Managing Humidity in Electronics Using Water Vapor-Selective Membranes

Abstract: As outdoor electronics have become prevalent in every aspect of daily life, handling humidity in them is an emerging issue for reliable devices. As water vapor enters the electronics enclosure, there is a risk of condensation, which could prevent the electronics from functioning and further damage the device. Traditionally, the humidity removal for electronics is usually done by heating the air within the enclosure, which can be energy-intensive and less efficient. Vapor selective membrane systems are promising alternatives for air heating dehumidification as they do not require heating energy for water vapor removal. It allows water vapor transport through the membrane while blocking air. The objective of this research in the spring is to design and assemble electronics enclosures with a vapor selective membrane and sensors to monitor the humidity removal progress. Two designs including a vacuum pump and joule pump will be tested. The expected results are testable prototypes and preliminary test data that prove it is possible to accurately monitor the humidity level both inside and outside the enclosure for future testing

Embedded Palmprint Recognition System Using OMAP 3530

We have proposed in this paper an embedded palmprint recognition system using the dual-core OMAP 3530 platform. An improved algorithm based on palm code was proposed first. In this method, a Gabor wavelet is first convolved with the palmprint image to produce a response image, where local binary patterns are then applied to code the relation among the magnitude of wavelet response at the ccentral pixel with that of its neighbors. The method is fully tested using the public PolyU palmprint database. While palm code achieves only about 89% accuracy, over 96% accuracy is achieved by the proposed G-LBP approach. The proposed algorithm was then deployed to the DSP processor of OMAP 3530 and work together with the ARM processor for feature extraction. When complicated algorithms run on the DSP processor, the ARM processor can focus on image capture, user interface and peripheral control. Integrated with an image sensing module and central processing board, the designed device can achieve accurate and real time performance

Atmospheric histories and emissions of chlorofluorocarbons CFC-13 (CClF3), ΣCFC-114 (C2Cl2F4), and CFC-115 (C2ClF5)

Based on observations of the chlorofluorocarbons CFC-13 (chlorotrifluoromethane), ΣCFC-114 (combined measurement of both isomers of dichlorotetrafluoroethane), and CFC-115 (chloropentafluoroethane) in atmospheric and firn samples, we reconstruct records of their tropospheric histories spanning nearly 8 decades. These compounds were measured in polar firn air samples, in ambient air archived in canisters, and in situ at the AGAGE (Advanced Global Atmospheric Gases Experiment) network and affiliated sites. Global emissions to the atmosphere are derived from these observations using an inversion based on a 12-box atmospheric transport model. For CFC-13, we provide the first comprehensive global analysis. This compound increased monotonically from its first appearance in the atmosphere in the late 1950s to a mean global abundance of 3.18 ppt (dry-air mole fraction in parts per trillion, pmol mol1) in 2016. Its growth rate has decreased since the mid-1980s but has remained at a surprisingly high mean level of 0.02 ppt yr⁻¹ since 2000, resulting in a continuing growth of CFC-13 in the atmosphere. ΣCFC-114 increased from its appearance in the 1950s to a maximum of 16.6 ppt in the early 2000s and has since slightly declined to 16.3 ppt in 2016. CFC-115 increased monotonically from its first appearance in the 1960s and reached a global mean mole fraction of 8.49 ppt in 2016. Growth rates of all three compounds over the past years are significantly larger than would be expected from zero emissions. Under the assumption of unchanging lifetimes and atmospheric transport patterns, we derive global emissions from our measurements, which have remained unexpectedly high in recent years: mean yearly emissions for the last decade (2007–2016) of CFC-13 are at 0.48 ± 0.15 kt yr⁻¹ (> 15 % of past peak emissions), of ΣCFC-114 at 1.90 ± 0.84 kt yr⁻¹ (∼ 10 % of peak emissions), and of CFC-115 at 0.80 ± 0.50 kt yr⁻¹(> 5 % of peak emissions). Mean yearly emissions of CFC-115 for 2015–2016 are 1.14 ± 0.50 kt yr⁻¹ and have doubled compared to the 2007–2010 minimum. We find CFC-13 emissions from aluminum smelters but if extrapolated to global emissions, they cannot account for the lingering global emissions determined from the atmospheric observations. We find impurities of CFC-115 in the refrigerant HFC-125 (CHF₂CF₃) but if extrapolated to global emissions, they can neither account for the lingering global CFC-115 emissions determined from the atmospheric observations nor for their recent increases. We also conduct regional inversions for the years 2012–2016 for the northeastern Asian area using observations from the Korean AGAGE site at Gosan and find significant emissions for ΣCFC-114 and CFC-115, suggesting that a large fraction of their global emissions currently occur in northeastern Asia and more specifically on the Chinese mainland

