Noise mitigation for OCDMA system with wavelength/time 2D hybrid code

2014 ◽  
Author(s):  
N. Din Keraf ◽  
S. A. Aljunid ◽  
A. R. Arief ◽  
M. N. Nurol ◽  
M. S. Anuar ◽  
...  
Keyword(s):  
Noise Mitigation ◽  
Hybrid Code

scholarly journals Artificial Neural Network Assisted Error Correction for MLC NAND Flash Memory

Micromachines ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 879
Author(s):  
Ruiquan He ◽  
Haihua Hu ◽  
Chunru Xiong ◽  
Guojun Han
Keyword(s):  
Neural Network ◽  
Error Correction ◽  
Error Detection ◽  
Flash Memory ◽  
Nand Flash ◽  
Data Reliability ◽  
Nand Flash Memory ◽  
Process Technology ◽  
Noise Mitigation ◽  
Memory Channel

The multilevel per cell technology and continued scaling down process technology significantly improves the storage density of NAND flash memory but also brings about a challenge in that data reliability degrades due to the serious noise. To ensure the data reliability, many noise mitigation technologies have been proposed. However, they only mitigate one of the noises of the NAND flash memory channel. In this paper, we consider all the main noises and present a novel neural network-assisted error correction (ANNAEC) scheme to increase the reliability of multi-level cell (MLC) NAND flash memory. To avoid using retention time as an input parameter of the neural network, we propose a relative log-likelihood ratio (LLR) to estimate the actual LLR. Then, we transform the bit detection into a clustering problem and propose to employ a neural network to learn the error characteristics of the NAND flash memory channel. Therefore, the trained neural network has optimized performances of bit error detection. Simulation results show that our proposed scheme can significantly improve the performance of the bit error detection and increase the endurance of NAND flash memory.

Acoustic meta-silencer: Toward enabling ultrawide-band air-permeable noise barrier

2021 ◽  
pp. 107754632110011
Author(s):  
Mohammad Javad Khodaei ◽  
Amin Mehrvarz ◽  
Reza Ghaffarivardavagh ◽  
Nader Jalili
Keyword(s):  
Heat Transfer ◽  
Design Methodology ◽  
Heat Transfer Performance ◽  
Transmission Loss ◽  
Design Parameters ◽  
Transfer Performance ◽  
Noise Mitigation ◽  
Acoustic Cavity ◽  
Road Map ◽  
Noise Barrier

In this article, we have first presented a metasurface design methodology by coupling the acoustic cavity to the coiled channel. The geometrical design parameters in this structure are subsequently studied both analytically and numerically to identify a road map for silencer design. Next, upon tuning the design parameters, we have introduced an air-permeable noise barrier capable of sound silencing in the ultrawide band of the frequency. It is has been shown that the presented metasurface can achieve +10 dB sound transmission loss from 170 Hz to 1330 Hz (≈3 octaves). Furthermore, we have numerically studied the ventilation and heat transfer performance of the designed metasurface. Enabling noise mitigation by leveraging the proposed metasurface opens up new possibilities ranging from residential and office noise reduction to enabling ultralow noise fan, propellers, and machinery.

scholarly journals Rejuvenation Mechanism of Asphalt Mixtures Modified with Crumb Rubber

CivilEng ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 370-384
Author(s):  
Hossein Noorvand ◽  
Kamil Kaloush ◽  
Jose Medina ◽  
Shane Underwood
Keyword(s):  
Tensile Strength ◽  
Dynamic Loading ◽  
Creep Compliance ◽  
Asphalt Mixture ◽  
Crumb Rubber ◽  
Indirect Tensile Strength ◽  
Laboratory Evaluation ◽  
Strength Testing ◽  
Noise Mitigation ◽  
Indirect Tensile

Asphalt aging is one of the main factors causing asphalt pavements deterioration. Previous studies reported on some aging benefits of asphalt rubber mixtures through laboratory evaluation. A field observation of various pavement sections of crumb rubber modified asphalt friction courses (ARFC) in the Phoenix, Arizona area indicated an interesting pattern of transverse/reflective cracking. These ARFC courses were placed several years ago on existing jointed plain concrete pavements for highway noise mitigation. Over the years, the shoulders had very noticeable and extensive cracking over the joints; however, the driving lanes of the pavement showed less cracking formation in severity and extent. The issue with this phenomenon is that widely adopted theories that stem from continuum mechanics of materials and layered mechanics of pavement systems cannot directly explain this phenomenon. One hypothesis could be that traffic loads continually manipulate the pavement over time, which causes some maltenes (oils and resins) compounds absorbed in the crumb rubber particles to migrate out leading to rejuvenation of the mastic in the asphalt mixture. To investigate the validity of such a hypothesis, an experimental laboratory testing was undertaken to condition samples with and without dynamic loads at high temperatures. This was followed by creep compliance and indirect tensile strength testing. The results showed the higher creep for samples aged with dynamic loading compared to those aged without loading. Higher creep compliance was attributed to higher flexibility of samples due to the rejuvenation of the maltenes. This was also supported by the higher fracture energy results obtained for samples conditioned with dynamic loading from indirect tensile strength testing.

scholarly journals Enhanced Bug Prediction in JavaScript Programs with Hybrid Call-Graph Based Invocation Metrics

Technologies ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 3
Author(s):  
Gábor Antal ◽  
Zoltán Tóth ◽  
Péter Hegedűs ◽  
Rudolf Ferenc
Keyword(s):  
Software Maintenance ◽  
Positive Impact ◽  
Source Code ◽  
Code Analysis ◽  
Static Source ◽  
Static Code Analysis ◽  
Function Calls ◽  
Hybrid Code ◽  
Code Metrics ◽  
Scripting Language

Bug prediction aims at finding source code elements in a software system that are likely to contain defects. Being aware of the most error-prone parts of the program, one can efficiently allocate the limited amount of testing and code review resources. Therefore, bug prediction can support software maintenance and evolution to a great extent. In this paper, we propose a function level JavaScript bug prediction model based on static source code metrics with the addition of a hybrid (static and dynamic) code analysis based metric of the number of incoming and outgoing function calls (HNII and HNOI). Our motivation for this is that JavaScript is a highly dynamic scripting language for which static code analysis might be very imprecise; therefore, using a purely static source code features for bug prediction might not be enough. Based on a study where we extracted 824 buggy and 1943 non-buggy functions from the publicly available BugsJS dataset for the ESLint JavaScript project, we can confirm the positive impact of hybrid code metrics on the prediction performance of the ML models. Depending on the ML algorithm, applied hyper-parameters, and target measures we consider, hybrid invocation metrics bring a 2–10% increase in model performances (i.e., precision, recall, F-measure). Interestingly, replacing static NOI and NII metrics with their hybrid counterparts HNOI and HNII in itself improves model performances; however, using them all together yields the best results.

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