Investigating established EEG parameter during real-world driving

AbstractIn real life, behavior is influenced by dynamically changing contextual factors and is rarely limited to simple tasks and binary choices. For a meaningful interpretation of brain dynamics underlying more natural cognitive processing in active humans, ecologically valid test scenarios are essential. To understand whether brain dynamics in restricted artificial lab settings reflect the neural activity in complex natural environments, we systematically tested the eventrelated P300 in both settings. We developed an integrative approach comprising an initial P300-study in a highly controlled laboratory set-up and a subsequent validation within a realistic driving scenario. Using a simulated dialog with a speech-based input system, increased P300 amplitudes reflected processing of infrequent and incorrect auditory feedback events in both the laboratory setting and the real world setup. Environmental noise and movement-related activity in the car driving scenario led to higher data rejection rates but revealed no effect on signal-to-noise ratio in theta and alpha frequency band or the amplitudes of the event-related P300. Our results demonstrate the possibility to investigate cognitive functions like context updating in highly adverse driving scenarios and encourage the consideration of more realistic task settings in prospective brain imaging approaches.

Download Full-text

Empirical investigation of wireless sensor network performance in noisy environments

Journal of Engineering Design and Technology ◽

10.1108/jedt-02-2012-0006 ◽

2014 ◽

Vol 12 (1) ◽

pp. 29-38

Author(s):

Silvanus Teneng Kiyang ◽

Robert Van Zyl

Keyword(s):

Ambient Noise ◽

Network Performance ◽

Signal To Noise Ratio ◽

Real Life ◽

Wireless Sensor ◽

Mathematical Tool ◽

Content Type ◽

The Real ◽

Test Platform ◽

Set Up

Purpose – The purpose of this work is to assess the influence of ambient noise on the performance of wireless sensor networks (WSNs) empirically and, based on these findings, develop a mathematical tool to assist technicians to determine the maximum inter-node separation before deploying a new WSN. Design/methodology/approach – A WSN test platform is set up in an electromagnetically shielded environment (RF chamber) to accurately control and quantify the ambient noise level. The test platform is subsequently placed in an operational laboratory to record network performance in typical unshielded spaces. Results from the RF chamber and the real-life environments are analysed. Findings – A minimum signal-to-noise ratio (SNR) at which the network still functions was found to be of the order 30 dB. In the real-life scenarios (machines, telecommunications and computer laboratories), the measured SNR exceeded this minimum value by more than 20 dB. This is due to the low ambient industrial noise levels observed in the 2.4 GHz ISM band for typical environments found at academic institutions. It, therefore, suggests that WSNs are less prone to industrial interferences than anticipated. Originality/value – A predictive mathematical tool is developed that can be used by technicians to determine the maximum inter-node separation before the WSN is deployed. The tool yields reliable results and promises to save installation time.

Download Full-text

Across Edges: Art to Cartography; One Landscape to the Next

Proceedings of the ICA ◽

10.5194/ica-proc-4-98-2021 ◽

2021 ◽

Vol 4 ◽

pp. 1-7

Author(s):

Darren Sears

Keyword(s):

Real World ◽

Landscape Architecture ◽

Real Life ◽

Two Dimensions ◽

Natural Environments ◽

Spatial Relationships ◽

The World ◽

The Individual ◽

Oil Paints

Abstract. Maps have the empowering effect of placing the “world at your fingertips,” compressing portions of it into a more “knowable” form. I find that some places have this map-like character even in real life—natural environments that are sliced by sharp, unexpected edges and contrasts into more accessible and digestible fragments. Over the years I have explored creating maps that heighten these places’ compressed quality but also preserve their immersive aspect.This search led me first to the field of landscape architecture, and then into two dimensions after I realized that creating these idealized places out in real world was mostly a fantasy. I began piecing together travel photographs into abstract photomontages, later reinterpreted in oil paints, that sharpen natural edges and contrasts to depict imaginary places. I then transitioned to watercolors, and toward depicting places not quite as imaginary, using the same fractured style to combine travel-inspired landscapes with bird’s-eye views.Finding the task of painting the individual fragments less engaging than the process of shaping them into compositions, I came to think of these works as maps in terms of both theory and process—in emphasizing the spatial relationships between scenes rather than the individual scenes themselves. My motivation for creating these maps has expanded beyond personal fulfilment to include conveying the fragility of the natural remnants and contrasts that captivate me.

