Window In Space Research Articles

Adaptive window space direction laser speckle contrast imaging to improve vascular visualization.

Vascular visualization is crucial in monitoring, diagnosing, and treating vascular diseases. Laser speckle contrast imaging (LSCI) is widely used for imaging blood flow in shallow or exposed vessels. However, traditional contrast computation using a fixed-sized sliding window introduces noise. In this paper, we propose dividing the laser speckle contrast image into regions and using the variance criterion to extract pixels more suitable for the corresponding regions for calculation, and changing the shape and size of the analysis window at the vascular boundary regions. Our results show that this method has a higher noise reduction and better image quality in deeper vessel imaging, revealing more microvascular structure information.

An Aftershock Deletion Method Based on Fault Buffer Zone

The existence of aftershocks in an earthquake sequence can impact the analysis of the mainshock. In this study, we present a method for deleting an aftershock sequence based on the spatial relationship between earthquakes and faults. This method improves the performance of space window selection in the classical K-K method by eliminating aftershocks with an ideal fault buffer zone. The determination of fault buffer zones is based on a trial-and-error analysis of 69,714 earthquake records from the China Seismic Network Center (CENC) collected between 1980 and 2020. We selected 20 typical big earthquakes (ML7.0–8.0 or ~Ms6.6–8.0; for earthquakes above magnitude Ms7 or ML7.2, ML is approximately equal to Ms) as the mainshocks to establish the fault buffer zones. We also propose an empirical formula to determine the distance of the fault buffer zone by counting the aftershock deletion effect at different buffer distances. Compared with the classical K-K method, our method considers the correlation between the spatial distribution of aftershocks and faults, eliminates earthquake groups that are not related to the mainshock, greatly reduces the spatial range of aftershocks, improves the performance of deleting aftershocks of different magnitudes, and provides a new rule and reference for aftershock deletion.

Rainfall Prediction Rate in Saudi Arabia Using Improved Machine Learning Techniques

Every farmer requires access to rainfall prediction (RP) to continue their exploration of harvest yield. The proper use of water assets, the successful collection of water, and the successful pre-growth of water construction all depend on an accurate assessment of rainfall. The prediction of heavy rain and the provision of information regarding natural catastrophes are two of the most challenging factors in this regard. In the twentieth century, RP was the most methodically and technically complicated issue worldwide. Weather prediction may be used to calculate and analyse the behaviour of weather with unique features and to determine rainfall patterns at an exact locale. To this end, a variety of methodologies have been used to determine the rainfall intensity in Saudi Arabia. The classification methods of data mining (DM) approaches that estimate rainfall both numerically and categorically can be used to achieve RP. This study, which used DM approaches, achieved greater accuracy in RP than conventional statistical methods. This study was conducted to test the efficacy of several machine learning (ML) approaches for forecasting rainfall, utilising southern Saudi Arabia’s historical weather data obtained from the live database that comprises various meteorological data variables. Accurate crop yield predictions are crucial and would undoubtedly assist farmers. While engineers have developed analysis systems whose performance relies on several connected factors, these methods are seldom used despite their potential for precise crop yield forecasts. For this reason, agricultural forecasting should make use of these methods. The impact of drought on crop yield can be difficult to forecast and there is a need for careful preparation regarding crop choice, planting window, harvest motive, and storage space. In this study, the relevant characteristics required to predict precipitation were identified and the ML approach utilised is an innovative classification method that can be used determine whether the predicted rainfall will be regular or heavy. The outcomes of several different methodologies, including accuracy, error, recall, F-measure, RMSE, and MAE, are used to evaluate the performance metrics. Based on this evaluation, it is determined that DT provides the highest level of accuracy. The accuracy of the Function Fitting Artificial Neural Network classifier (FFANN) is 96.1%, which is higher than that of any of the other classifiers currently used in the rainfall database.

