Mixing height determination by ceilometer

International audienceA novel method for estimating the mixing height based on ceilometer measurements is described and tested against commonly used methods for determining mixing height. In this method an idealised backscatter profile is fitted to the observed backscatter profile. The mixing height is one of the idealised backscatter profile parameters. An extensive amount of ceilometer data and vertical soundings data from the Helsinki area in 2002 is utilized to test the applicability of the ceilometer for mixing height determination. The results, including 71 convective and 38 stable cases, show that in clear sky conditions the mixing heights determined from ceilometer based aerosol profiles and BL-height estimates based on sounding data are in a good agreement. Rejected outlier cases corresponded to very low aerosol concentrations in the mixed layer leading to a very weak aerosol backscatter signal in the lowest layer

Modeling phosphorus diffusion gettering of iron in single crystal silicon

We propose a quantitative model for phosphorus diffusion gettering (PDG) of iron in silicon, which is based on a special fitting procedure to experimental data. We discuss the possibilities of the underlying physics of the segregation coefficient. Finally, we show that the proposed PDG model allows quantitative analysis of gettering efficiency of iron at various processing conditions.Peer reviewe

Interaction between clients and physiotherapists in group exercise classes in geriatric rehabilitation

The aim of this paper is to explore how older people construct their interaction in group exercise classes in geriatric rehabilitation and what is their contribution to the interaction. Discourse analysis was employed and data, consisting of seven videotaped group-based exercise sessions, were collected from 52 older people (aged 66–93 years) and nine rehabilitation professionals in seven rehabilitation centres. Four discourse categories were found. In “taciturn exercising”, older people remained verbally silent but physically active. In “submissive disagreeing”, older people opposed the professionals’ agenda by displaying reluctant consent to proposals. In “resilient endeavouring”, older adults persisted on their course of action, regardless of the disapproval of the professionals. In “lay helping”, older people initiated spontaneous encouragement, but also gave verbal and physical assistance to their peers. Older people's meaningful contribution to interaction, whilst it may challenge the institutional flow of activities, can constitute an integral part of the re-ablement process of rehabilitation

Modeling boron diffusion gettering of iron in silicon solar cells

In this paper, a model is presented for boron diffusion gettering of iron in silicon during thermal processing. In the model, both the segregation of iron due to high boron doping concentration and heterogeneous precipitation of iron to the surface of the wafer are taken into account. It is shown, by comparing simulated results with experimental ones, that this model can be used to estimate boron diffusion gettering efficiency of iron under a variety of processing conditions. Finally, the application of the model to phosphorus diffusion gettering is discussed.Peer reviewe

Ownership and governance of Finnish infrastructure networks

This research report investigates and analyzes the pros and cons of different ownership and governance models of infrastructure networks. The report covers most infrastructure networks: transportation networks (roads, streets, railways, airports, harbors) and utility networks (water and sewage, energy and electricity). There is no unifying solution that would fit all sectors in terms of the most efficient ownership model. However, in many sectors reforms are needed towards more elaborated client-supplier frameworks to ensure greater efficiency and cost transparency. Surprisingly, traditional organizational structures do not seem to impact on financial returns of those networks that provide user-financed services. In Finland technical infrastructure networks are typically owned, administered and managed by the public sector as they are considered public goods and critical assets for the wellbeing of citizens. In many ways the sectors have remained passive and with little interaction towards more innovative service provision solutions or organizational models. In terms of developing the networks’ services and their profitability, the greatest business opportunity would result from allowing open entry to market and competition in contracting. This would mean abandonment of negotiated contracts and proactive evolution of functional markets. The scope of business opportunities will increase in all aspect of service delivery; from management to engineering and economic studies, asset management systems, construction and maintenance works, and the labor to do all that

HybridDeepRx: Deep Learning Receiver for High-EVM Signals

In this paper, we propose a machine learning (ML) based physical layer receiver solution for demodulating OFDM signals that are subject to a high level of nonlinear distortion. Specifically, a novel deep learning based convolutional neural network receiver is devised, containing layers in both time- and frequency domains, allowing to demodulate and decode the transmitted bits reliably despite the high error vector magnitude (EVM) in the transmit signal. Extensive set of numerical results is provided, in the context of 5G NR uplink incorporating also measured terminal power amplifier characteristics. The obtained results show that the proposed receiver system is able to clearly outperform classical linear receivers as well as existing ML receiver approaches, especially when the EVM is high in comparison with modulation order. The proposed ML receiver can thus facilitate pushing the terminal power amplifier (PA) systems deeper into saturation, and thereon improve the terminal power-efficiency, radiated power and network coverage.Comment: To be presented in the 2021 IEEE International Symposium on Personal, Indoor and Mobile Radio Communication

Towards Modeling Privacy in WiFi Fingerprinting Indoor Localization and its Application

In this paper, we study privacy models for privacy-preserving WiFi fingerprint based indoor local- ization (PPIL) schemes. We show that many existing models are insufficient and make unrealistic assumptions regarding adversaries’ power. To cover the state-of-the-art practical attacks, we propose the first formal security model which formulates the security goals of both client-side and server-side privacy beyond the curious-but-honest setting. In particular, our model considers various malicious behaviors such as exposing secrets of principles, choosing malicious WiFi fingerprints in location queries, and specifying the location area of a target client. Furthermore, we formulate the client-side privacy in an indistinguishability manner where an adversary is required to distinguish a client’s real location from a random one. The server-side privacy requires that adversaries cannot generate a fab- ricate database which provides a similar function to the real database of the server. In particular, we formally define the similarity between databases with a ball approach that has not been formalized before. We show the validity and applicability of our model by applying it to analyze the security of an existing PPIL protocol. We also design experiments to test the server-privacy in the presence of database leakage, based on a candidate server-privacy attack.Peer reviewe

Quality control and beam test of GEM detectors for future upgrades of the CMS muon high rate region at the LHC

Gas Electron Multipliers (GEM) are a proven position sensitive gas detector technology which nowadays is becoming more widely used in High Energy Physics. GEMs offer an excellent spatial resolution and a high particle rate capability, with a close to 100% detection efficiency. In view of the high luminosity phase of the CERN Large Hadron Collider, these aforementioned features make GEMs suitable candidates for the future upgrades of the Compact Muon Solenoid (CMS) detector. In particular, the CMS GEM Collaboration proposes to cover the high-eta region of the muon system with large-area triple-GEM detectors, which have the ability to provide robust and redundant tracking and triggering functions. In this contribution, after a general introduction and overview of the project, the construction of full-size trapezoidal triple-GEM prototypes will be described in more detail. The procedures for the quality control of the GEM foils, including gain uniformity measurements with an x-ray source will be presented. In the past few years, several CMS triple-GEM prototype detectors were operated with test beams at the CERN SPS. The results of these test beam campaigns will be summarised

Detection of Impaired OFDM Waveforms Using Deep Learning Receiver

With wireless networks evolving towards mmWave and sub-THz frequency bands, hardware impairments such as IQ imbalance, phase noise (PN) and power amplifier (PA) nonlinear distortion are increasingly critical implementation challenges. In this paper, we describe deep learning based physical-layer receiver solution, with neural network layers in both time- and frequency-domain, to efficiently demodulate OFDM signals under coexisting IQ, PN and PA impairments. 5G NR standard-compliant numerical results are provided at 28 GHz band to assess the receiver performance, demonstrating excellent robustness against varying impairment levels when properly trained.acceptedVersionPeer reviewe