A digital technique for diagnosing interconnect degradation by using digital signal characteristics

Lee, Jun Young; Kwon, Daeil

doi:10.1016/j.mejo.2016.12.008

Cited by 7 publications

(5 citation statements)

References 13 publications

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“…The application of agricultural big data is very wide, mainly in agricultural situation monitoring, agricultural product monitoring and early warning, agricultural decision-making, and the establishment of rural integrated information service system [21,22]. Agricultural situation monitoring is to monitor changes in the farmland environment, crop yields, and natural disasters, and to predict changes in the natural environment such as climate one step in advance.…”

Section: Digital Technologymentioning

confidence: 99%

Digital Technology Boosting Agricultural Supply-Side Constitutive Revolution in Poor Areas Based on the Intelligent Environment of the Internet of Things

Wang

Yang

2022

Wireless Communications and Mobile Computing

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China is a big agricultural country, and China’s agricultural development is related to the development of the country. Especially in poor rural areas, the development of agriculture still stays at low-level manual farming. Therefore, with the help of the developed Internet of Things technology, it is necessary for digital technology to develop and reform the rural areas in poverty-stricken areas. This paper aims to promote the supply-side structural revolution of agriculture in poverty-stricken areas by digital technology based on intelligent environment of Internet of Things. Firstly, the KNN intelligent algorithm is improved to improve the accuracy and reduce the time complexity. Then, based on the data support of Internet of Things technology, a prediction model is built, and the parameters are optimized by particle swarm optimization, and finally the best prediction model with high prediction accuracy, good stability and reduced prediction time complexity is obtained. Taking the source area of the Danjiang River in the South-to-North Water Transfer Project as the research object, the total grain output and soybean production demand in this area from 2010 to 2018 were selected, and the change trend of soybean production and demand in this area from 2019 to 2021 was predicted. The experimental data show that the soybean output in this region has increased year by year, with a cumulative increase of 6,985.4 tons from 2010 to 2018. Soybean output sometimes exceeds demand, and sometimes it is less than demand. There will be an oversupply situation in 2019 and 2021, and an oversupply situation in 2020. Therefore, the prediction model of Internet of Things can effectively predict the supply and demand situation of soybean with an accuracy rate of over 90%, which can provide data support for the decision-making of structural change of agricultural supply side in poverty-stricken areas.

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Section: Digital Technologymentioning

confidence: 99%

Digital Technology Boosting Agricultural Supply-Side Constitutive Revolution in Poor Areas Based on the Intelligent Environment of the Internet of Things

Wang

Yang

2022

Wireless Communications and Mobile Computing

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“…Transitioning to the single particle regime would only further improve our understanding of catalysis and energy efficient chemical synthesis. LNPs may also have potential applications in small scale devices to detect changes in chemical composition or pressure, both of which are signals of device failure. , …”

Section: Engineering Single Particle Nanoscale Sensorsmentioning

confidence: 99%

“…LNPs may also have potential applications in small scale devices to detect changes in chemical composition or pressure, both of which are signals of device failure. 201,202 ■ CONCLUSION AND OUTLOOK Because of the advantageous and unique optical properties of LNPs, it is not surprising that there are many studies identifying and quantifying their sensing properties at the ensemble level. While these ensemble measurements have generated valuable insights into fields from biology to physics, many questions remain that require much more granular sensing capabilities.…”

Section: Sensorsmentioning

confidence: 99%

Lanthanide-Based Nanosensors: Refining Nanoparticle Responsiveness for Single Particle Imaging of Stimuli

et al. 2020

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Lanthanide nanoparticles (LNPs) are promising sensors of chemical, mechanical, and temperature changes; they combine the narrow-spectral emission and long-lived excited states of individual lanthanide ions with the high spatial resolution and controlled energy transfer of nanocrystalline architectures. Despite considerable progress in optimizing LNP brightness and responsiveness for dynamic sensing, detection of stimuli with a spatial resolution approaching that of individual nanoparticles remains an outstanding challenge. Here, we highlight the existing capabilities and outstanding challenges of LNP sensors, en-route to nanometer-scale, single particle sensor resolution. First, we summarize LNP sensor read-outs, including changes in emission wavelength, lifetime, intensity, and spectral ratiometric values that arise from modified energy transfer networks within nanoparticles. Then, we describe the origins of LNP sensor imprecision, including sensitivity to competing conditions, interparticle heterogeneities, such as the concentration and distribution of dopant ions, and measurement noise. Motivated by these sources of signal variance, we describe synthesis characterization feedback loops to inform and improve sensor precision, and introduce noise-equivalent sensitivity as a figure of merit of LNP sensors. Finally, we project the magnitudes of chemical and pressure stimulus resolution achievable with single LNPs at nanoscale resolution. Our perspective provides a roadmap for translating ensemble LNP sensing capabilities to the single particle level, enabling nanometerscale sensing in biology, medicine, and sustainability.

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“…Thus, digital signals can serve as a means for detecting physical degradation of interconnect surfaces based on the skin effect [ 13 , 14 ], which is a phenomenon wherein high-frequency signals accumulate near the surface of a conductor. Yoon et al [ 13 ] presented a diagnosis method for solder joints by monitoring eye parameters, which are sets of parameters obtained from SI analysis.…”

Section: Digital Signal Characteristicsmentioning

confidence: 99%

“…Eye parameters were collected during solder joint degradation testing, and the observed jitters showed significant deviation with the degradation of the solder joints subjected to thermo-mechanical stress conditions. Furthermore, Lee et al [ 14 ] developed a health monitoring system based on eye parameter measurement; in their study, the eye height extracted from the eye diagram showed gradual degradation under an accelerated life test of solder joints, and it was used for anomaly detection of the solder joints.…”

Section: Digital Signal Characteristicsmentioning

confidence: 99%

Development of a Non-Invasive On-Chip Interconnect Health Sensing Method Based on Bit Error Rates

Shin¹,

Koo²,

Kwon³

2018

Sensors

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Electronic products and systems are widely used in industrial network systems, control devices, and data acquisition devices across many industry sectors. Failures of such electronic systems might lead to unexpected downtime, loss of productivity, additional work for repairs, and delay in product and service development. Thus, developing an appropriate sensing technique is necessary, because it is the first step in system fault diagnosis and prognosis. Many sensing techniques often require external and additional sensing devices, which might disturb system operation and consequently increase operating costs. In this study, we present an on-chip health sensing method for non-destructive and non-invasive interconnect degradation detection. Bit error rate (BER), which represents data integrity during digital signal transmission, was selected to sense interconnect health without connecting external sensing devices. To verify the health sensing performance, corrosion tests were conducted with in situ monitoring of the BER and direct current (DC) resistance. The eye size, extracted from the BER measurement, showed the highest separation between the intact and failed interconnect, as well as a gradual transition, compared with abrupt changes in the DC resistance, during interconnect degradation. These experimental results demonstrate the potential of the proposed sensing method for on-chip interconnect health monitoring applications without disturbing system operation.

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A digital technique for diagnosing interconnect degradation by using digital signal characteristics

Cited by 7 publications

References 13 publications

Digital Technology Boosting Agricultural Supply-Side Constitutive Revolution in Poor Areas Based on the Intelligent Environment of the Internet of Things

Digital Technology Boosting Agricultural Supply-Side Constitutive Revolution in Poor Areas Based on the Intelligent Environment of the Internet of Things

Lanthanide-Based Nanosensors: Refining Nanoparticle Responsiveness for Single Particle Imaging of Stimuli

Development of a Non-Invasive On-Chip Interconnect Health Sensing Method Based on Bit Error Rates

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