Les sauts de l’ange : Appreciative Inquiry, une manière d’être

‘To be an AI practitioner is to be called to manifest trust in oneself, others and life. This alignment is, first and foremost, an inner one: it refers to our intention, which constantly asks to be purified. It also refers to the acceptance of our fears and doubts. And, when the magic of Appreciative Inquiry takes place in me for me, I see doors and windows in my space that let the light in, and I jump.’ Patricia

Numerical study of the Schwinger effect in axion inflation

Previous studies demonstrate that the inflaton, when coupled to the hypercharge Chern-Simons density, can source an explosive production of helical hypermagnetic fields. Then, in the absence of fermion production, those fields have the capability of preheating the Universe after inflation and triggering a successful baryogenesis mechanism at the electroweak phase transition. In the presence of fermion production, however, we expect a strong damping of the gauge fields production from the fermion backreaction, a phenomenon called Schwinger effect, thus jeopardizing their original capabilities. Using numerical methods, we study the backreaction on the generated gauge fields and revisit the processes of gauge preheating and baryogenesis in the presence of the Schwinger effect. We have found that gauge preheating is very unlikely, while still having a sizable window in the parameter space to achieve the baryon asymmetry of the Universe at the electroweak phase transition.

Bottlenose dolphins share fish farm areas while maintaining sexual segregation: Investigating group memberships through spatially and temporally explicit parameters

Abstract Group membership is a key attribute of animal societies and central to the study of social structure in several taxa. However, social structure analyses are sensitive to the way data are collected and associations defined. In this study, a time–space method was used to investigate the social structure of common bottlenose dolphins Tursiops truncatus observed and photographed across 7 years in the semi‐enclosed Gulf of Corinth, Greece. Instead of adopting traditional group definitions, individuals were considered as being members of the same group if photographed within a specific time and space window. This approach can be applied post hoc across studies and can offer advantages under challenging sampling conditions (e.g. when dealing with groups spread over vast areas or when group membership is otherwise hard to assess). Dolphins were mostly found around coastal cage aquaculture facilities farming European sea bass Dicentrarchus labrax and gilthead seabream Sparus aurata. Dolphins formed clusters largely or entirely composed of individuals of the same sex, suggestive of sex‐based homophily. Habitat partitioning was not detected: there was substantial spatial overlap among dolphin clusters, with all individuals using a relatively small area in the northern portion of the Gulf, where most of the productive fish farms were located. Associations between females were stronger than those between males, and daughters tended to stay in the group of their mothers. Sex‐based social clustering may allow females and calves to limit interactions with potentially aggressive males, while individuals of both sexes benefit from prey concentrated around fish farms. Adaptation to foraging around farms can result in trade‐offs between the costs and benefits of nourishment and social interaction. This may have both positive or negative effects on the animals that should be considered in the context of ensuring their favourable conservation status.

Dimples, jets and self-similarity in nonlinear capillary waves

Numerical studies of dimple and jet formation from a collapsing cavity often model the initial cavity shape as a truncated sphere, mimicking a bursting bubble. In this study, we present a minimal model containing only nonlinear inertial and capillary forces, which produces dimples and jets from a collapsing capillary wave trough. The trough in our simulation develops from a smooth initial perturbation, chosen to be an eigenmode to the linearised ${O}(\epsilon )$ problem ( $\epsilon$ is the non-dimensional amplitude). We explain the physical mechanism of dimple formation and demonstrate that, for moderate $\epsilon$ , the sharp dimple seen in simulations is well captured by the weakly nonlinear ${O}(\epsilon ^3)$ theory developed here. For $\epsilon \gg 1$ the regime is strongly nonlinear, spreading surface energy into many modes, and the precursor dimple now develops into a sharply rising jet. Here, simulations reveal a novel localised window (in space and time) where the jet evolves self-similarly following inviscid (Keller & Miksis, SIAM J. Appl. Maths, vol. 43, issue 2, 1983, pp. 268–277) scales. We develop an analogy of this regime to a self-similar solution of the first kind, for linearised capillary waves. Our first-principles study demonstrates that, at sufficiently small scales, dimples and jets can form from radial inward focusing of capillary waves, and the formation of this may be described by a relatively simple model employing (nonlinear) inertial and capillary effects. Viscosity and gravity can, however, significantly influence the focusing process, either intensifying the singularity or weakening it (Walls et al., Phys. Rev. E, vol. 92, issue 2, 2015, 021002; Gordillo & Rodríguez-Rodríguez, J. Fluid Mech., vol. 867, 2019, pp. 556–571). This leads, in particular, to critical values of Ohnesorge and Bond numbers, which cannot be obtained from our minimal model.