Semantic-Based Requirements Content Management for Cloud Software

Cloud Software is a software complex system whose topology and behavior can evolve dynamically in Cloud-computing environments. Given the unpredictable, dynamic, elasticity, and on-demand nature of the Cloud, it would be unrealistic to assume that traditional software engineering can “cleanly” satisfy the behavioral requirements of Cloud Software. In particular, the majority of traditional requirements managements take document-centric approaches, which have low degree of automation, coarse-grained management, and limited support for requirements modeling activities. Facing the challenges, based on metamodeling frame called RGPS (Role-Goal-Process-Service) international standard, this paper firstly presents a hierarchical framework of semantic-based requirements content management for Cloud Software. And then, it focuses on some of the important management techniques in this framework, such as the native storage scheme, an ordered index with keywords, requirements instances classification based linear conditional random fields (CRFs), and breadth-first search algorithm for associated instances. Finally, a prototype tool called RGPS-RM for semantic-based requirements content management is implemented to provide supporting services for open requirements process of Cloud Software. The proposed framework applied to the Cloud Software development is demonstrated to show the validity and applicability. RGPS-RM also displays effect of fine-grained retrieval and breadth-first search algorithm for associated instance in visualization

One-Step Preparation of Si-Doped Ultra-Long <i>β</i>-Ga₂O₃ Nanowires by Low-Pressure Chemical Vapor Deposition

In this work, we prepared ultra-long Si-doped β-Ga2O3 nanowires on annealed Al2O3-film/Si substrate by low-pressure chemical vapor deposition (LPCVD) assisted by Au as catalyst. The length of nanowires exceeds 300 μm and diameters range from ~30 to ~100 nm in one-dimensional structures. The nanowires show good crystal quality and exhibit (201) orientation, confirmed by transmission electron microscopy and X-ray diffraction analysis. The PL spectrum obtained from these β-Ga2O3 nanowires has three obvious blue luminescence peaks at 398 nm (3.12 eV), 440 nm (2.82 eV), and 492 nm (2.51 eV). The electrical properties obtained from Si-doped β-Ga2O3 nanowires exhibit good conductivity. A metal-semiconductor-metal device is made by using Ti/Au as the electrode, and the device current reaches 200 pA at a bias voltage of 3 V. Our results show that ultra-long Si-doped β-Ga2O3 nanowires can be grown directly on the surface of Al2O3-film/Si substrates. These nanowires have a very high length-diameter ratio and good electrical properties. A possible mechanism for Si doping is also presented

Roadway Surrounding Rock under Multi-Coal-Seam Mining: Deviatoric Stress Evolution and Control Technology

Multi-coal-seam mining creates surrounding rock control difficulties, because the mining of a coal face in one seam can affect coal faces in another. We examine the effects of multi-coal-seam mining on the evolution of the deviatoric stress distribution and plastic zone in the roadway surrounding rock. In particular, we use numerical simulation, theoretical calculation, drilling detection, and mine pressure observation to study the distribution and evolution characteristics of deviatoric stress on Tailgate 8709 in No. 11 coal seam in Jinhuagong mine when the N8707 and N8709 coal faces in No. 7-4 coal seam and the N8707 and N8709 coal faces in No. 11 coal seam are mined. The evolution laws of deviatoric stress and the plastic zone of roadway surrounding rock in the advance and behind sections of the coal face are studied, and a corresponding control technology is proposed. The results show that the peak value of deviatoric stress increases with the advance of the coal face, and the positions of the peak value of deviatoric stress and the plastic zone become deeper. The deflection angle of the peak stress after mining at each coal face and the characteristics of the peak zone of deviatoric stress and the plastic zone of the roadway surrounding rock under the disturbance of multi-coal-seam mining are determined. In conclusion, the damage range in the roadway roof in the solid-coal side and coal pillar is large and must be controlled. A combined support technology based on high-strength and high pretension anchor cables and truss anchor cables is proposed; long anchor cables are used to strengthen the support of the roadway roof in the solid-coal side and coal pillar. The accuracy of the calculated plastic zone range and the reliability of the combined support technology are verified through drilling detection and mine pressure observation on site. This research can provide a point of reference for roadway surrounding rock control under similar conditions