Download Full-text

Neuropsychology in the Real World

Zeitschrift für Neuropsychologie ◽

10.1024/1016-264x/a000139 ◽

2014 ◽

Vol 25 (4) ◽

pp. 233-238 ◽

Cited By ~ 2

Author(s):

Martin Peper ◽

Simone N. Loeffler

Keyword(s):

Neuropsychological Assessment ◽

Real World ◽

Ecological Validity ◽

Real Life ◽

Emotional States ◽

Context Sensitive ◽

Traditional Assessment ◽

Life Data ◽

Real Life Data ◽

Assessment And Treatment

Current ambulatory technologies are highly relevant for neuropsychological assessment and treatment as they provide a gateway to real life data. Ambulatory assessment of cognitive complaints, skills and emotional states in natural contexts provides information that has a greater ecological validity than traditional assessment approaches. This issue presents an overview of current technological and methodological innovations, opportunities, problems and limitations of these methods designed for the context-sensitive measurement of cognitive, emotional and behavioral function. The usefulness of selected ambulatory approaches is demonstrated and their relevance for an ecologically valid neuropsychology is highlighted.

Download Full-text

Overcoming detection loss and noise in squeezing-based optical sensing

npj Quantum Information ◽

10.1038/s41534-021-00407-0 ◽

2021 ◽

Vol 7 (1) ◽

Author(s):

Gaetano Frascella ◽

Sascha Agne ◽

Farid Ya. Khalili ◽

Maria V. Chekhova

Keyword(s):

Shot Noise ◽

Optical Sensing ◽

Detection Efficiency ◽

Signal To Noise Ratio ◽

Real Life ◽

Squeezed States ◽

Squeezed Light ◽

Noise Limit ◽

Imaging And Spectroscopy ◽

Shot Noise Limit

AbstractAmong the known resources of quantum metrology, one of the most practical and efficient is squeezing. Squeezed states of atoms and light improve the sensing of the phase, magnetic field, polarization, mechanical displacement. They promise to considerably increase signal-to-noise ratio in imaging and spectroscopy, and are already used in real-life gravitational-wave detectors. But despite being more robust than other states, they are still very fragile, which narrows the scope of their application. In particular, squeezed states are useless in measurements where the detection is inefficient or the noise is high. Here, we experimentally demonstrate a remedy against loss and noise: strong noiseless amplification before detection. This way, we achieve loss-tolerant operation of an interferometer fed with squeezed and coherent light. With only 50% detection efficiency and with noise exceeding the level of squeezed light more than 50 times, we overcome the shot-noise limit by 6 dB. Sub-shot-noise phase sensitivity survives up to 87% loss. Application of this technique to other types of optical sensing and imaging promises a full use of quantum resources in these fields.

Download Full-text

Dealing with multiple experts and non-stationarity in inverse reinforcement learning: an application to real-life problems

Machine Learning ◽

10.1007/s10994-020-05939-8 ◽

2021 ◽

Author(s):

Amarildo Likmeta ◽

Alberto Maria Metelli ◽

Giorgia Ramponi ◽

Andrea Tirinzoni ◽

Matteo Giuliani ◽

...