Time irreversibility analysis and abnormality detection based on Riemannian geometry for complex time series

Time irreversibility (TIR) is one of the basic properties of nonlinear systems, and it can be used as an effective way to explore the nonlinear complexity of dynamic systems. In this paper, we propose the TIR measure algorithm based on Riemannian geometry and apply this algorithm to abnormality detection tasks. The core idea is to calculate the positive definite covariance matrices of the forward sequence and its inverse sequence based on the theories of sliding window and phase space reconstruction, and compute the affine invariant Riemannian metric (AIRM) between them to characterize the TIR of the time series. The advantage of this algorithm is that the framework based on Riemannian geometry can more effectively use the spatial information of time series. In addition, compared with the traditional methods, the new method is suitable for nonstationary complex systems, which introduces a sliding window to make subsequences satisfy weak stationary conditions to measure local time irreversibility. The simulated and surrogate data are used to verify the effectiveness of the algorithm. Finally, we apply the algorithm to empirical analysis. The results show that, the algorithm detects the financial crisis period and stable period of the stock markets in the analysis of the financial system, and the loss degree of TIR of physiologic signals of different types of cardiac patients is detected in the study of physiologic signals. In the research of Parkinson’s gait, we verify that the walker is an effective tool to improve the gait of early Parkinson’s patients through statistical tests.

Impact of natural window views on perceptions of indoor environmental quality: An overground experimental study

• People's thermal sensations move towards the neutral level when with a window. • Natural window views can enhance people's adaptation to slightly dark environments. • Natural window views can significantly improve people's overall comfort level. • Natural landscapes' effects on occupants are more psychological than physiological. Visual connection with natural elements has been shown to contribute to emotional and physical health, as well as to productivity. This study assessed the main effects of natural window views on subjective perceptions of indoor environmental quality and physiological parameters. We conducted a laboratory experiment with 22 participants in spaces with and without natural window views. The indoor temperatures were set to 23, 26, and 28°C, and the illumination to 150, 300, and 500 lx. Environmental and physiological parameters were monitored and responses to subjective questionnaires were collected. The results showed that participant's thermal sensations move towards the neutral level when with natural window views, especially under slightly warm conditions (28°C, votes decreased by 0.36). Additionally, participants with natural window views showed a 0.4 improvement in luminous sensation and a 17.5% reduction in eye symptoms under 150 lx. The window increased participants' ratings of overall comfort by 0.23 and decreased the effects of temperature and illumination by 2.7% and 2.3%, respectively. Decreasing pulse rate and increasing arterial oxygen saturation (SpO 2 ) in the window space reflected the relief of stress and fatigue. The reduction in cooling and lighting requirements demonstrates the potential energy-saving benefits of windows.

