scholarly journals Prediction of the EM signal delay in the ionosphere using neural model

2019 ◽  
Vol 32 (2) ◽  
pp. 287-302
Author(s):  
Zoran Stankovic ◽  
Nebojsa Doncov
Keyword(s):  
Time Delay ◽  
Geographic Location ◽  
Neural Model ◽  
Signal Propagation ◽  
Propagation Delay ◽  
Propagation Path ◽  
Electromagnetic Signal ◽  
Signal Delay ◽  
Proposed Model ◽  
Global Positioning

Neural model capable to accurately and efficiently predict a propagation delay of electromagnetic signal in the ionosphere is proposed in this paper. The model performs this prediction for a given geographic location in Europe between 40?(N) and 70?(N) latitude and 10?(W) and 30?(E) longitude, according to the following parameters: particular day in a year, time during the day and frequency of a signal carrier. Architecture of the model consists of four multilayer perceptron (MLP) networks with the task to estimate, for the known values of the previously mentioned input parameters of the model, the approximate value of free ions concentration in the atmosphere along the signal propagation path above the geographic location of the receiver. Based on the estimated ions concentration and taking into account the considered frequency of the signal carrier, the model calculates the time delay of signal propagation in the ionosphere. The developed neural model is applicable on the whole territory of Republic of Serbia, for all four weather seasons in the period of low solar activity. The results of using the proposed model for the prediction of time delay of the GPS (Global Positioning System) signal in the area of city of Nis are provided in the paper.

scholarly journals DPFFs:C2MOSDirect Path Flip-Flops for Process-Resilient Ultradynamic Voltage Scaling

2016 ◽  
Vol 2016 ◽  
pp. 1-10
Author(s):  
Myeong-Eun Hwang ◽  
Sungoh Kwon
Keyword(s):  
Load Condition ◽  
Signal Propagation ◽  
Propagation Delay ◽  
Propagation Path ◽  
Direct Connection ◽  
Standard Cell ◽  
Direct Path ◽  
Output Load ◽  
Adaptive Body Bias ◽  
Signal Propagation Path

We propose two master-slave flip-flops (FFs) that utilize the clocked CMOS (C2MOS) technique with an internal direct connection along the main signal propagation path between the master and slave latches and adopt an adaptive body bias technique to improve circuit robustness.C2MOSstructure improves the setup margin and robustness while providing full compatibility with the standard cell characterization flow. Further, the direct path shortens the logic depth and thus speeds up signal propagation, which can be optimized for less power and smaller area. Measurements from test circuits fabricated in 130 nm technology show that the proposed FF operates down to 60 mV, consuming 24.7 pW while improving the propagation delay, dynamic power, and leakage by 22%, 9%, and 13%, respectively, compared with conventional FFs at the iso-output-load condition. The proposed FFs are integrated into an8×8FIR filter which successfully operates all the way down to 85 mV.

Evaluation of EGNOS Tropospheric Delay Model in South-Eastern Europe

2009 ◽  
Vol 62 (2) ◽  
pp. 341-349 ◽  
Author(s):  
Tomislav Kos ◽  
Maja Botincan ◽  
Ivan Markezic
Keyword(s):  
Real Time ◽  
Meteorological Parameters ◽  
Prediction Models ◽  
Signal Propagation ◽  
Electromagnetic Signal ◽  
Tropospheric Delay ◽  
Delay Model ◽  
Signal Delay ◽  
One Year ◽  
Delay Prediction

The troposphere affects electromagnetic signal propagation causing signal path bending and the alteration of the electromagnetic wave velocity. Tropospheric delay can introduce a considerable error in satellite positioning if it is not properly estimated. The GPS signal delay can vary from 2 to 20 m depending on the elevation angles between the receiver and the satellite. Two basic types of delay prediction models exist. The first use surface meteorological parameters to estimate the value of the tropospheric delay, and the other models that do not require real-time meteorological input use average and seasonal variation data related to the receiver's latitude and day-of-year. This paper compares the performance of both types of model over a period of one year, comprising all seasons, to verify their accuracy over a longer period. The Saastamoinen model, known as one of the best performing prediction models, was taken as a reference and the global EGNOS model was used to check how the global estimates of the yearly averages of the meteorological parameters and their related seasonal variations comply with the real-time surface parameters.