Keyword(s):

Reinforcement Learning ◽

Real World ◽

Real Life ◽

User Preferences ◽

Inverse Reinforcement Learning ◽

Water Release ◽

Reward Function ◽

Model Free ◽

Conflicting Objectives ◽

Multiple Experts

AbstractIn real-world applications, inferring the intentions of expert agents (e.g., human operators) can be fundamental to understand how possibly conflicting objectives are managed, helping to interpret the demonstrated behavior. In this paper, we discuss how inverse reinforcement learning (IRL) can be employed to retrieve the reward function implicitly optimized by expert agents acting in real applications. Scaling IRL to real-world cases has proved challenging as typically only a fixed dataset of demonstrations is available and further interactions with the environment are not allowed. For this reason, we resort to a class of truly batch model-free IRL algorithms and we present three application scenarios: (1) the high-level decision-making problem in the highway driving scenario, and (2) inferring the user preferences in a social network (Twitter), and (3) the management of the water release in the Como Lake. For each of these scenarios, we provide formalization, experiments and a discussion to interpret the obtained results.

Download Full-text

Improving the performance of a radio-frequency localization system in adverse outdoor applications

EURASIP Journal on Wireless Communications and Networking ◽

10.1186/s13638-021-02001-6 ◽

2021 ◽

Vol 2021 (1) ◽

Author(s):

Marcelo N. de Sousa ◽

Ricardo Sant’Ana ◽

Rigel P. Fernandes ◽

Julio Cesar Duarte ◽

José A. Apolinário ◽

...

Keyword(s):

Random Forest ◽

Ray Tracing ◽

Real World ◽

Practical Implication ◽

Real Life ◽

Simulated Data ◽

Real Data ◽

Gradient Boosting ◽

Real World Data ◽

Localization Accuracy

AbstractIn outdoor RF localization systems, particularly where line of sight can not be guaranteed or where multipath effects are severe, information about the terrain may improve the position estimate’s performance. Given the difficulties in obtaining real data, a ray-tracing fingerprint is a viable option. Nevertheless, although presenting good simulation results, the performance of systems trained with simulated features only suffer degradation when employed to process real-life data. This work intends to improve the localization accuracy when using ray-tracing fingerprints and a few field data obtained from an adverse environment where a large number of measurements is not an option. We employ a machine learning (ML) algorithm to explore the multipath information. We selected algorithms random forest and gradient boosting; both considered efficient tools in the literature. In a strict simulation scenario (simulated data for training, validating, and testing), we obtained the same good results found in the literature (error around 2 m). In a real-world system (simulated data for training, real data for validating and testing), both ML algorithms resulted in a mean positioning error around 100 ,m. We have also obtained experimental results for noisy (artificially added Gaussian noise) and mismatched (with a null subset of) features. From the simulations carried out in this work, our study revealed that enhancing the ML model with a few real-world data improves localization’s overall performance. From the machine ML algorithms employed herein, we also observed that, under noisy conditions, the random forest algorithm achieved a slightly better result than the gradient boosting algorithm. However, they achieved similar results in a mismatch experiment. This work’s practical implication is that multipath information, once rejected in old localization techniques, now represents a significant source of information whenever we have prior knowledge to train the ML algorithm.

Download Full-text

An Adaptive Game-Based Learning Strategy for Children Road Safety Education and Practice in Virtual Space

Sensors ◽

10.3390/s21113661 ◽

2021 ◽

Vol 21 (11) ◽

pp. 3661

Author(s):

Noman Khan ◽

Khan Muhammad ◽

Tanveer Hussain ◽

Mansoor Nasir ◽

Muhammad Munsif ◽

...

Keyword(s):