이비인후과 비대면 로봇 진료를 위한 UX 디자인 연구

In a face-to-face medical environment where masks are taken off in a continuous COVID-19 infection environment, medical staff and patients are exposed to respiratory disease infection environments. The purpose of this study is to propose a concept design according to non-face-to-face robot treatment in otolaryngology for the prevention of respiratory diseases and infectious diseases for patients and medical staff by analyzing the face-to-face treatment environment by approaching from a UX perspective. First, the literature and cases were investigated, and patient experiences, observations, interviews, and treatment environments were conducted through visits to the otolaryngology hospital. Second, a design concept was derived through face-to-face treatment environment analysis and a non-face-to-face robot treatment scenario was presented. Third, we proposed a concept design for an otolaryngology robot treatment room according to a non-face-to-face robot treatment scenario. As a result of the study, the three key words for design direction development were derived by analyzing the collected data as spatiality, observability, and usability of treatment. According to three keywords, the treatment method process, treatment room layout, unit chair, and robot treatment UI for otolaryngology robot treatment were designed. The problems derived from the Master device and the Robot system of Main and Sub to operate the treatment robot more precisely will proceed to follow-up research. The patient wants to see the doctor in the hospital for treatment. In order for non-face-to-face robotic treatment to be implemented in otolaryngology, a gradual shift from face-to-face treatment is required. When the patient and doctor are interviewed through a glass window in a separate space, and when the robot medical experience becomes common, it is converted to an online questionnaire, suggesting the possibility of non-face-to-face robotic treatment and remote treatment. This study approaches from the UX point of view, suggests concept design, and finds solutions to problems, and places significance on the functional aspect of concept design development from the research results, where problems are found again. It is expected that non-face-to-face medical services will be developed.

Hearing impairment in murine model of Down syndrome.

Hearing impairment is a cardinal feature of Down syndrome (DS), but its clinical manifestations have been attributed to multiple factors. Murine models could provide mechanistic insights on various causes of hearing loss in DS. To investigate mechanisms of hearing loss in DS in the absence of the cadherin 23 mutation, we backcrossed our DS mice, Dp(16)1Yey, onto normal-hearing CBA/J mice and evaluated their auditory function. Body weights of wild type (WT) and DS mice were similar at 3-months of age, but at 9-months, WT weighed 30% more than DS mice. Distortion product otoacoustic emissions (DPOAE), a test of sensory outer hair cell (OHC) function negatively impacted by conductive hearing loss, were reduced in amplitude and sensitivity across all frequencies in DS mice. The middle ear space in DS mice appeared normal with no evidence of infection. MicroCT structural imaging of DS temporal bones revealed a smaller tympanic membrane diameter, oval window, and middle ear space and localized thickening of the bony otic capsule, but no gross abnormalities of the middle ear ossicles. Histological analysis of the cochlear and vestibular sensory epithelium revealed a normal density of cochlear and vestibular hair cells; however, the cochlear basal membrane was approximately 0.6 mm shorter in DS than WT mice so that the total number of hair cells was greater in WT than DS mice. In DS mice, the early and late peaks in the auditory brainstem response (ABR), reflecting neural responses from the cochlear auditory nerve followed by subsequent neural centers in the brainstem, were reduced in amplitude and ABR thresholds were elevated to a similar degree across all frequencies, consistent with a conductive hearing impairment. The latency of the peaks in the ABR waveform were longer in DS than WT mice when compared at the same intensity; however, the latency delays disappeared when the data were compared at the same intensity above thresholds to compensate for the conductive hearing loss. Future studies using wideband tympanometry and absorbance together with detailed histological analysis of the middle ear could illuminate the nature of the conductive hearing impairment in DS mice.

Fibonacci direct product variation tilings

The direct product of two Fibonacci tilings can be described as a genuine stone inflation rule with four prototiles. This rule admits various modifications, which lead to 48 different inflation rules, known as the direct product variations. They all result in tilings that are measure-theoretically isomorphic by the Halmos–von Neumann theorem. They can be described as cut and project sets with characteristic windows in a two-dimensional Euclidean internal space. Here, we analyze and classify them further, in particular, with respect to topological conjugacy.

Thermal Environment and Energy Performance of a Typical Classroom Building in a Hot-Humid Region: A Case Study in Guangzhou, China