Hybrid Deep Neural Model for Duplicate Question Detection in Transliterated Bi-lingual Data

2019 ◽  
Vol 12 ◽  
Author(s):  
Seema Rani ◽  
Avadhesh Kumar ◽  
Naresh Kumar
Keyword(s):  
Question Answering ◽  
Neural Model ◽  
Manhattan Distance ◽  
Semantic Matching ◽  
English Only ◽  
Detection Model ◽  
Proposed Model ◽  
Reported Study ◽  
Social Media Platforms ◽  
Efficient Information

Background: Duplicate content often corrupts the filtering mechanism in online question answering. Moreover, as users are usually more comfortable conversing in their native language questions, transliteration adds to the challenges in detecting duplicate questions. This compromises with the response time and increases the answer overload. Thus, it has now become crucial to build clever, intelligent and semantic filters which semantically match linguistically disparate questions. Objective: Most of the research on duplicate question detection has been done on mono-lingual, majorly English Q&A platforms. The aim is to build a model which extends the cognitive capabilities of machines to interpret, comprehend and learn features for semantic matching in transliterated bi-lingual Hinglish (Hindi + English) data acquired from different Q&A platforms. Method: In the proposed DQDHinglish (Duplicate Question Detection) Model, firstly language transformation (transliteration & translation) is done to convert the bi-lingual transliterated question into a mono-lingual English only text. Next a hybrid of Siamese neural network containing two identical Long-term-Short-memory (LSTM) models and Multi-layer perceptron network is proposed to detect semantically similar question pairs. Manhattan distance function is used as the similarity measure. Result: A dataset was prepared by scrapping 100 question pairs from various social media platforms, such as Quora and TripAdvisor. The performance of the proposed model on the basis of accuracy and F-score. The proposed DQDHinglish achieves a validation accuracy of 82.40%. Conclusion: A deep neural model was introduced to find semantic match between English question and a Hinglish (Hindi + English) question such that similar intent questions can be combined to enable fast and efficient information processing and delivery. A dataset was created and the proposed model was evaluated on the basis of performance accuracy. To the best of our knowledge, this work is the first reported study on transliterated Hinglish semantic question matching.

scholarly journals Joint UAV channel modeling and power control for 5G IoT networks

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Xiuhua Fu ◽  
Tian Ding ◽  
Rongqun Peng ◽  
Cong Liu ◽  
Mohamed Cheriet
Keyword(s):  
Energy Efficiency ◽  
Power Control ◽  
Channel Model ◽  
Path Loss ◽  
Channel Modeling ◽  
Signal Propagation ◽  
Spectrum Efficiency ◽  
Propagation Path ◽  
Control Factor ◽  
The Impact

AbstractThis paper studies the communication problem between UAVs and cellular base stations in a 5G IoT scenario where multiple UAVs work together. We are dedicated to the uplink channel modeling and the performance analysis of the uplink transmission. In the channel model, we consider the impact of 3D distance and multi-UAVs reflection on wireless signal propagation. The 3D distance is used to calculate the path loss, which can better reflect the actual path loss. The power control factor is used to adjust the UAV's uplink transmit power to compensate for different propagation path losses, so as to achieve precise power control. This paper proposes a binary exponential power control algorithm suitable for 5G networked UAV transmitters and presents the entire power control process including the open-loop phase and the closed-loop phase. The effects of power control factors on coverage probability, spectrum efficiency and energy efficiency under different 3D distances are simulated and analyzed. The results show that the optimal power control factor can be found from the point of view of energy efficiency.

ACCURATE ANALYSIS OF GLOBAL INTERCONNECTS IN NANO-FPGAs

NANO ◽  
2009 ◽  
Vol 04 (03) ◽  
pp. 171-176 ◽  
Author(s):  
DAVOOD FATHI ◽  
BEHJAT FOROUZANDEH
Keyword(s):  
Propagation Delay ◽  
Modeling Method ◽  
Accurate Analysis ◽  
Proposed Model ◽  
Simulation Results ◽  
The Difference ◽  
A New Technique ◽  
Global Interconnects ◽  
Technology Nodes ◽  
Model Technique

This paper introduces a new technique for analyzing the behavior of global interconnects in FPGAs, for nanoscale technologies. Using this new enhanced modeling method, new enhanced accurate expressions for calculating the propagation delay of global interconnects in nano-FPGAs have been derived. In order to verify the proposed model, we have performed the delay simulations in 45 nm, 65 nm, 90 nm, and 130 nm technology nodes, with our modeling method and the conventional Pi-model technique. Then, the results obtained from these two methods have been compared with HSPICE simulation results. The obtained results show a better match in the propagation delay computations for global interconnects between our proposed model and HSPICE simulations, with respect to the conventional techniques such as Pi-model. According to the obtained results, the difference between our model and HSPICE simulations in the mentioned technology nodes is (0.29–22.92)%, whereas this difference is (11.13–38.29)% for another model.

scholarly journals Blockchain Network Propagation Mechanism Based on P4P Architecture

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Junjie Huang ◽  
Liang Tan ◽  
Sun Mao ◽  
Keping Yu
Keyword(s):  
Propagation Speed ◽  
Propagation Delay ◽  
Propagation Path ◽  
Propagation Mechanism ◽  
Internet Service ◽  
Network Provider ◽  
Network Propagation ◽  
System Overhead ◽  
Message Propagation