Real World ◽

Road Safety ◽

Learning Strategy ◽

Real Life ◽

Safety Training ◽

Virtual Space ◽

Safety Education ◽

Average Output ◽

Training Environment ◽

The Road

Virtual reality (VR) has been widely used as a tool to assist people by letting them learn and simulate situations that are too dangerous and risky to practice in real life, and one of these is road safety training for children. Traditional video- and presentation-based road safety training has average output results as it lacks physical practice and the involvement of children during training, without any practical testing examination to check the learned abilities of a child before their exposure to real-world environments. Therefore, in this paper, we propose a 3D realistic open-ended VR and Kinect sensor-based training setup using the Unity game engine, wherein children are educated and involved in road safety exercises. The proposed system applies the concepts of VR in a game-like setting to let the children learn about traffic rules and practice them in their homes without any risk of being exposed to the outside environment. Thus, with our interactive and immersive training environment, we aim to minimize road accidents involving children and contribute to the generic domain of healthcare. Furthermore, the proposed framework evaluates the overall performance of the students in a virtual environment (VE) to develop their road-awareness skills. To ensure safety, the proposed system has an extra examination layer for children’s abilities evaluation, whereby a child is considered fit for real-world practice in cases where they fulfil certain criteria by achieving set scores. To show the robustness and stability of the proposed system, we conduct four types of subjective activities by involving a group of ten students with average grades in their classes. The experimental results show the positive effect of the proposed system in improving the road crossing behavior of the children.

Download Full-text

A large area diamond-based beam tagging hodoscope for ion therapy monitoring

EPJ Web of Conferences ◽

10.1051/epjconf/201817009005 ◽

2018 ◽

Vol 170 ◽

pp. 09005 ◽

Cited By ~ 4

Author(s):

M.-L. Gallin-Martel ◽

L. Abbassi ◽

A. Bes ◽

G. Bosson ◽

J. Collot ◽

...

Keyword(s):

Detection Efficiency ◽

Signal To Noise Ratio ◽

Therapy Monitoring ◽

Chemical Vapor ◽

X Rays ◽

Reaction Products ◽

Large Area ◽

Position Measurement ◽

Set Up ◽

Good Signal

The MoniDiam project is part of the French national collaboration CLaRyS (Contrôle en Ligne de l’hAdronthérapie par RaYonnements Secondaires) for on-line monitoring of hadron therapy. It relies on the imaging of nuclear reaction products that is related to the ion range. The goal here is to provide large area beam detectors with a high detection efficiency for carbon or proton beams giving time and position measurement at 100 MHz count rates (beam tagging hodoscope). High radiation hardness and intrinsic electronic properties make diamonds reliable and very fast detectors with a good signal to noise ratio. Commercial Chemical Vapor Deposited (CVD) poly-crystalline, heteroepitaxial and monocrystalline diamonds were studied. Their applicability as a particle detector was investigated using α and β radioactive sources, 95 MeV/u carbon ion beams at GANIL and 8.5 keV X-ray photon bunches from ESRF. This facility offers the unique capability of providing a focused (~1 μm) beam in bunches of 100 ps duration, with an almost uniform energy deposition in the irradiated detector volume, therefore mimicking the interaction of single ions. A signal rise time resolution ranging from 20 to 90 ps rms and an energy resolution of 7 to 9% were measured using diamonds with aluminum disk shaped surface metallization. This enabled us to conclude that polycrystalline CVD diamond detectors are good candidates for our beam tagging hodoscope development. Recently, double-side stripped metallized diamonds were tested using the XBIC (X Rays Beam Induced Current) set-up of the ID21 beamline at ESRF which permits us to evaluate the capability of diamond to be used as position sensitive detector. The final detector will consist in a mosaic arrangement of double-side stripped diamond sensors read out by a dedicated fast-integrated electronics of several hundreds of channels.

Download Full-text

Inter-UAV Routing Scheme Testbeds

Drones ◽

10.3390/drones5010002 ◽

2020 ◽

Vol 5 (1) ◽

pp. 2

Author(s):

Georgios Amponis ◽

Thomas Lagkas ◽

Panagiotis Sarigiannidis ◽

Vasileios Vitsas ◽

Panagiotis Fouliras

Keyword(s):

Signal To Noise Ratio ◽

Real Life ◽

Simulation Software ◽

Propagation Models ◽

Routing Schemes ◽

Routing Scheme ◽

Related Information ◽

Efficient Control ◽

Communication Architectures ◽

Scheme Evaluation

With the development of more advanced and efficient control algorithms and communication architectures, UAVs and networks thereof (swarms) now find applications in nearly all possible environments and scenarios. There exist numerous schemes which accommodate routing for such networks, many of which are specifically designed for distinct use-cases. Validation and evaluation of routing schemes is implemented for the most part using simulation software. This approach is however incapable of considering real-life noise, radio propagation models, channel bit error rate and signal-to-noise ratio. Most importantly, existing frameworks or simulation software cannot sense physical-layer related information regarding power consumption which an increasing number of routing protocols utilize as a metric. The work presented in this paper contributes to the analysis of already existing routing scheme evaluation frameworks and testbeds and proposes an efficient, universal and standardized hardware testbed. Additionally, three interface modes aimed at evaluation under different scenarios are provided.

