level of 0.8, the sample size of 14 samples was determined using G*Power for two groups. Results: Based on the data, FFA performs better than BA at raising the Power Factor. The computed significance value of 0.941 (p>0.05) suggests that the difference is not statistically significant. Conclusion: The FFA-based optimization strategy outperforms the BA-based method (0.9089) in terms of Power Factor improvement (0.9132).
In order to realize a "double carbon"goal, it is necessary to further conserve energy and reduce emissions on the power grid. The high proportion of distributed generation dramatically impacts the power syst...
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