Buildings and the construction sector account substantially for global energy consumption. In hot-humid areas of China, suboptimal thermal comfort in classrooms has heightened their cooling load and energy consumption. It is necessary to renovate the buildings of outdated code according to the current weather conditions to save energy. This study thus aimed to examine the thermal effects of such designs on the cooling load, based on an actual classroom building during summers in hot-humid southern China. Using air temperature and PMV values to evaluate thermal comfort, this study conducted simulation through EnergyPlus and DesignBuilder. The resultant updated typical meteorological year (TMY) and the monthly and hourly analyses of indoor thermal comfort revealed persistent classroom overheating. To mitigate the cooling load, numerous design variables were investigated: space form, roofing, external walls, windows, and shading devices. Evaluative comparisons found that appropriate choice of external windows and shading devices represented the two most effective strategies in mitigating the cooling load. Furthermore, jointly applying effective retrofit strategies to the building yielded a favorable reduction in the annual cooling energy consumption by 16.6%. The findings herein are envisioned to provide evidence-based referential guidance for building designs for classrooms in a hot-humid climate.

Cross-Comparison of Individual Tree Detection Methods Using Low and High Pulse Density Airborne Laser Scanning Data

Numerous individual tree detection (ITD) methods have been developed for use with airborne laser scanning (ALS) data to provide tree-scale forest inventories across large spatial extents. Despite the growing number of methods, relatively few have been comparatively assessed using a single benchmark forest inventory validation dataset, limiting their operational application. In this study, we assessed seven ITD methods, representing three common approaches (point-cloud-based, raster-based, hybrid), across coniferous forest stands with diverse structure and composition to understand how ITD and height measurement accuracy vary with method, input parameters and data, and stand density. There was little variability in accuracy between the ITD methods where the average F-score and standard deviation (±SD) were 0.47 ± 0.03 using a lower pulse density ALS dataset with an average of 8 pulses per square meter (ppm2) and 0.50 ± 0.02 using a higher pulse density ALS dataset with an average of 22 ppm2. Using higher ALS pulse density data produced higher ITD accuracies (F-score increase of 10–13%) in some of the methods versus more modest gains in other methods (F-score increase of 1–3%). Omission errors were strongly related with stand density and largely consisted of suppressed trees underneath the dominant canopy. Simple canopy height model (CHM)-based methods that utilized fixed-size local maximum filters had the lowest omission errors for trees across all canopy positions. ITD accuracy had large intra-method variation depending on input parameters; however, the highest accuracies were obtained when parameters such as search window size and spacing thresholds were equal to or less than the average crown diameter of trees in the study area. All ITD methods produced height measurements for the detected trees that had low RMSE (<1.1 m) and bias (<0.5 m). Overall, the results from this study may help guide end-users with ITD method application and highlight future ITD method improvements.

SPNet: Learning Stereo Matching With Slanted Plane Aggregation

Matching cost aggregation plays a critical role for the stereo matching task. Existing CNN-based methods commonly use 3D convolutions to aggregate matching costs from a local 3D space. However, the high computational cost of 3D convolutions limits their applications. Traditional methods show that a slanted support window in 3D space can help to aggregate matching costs from informative regions, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e.,</i> the surfaces of objects. Motivated by this idea, we propose a SPNet with differentiable slanted plane aggregation. Our slanted plane aggregation layers aggregate matching costs from a learnable slanted plane in a local 3D space to reduce computational and memory costs. Experimental results show that our slanted plane aggregation layers can learn to fit the surfaces of objects and effectively aggregate matching costs. Comparison with previous stereo matching methods shows that our network achieves competitive performance with higher efficiency.

Design and evaluation of window management operations in AR headset+smartphone interface

BackgroundThe combination of an augmented reality (AR) headset and a smartphone can simultaneously provide a wider display and a precise touch input; it can redefine the way we use applications today. However, users are deprived of such benefits owing to the independence of the two devices. There is a lack of intuitive and direct interactions between them. MethodsIn this study, we conduct a formative investigation to understand the window management requirements and interaction preferences of using an AR headset and a smartphone simultaneously and report the insights we gained. In addition, we introduce an example vocabulary of window management operations in the AR headset and smartphone interface. ResultsThis allows users to manipulate windows in a virtual space and shift windows between devices efficiently and seamlessly.