Blockchain is a mainstream technology in which many untrustworthy nodes work together to maintain a distributed ledger with advantages such as decentralization, traceability, and tamper-proof. The network layer communication mechanism in its architecture is the core of the networking method, message propagation, and data verification among blockchain nodes, which is the basis to ensure blockchain’s performance and key features. When blocks are propagated in peer-to-peer (P2P) networks with gossip protocol, the high propagation delay of the protocol itself reduces the propagation speed of the blocks, which is prone to the chain forking phenomenon and causes double payment attacks. To accelerate the propagation speed and reduce the fork probability, this paper proposes a blockchain network propagation mechanism based on proactive network provider participation for P2P (P4P) architecture. This mechanism first obtains the information of network topology and link status in a region based on the internet service provider (ISP), then it calculates the shortest path and link overhead of peer nodes using P4P technology, prioritizes the nodes with good local bandwidth conditions for transmission, realizes the optimization of node connections, improves the quality of service (QoS) and quality of experience (QoE) of blockchain networks, and enables blockchain nodes to exchange blocks and transactions through the secure propagation path. Simulation experiments show that the proposed propagation mechanism outperforms the original propagation mechanism of the blockchain network in terms of system overhead, rate of data success transmission, routing hops, and propagation delay.

scholarly journals Propagation of cortical activity via open-loop intrathalamic architectures: a computational analysis

2019 ◽  
Author(s):  
Jeffrey W. Brown ◽  
Aynaz Taheri ◽  
Robert V. Kenyon ◽  
Tanya Berger-Wolf ◽  
Daniel A. Llano
Keyword(s):  
Closed Loop ◽  
Neural Model ◽  
Signal Propagation ◽  
Open Loop ◽  
Thalamic Reticular Nucleus ◽  
Oscillatory Activity ◽  
Reticular Nucleus ◽  
Dorsal Thalamus ◽  
In Series ◽  
Intracortical Connectivity

AbstractPropagation of signals across the cerebral cortex is a core component of many cognitive processes and is generally thought to be mediated by direct intracortical connectivity. The thalamus, by contrast, is considered to be devoid of internal connections and organized as a collection of parallel inputs to the cortex. Here, we provide evidence that “open-loop” intrathalamic connections involving the thalamic reticular nucleus (TRN) can support propagation of oscillatory activity across the cortex. Recent studies support the existence of open-loop thalamo-reticulo-thalamic (TC-TRN-TC) synaptic motifs in addition to traditional closed-loop architectures. We hypothesized that open-loop structural modules, when connected in series, might underlie thalamic and, therefore cortical, signal propagation. Using a supercomputing platform to simulate thousands of permutations of a thalamo-reticular-cortical network and allowing select synapses to vary both by class and individually, we evaluated the relative capacities of closed- and open-loop TC-TRN-TC synaptic configurations to support both propagation and oscillation. We observed that 1) signal propagation was best supported in networks possessing strong open-loop TC-TRN-TC connectivity; 2) intrareticular synapses were neither primary substrates of propagation nor oscillation; and 3) heterogeneous synaptic networks supported more robust propagation of oscillation than their homogeneous counterparts. These findings suggest that open-loop heterogeneous intrathalamic architectures complement direct intracortical connectivity to facilitate cortical signal propagation.Significance StatementInteractions between the dorsal thalamus and thalamic reticular nucleus (TRN) are speculated to contribute to phenomena such as arousal, attention, sleep, and seizures. Despite the importance of the TRN, the synaptic microarchitectures forming the basis for dorsal thalamus-TRN interactions are not fully understood. The computational neural model we present incorporates “open-loop” thalamo-reticular-thalamic (TC-TRN-TC) synaptic motifs, which have been experimentally observed. We elucidate how open-loop motifs possess the capacity to shape the propagative properties of signals intrinsic to the thalamus and evaluate the wave dynamics they support relative to closed-loop TC-TRN-TC pathways and intrareticular synaptic connections. Our model also generates predictions regarding how different spatial distributions of reticulothalamic and intrareticular synapses affect these signaling properties.

Design of Equivalent Sampling Based on Printed Circuit Board Suited for Power Communication System

2013 ◽  
Vol 333-335 ◽  
pp. 465-471
Author(s):  
Chuan Liu ◽  
Zhi Chao Huang ◽  
Peng Wu ◽  
Lei Chen ◽  
Wei Wang
Keyword(s):  
Time Delay ◽  
Communication System ◽  
High Speed ◽  
Printed Circuit Board ◽  
Circuit Board ◽  
Transmission Time ◽  
Clock Signal ◽  
Signal Delay ◽  
Printed Circuit ◽  
Sequential Logic

Many applications in Power communication system have a demand of adjustable transmission time delay of high-speed signal. In sequential logic circuit, the control of transmission time delay of high-speed signal can effectively improve the accuracy of clock sampling, as a result, satisfy the constraints between clock signal and periodic data. A method of equivalent sampling based on printed circuit board (PCB) is provided in the article, it realizes equivalent sampling of the data by fixing a group of clock signal delay, thus, increase the accuracy of sampling.

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