Download Full-text

PALOMAGE, a French real-world cohort of elderly women beyond age 70 with advanced breast cancer receiving palbociclib: Baseline characteristics and safety evaluation.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.1012 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. 1012-1012

Author(s):

Philippe Caillet ◽

Marina Pulido ◽

Etienne Brain ◽

Claire Falandry ◽

Isabelle Desmoulins ◽

...

Keyword(s):

Breast Cancer ◽

Advanced Breast Cancer ◽

Real World ◽

Older Patients ◽

Systemic Treatment ◽

Safety Data ◽

Real Life ◽

Advanced Breast ◽

Baseline Characteristics ◽

Grade 3

1012 Background: Advanced breast cancer (ABC) is common in older patients, resulting from the high incidence of breast cancer beyond age 70. This population is often limited in clinical trials. Endocrine therapy (ET) combined with a CDK4/6 inhibitor is the standard of care in ABC overexpressing hormonal receptors (HR+). Data specific to older patients are scarce in the literature, deserving further research. Methods: PALOMAGE is an ongoing French prospective study evaluating palbociclib (PAL) + ET in real life setting in women aged ≥70 with HR+ HER2- ABC, split in 2 cohorts: ET sensitive patients with no prior systemic treatment for ABC (cohort A), and ET resistant patients and/or with prior systemic treatment for ABC (cohort B). Data collected include clinical characteristics, quality of life (EORTC QLQ-C30 and ELD14) and geriatric description [G8 and Geriatric-COre DatasEt (G-CODE)]. This analysis reports on baseline characteristics and safety data for the whole population. Results: From 10/2018 to 10/2020, 400 and 407 patients were included in cohort A and B, respectively. The median age was 79 years (69-98), 15.1% with an age > 85. ECOG performance status (PS) was ≥2 in 17.9% patients, 68.3% had a G8 score ≤14 suggesting frailty, 32.1% had bone only metastasis, and 44% had visceral disease. 35.8% of patients in cohort B had no prior treatment for ABC. Safety data were available for 787 patients. The median follow-up was 6.7 months (IC95% = 6.1-7.6). At start of treatment, full dose of PAL (125 mg) was used in 76% of the patients: 62.6%, 68.7% and 71.6% of patients aged ≥ 80, those with ECOG PS ≥2 and those with a G8 score ≤14, respectively. In the safety population, 70% had ≥1 adverse event (AE), including 43.1% grade 3/4 AE, and 22.9% ≥ 1 serious AE. Most frequent AE reported were neutropenia (43.2%), anemia (17.5%), asthenia (16.3%) and thrombocytopenia (13.6%). Grade 3/4 neutropenia was observed in 32.3% of patients, with febrile neutropenia in 1.1%. Grade 3/4 AE PAL-related were reported in 40.1%, 31.4% of patients aged < 80, ≥80, respectively. Regarding PAL, 23.4% of patients had a dose reduction and 41.8% had a temporary or permanent discontinuation due to AE. Safety data were similar in both cohorts. Geriatric data and impact on safety will be presented. Conclusions: PALOMAGE is a unique large real-world cohort focusing on older patients treated with PAL in France. These preliminary data do not suggest any new safety signal, matching data derived from PALOMA trials. The occurrence of less grade3/4 AE related to PAL in patients aged 80 and beyond might reflect the 30% decrease of PAL dose upfront. Effectiveness analyses are eagerly awaited. Clinical trial information: EUPAS23012 .

Download Full-text