Synchronization of a genetic oscillator with the cell division cycle

Genetic circuits that control specific cellular functions are never fully insulated against influences of other parts of the cell. For example, they are subject to periodic modulation by the cell cycle through volume growth and gene doubling. To investigate possible effects of the cell cycle on oscillatory gene circuits dynamics, we modelled a simple synthetic genetic oscillator, the repressilator, and studied hallmarks of the resulting nonlinear dynamics. We found that the repressilator coupled to the cell cycle shows typical quasiperiodic motion with discrete Fourier spectra and windows in parameter space with synchronization of the two oscillators, with a devil’s stair case indicating the Arnold tongues of synchronization. In the case of identical parameters for the three genes of the repressilator and simultaneous gene duplication, we identify two classes of synchronization windows, symmetric and asymmetric, depending on whether the trajectories satisfy a discrete three-fold rotation symmetry, corresponding to cyclic permutation of the three genes. Unexpectedly changing the gene doubling time revealed that the width of the Arnold tongues is connected to that three-fold symmetry of the synchronization trajectories: non-simultaneous gene duplication increases the width of asymmetric synchronization regions, for some of them by an order of magnitude. By contrast, there is only a small or even a negative effect on the window size for symmetric synchronization. This observation points to a control mechanism of synchronization via the location of the genes on the chromosome.

How much efficiency improvement can a spatiotemporal window generate for shared mobility? A case study in New York City

The popularity of shared mobility services has increased in recent years. A complete door-to-door mode is typically deployed. However, the efficiency of the underlying resource utilization is limited in this mode. The space window, a recently developed concept, has the potential to optimize the underlying resource utilization. In this article, the impacts of this concept on the performance of shared mobility in major urban centres, e.g. New York City (NYC), is investigated. To this end, a dynamic routing framework with a spatiotemporal window in L1-norm and a dispatching mechanism are introduced. The operation data demonstrates a 15% reduction of the total distance travelled and the number of vehicles needed if passengers walk a few blocks. These results indicate that a spatiotemporal window holds the promise of a more environmentally friendly, energy efficient and intelligently shared mobility platform with alleviated congestion.

Intermittency regimes of poorly-mixed chemical oscillators

Perfect mixing or interaction between oscillators is almost never achieved under experimental conditions and, nevertheless, it might be crucial in understanding the observed phenomena. We propose a mathematical model that directly introduces the degree of mixing and analyze the consequences on the synchronization patterns observed. For that we considered catalyst-loaded chemical oscillators as they represent a paradigm for synchronization phenomena from the experimental and numerical point of view. In this study we explore a modified 3-variable Oregonator model where the active surrounding solution is discretized as oscillators themselves and a discrete radius of chemical exchange is introduced to account for spatial distribution and movement dynamics. We found that for low-to none levels of mixing in the system, a series of irregular states appear on the edge of phase transitions among dynamical regimes, and that several novel non-fully synchronized behaviors appear for a small window in the parameter space.

Effect of service differentiation on QoS in IEEE 802.11e enhanced distributed channel access: a simulation approach

The enhanced distributed channel access (EDCA) protocol is a supplement to IEEE 802.11 medium access control (MAC), ratified by IEEE 802.11e task group to support quality of service (QoS) requirements of both data and real-time applications. Previous research show that it supports priority scheme for multimedia traffic but strict QoS is not guaranteed. This can be attributed to inappropriate tuning of the medium access parameters. Thus, an in-depth analysis of the EDCA protocol and ways of tuning medium access parameters to improve QoS requirements for multimedia traffic is presented in this work. An EDCA model was developed and simulated using MATLAB to assess the effect of differentiating contention window (CW) and arbitration inter-frame space (AIFS) of different traffic on QoS parameters. The optimal performance, delay, and maximum sustainable throughput for each traffic type were computed under saturation load. Insight shows that traffic with higher priority values acquired most of the available channels and starved traffic with lower priority values. The AIFS has more influence on the QoS of EDCA protocol. It was also observed that small CW values generate higher packet drops and collision rate probability. Thus, EDCA protocol provides mechanism for service differentiation which strongly depends on channel access parameters: CW sizes and AIFS.