Position Of Window Research Articles

Identification and classification of transient pulses observed in magnetometer array data by time-domain principal component analysis filtering

A method for identification of pulsations in time series of magnetic field data which are simultaneously present in multiple channels of data at one or more sensor locations is described. Candidate pulsations of interest are first identified in geomagnetic time series by inspection. Time series of these “training events” are represented in matrix form and transpose-multiplied to generate time-domain covariance matrices. The ranked eigenvectors of this matrix are stored as a feature of the pulsation. In the second stage of the algorithm, a sliding window (approximately the width of the training event) is moved across the vector-valued time-series comprising the channels on which the training event was observed. At each window position, the data covariance matrix and associated eigenvectors are calculated. We compare the orientation of the dominant eigenvectors of the training data to those from the windowed data and flag windows where the dominant eigenvectors directions are similar. This was successful in automatically identifying pulses which share polarization and appear to be from the same source process. We apply the method to a case study of continuously sampled (50 Hz) data from six observatories, each equipped with three-component induction coil magnetometers. We examine a 90-day interval of data associated with a cluster of four observatories located within 50 km of Napa, California, together with two remote reference stations-one 100 km to the north of the cluster and the other 350 km south. When the training data contains signals present in the remote reference observatories, we are reliably able to identify and extract global geomagnetic signals such as solar-generated noise. When training data contains pulsations only observed in the cluster of local observatories, we identify several types of non-plane wave signals having similar polarization.

Dynamically tunable electromagnetically-induced-transparency–like resonances in graphene nanoring and nanodisk hybrid metamaterials

A tunable electromagnetically-induced-transparency–like (EIT-like) device is proposed numerically and theoretically in the mid-infrared region, which is composed of periodically patterned ring and disk graphene. Distinguished from the commonly used three-level system, the hybridization of the plasmon mode is applied to describing and explaining the EIT-like phenomenon in the proposed systems. What is more, further researches have revealed that the spectral position of the transparency window can be tuned not only by geometrically changing the couple distance in graphene nanostructures, but also by dynamically altering the radius of the graphene nanodisk and the chemical potential of the graphene. At the transparency window, there exist large optical delays, which can slow down the speed of light in vacuum. This work may pave the way to the development of applications including tunable sensors, slow-light devices, and optical switches.

Thermal Performance Evaluation of Junction Thermal Bridge according to Installation Position of Window

Thermal Performance Evaluation of Junction Thermal Bridge according to Installation Position of Window

Improved transient evoked otoacoustic emission screening test using simple regression model and window optimization

The underlying problem in detection of transient evoked otoacoustic emission (TEOAE) is its extremely low level which is much under the level of noise that appears in the auditory canal. The algorithms based on wavelet transformation (WT) and frequency (e.g. scale) dependent windows are proved to have higher specificity and sensitivity of TEOAE test in comparison to the FFT-based algorithms using single analysis window. In this paper, a new algorithm for TEOAE screening test with improved performances is proposed. It is based on three improvements. The first one is based on simple linear regression model applied to series of signal-to-noise ratio (SNR) estimates and correction of the reproducibility estimate by mean square error criterion. The second one exploits inter-subjects variability of TEOAE latency by selecting the best window position. The third is based on the use of specific window shape developed from approximate of minimum mean square error criterion. The performance of the proposed TEOAE algorithm was tested on real TEOAE measurements embedded in artificial noise as well as on pure noise extracted from TEOAE measurements. The results provided evidence for the superiority of its performance in comparison with two referential algorithms.

Comparison of different incremental analysis update schemes in a realistic assimilation system with Ensemble Kalman Filter

In this paper, three incremental analysis update schemes (IAU 0, IAU 50 and IAU 100) are compared in the same assimilation experiments with a realistic eddy permitting primitive equation model of the North Atlantic Ocean using the Ensemble Kalman Filter. The difference between the three IAU schemes lies on the position of the increment update window. The relevance of each IAU scheme is evaluated through analyses on both thermohaline and dynamical variables. The validation of the assimilation results is performed according to both deterministic and probabilistic metrics against different sources of observations. For deterministic validation, the ensemble mean and the ensemble spread are compared to the observations. For probabilistic validation, the continuous ranked probability score (CRPS) is used to evaluate the ensemble forecast system according to reliability and resolution. The reliability is further decomposed into bias and dispersion by the reduced centred random variable (RCRV) score. The obtained results show that 1) the IAU 50 scheme has the same performance as the IAU 100 scheme 2) the IAU 50/100 schemes outperform the IAU 0 scheme in error covariance propagation for thermohaline variables in relatively stable region, while the IAU 0 scheme outperforms the IAU 50/100 schemes in dynamical variables estimation in dynamically active region 3) in case with sufficient number of observations and good error specification, the impact of IAU schemes is negligible. The differences between the IAU 0 scheme and the IAU 50/100 schemes are mainly due to different model integration time and different instability (density inversion, large vertical velocity, etc.) induced by the increment update. The longer model integration time with the IAU 50/100 schemes, especially the free model integration, on one hand, allows for better re-establishment of the equilibrium model state, on the other hand, smooths the strong gradients in dynamically active region.

Study of fluid edge detection and tracking method in glass flume based on image processing technology

Research on changes in the fluid edge of a wave flume is important for experimental hydrodynamics. However, disturbances often occur because of the presence of sensors. To solve this problem, a new grey-scale image processing method for fluid edge analysis is presented here. By fusing methods combining image gradients and image segmentation with shifting-window technology and with concepts derived from experimental fluid mechanics, the proposed method can overcome many of the inherent challenges of fluid-edge measurement. First, the geodesic distance is modified to obtain a class curve. Second, an edge position is determined by the inflection point of the class curve related to the gradient peak distribution. Next, the position of the interrogation window is relocated with reference to neighbors or to previous results, and the current edge position can be calculated according to the predicted value. During the computation, the interrogation window can change its position adaptively with fluid motion, ensuring that the amount of data to be analyzed always remains stable. A model combining the class curve and gradient curve can improve the validity of edge identification. Finally, the performance of the proposed method has been evaluated using images in a glass flume. The results show that the proposed method for studying the fluid edge is effective and robust.

Energy-saving potential by changing window position and size in an isolated building

ABSTRACTThe physical comfort of a building completely depends on the airing in the building. The window plays a superior role in providing ventilation without burning artificial energy. The forced system releases high poisonous gases such as CFCs, HCFCs, and HFCs. This paper concentrates on improvement of natural ventilation which is freely available by changing the size of the window and the orientation of the building. The computational fluid approach is used to understand the physical mechanism of air circulating inside the building. The forces and moments of air created inside the building also measured to achieve healthier considerations of circulation. From the results, it is evident that the natural ventilation is not only dependent on the velocity of air but also the orientation and shape of windows, and implementing an optimised design can save up to 20% of energy in residential buildings.

Systematic search for wide periodic windows and bounds for the set of regular parameters for the quadratic map

An efficient method to find positions of periodic windows for the quadratic map f(x)=ax(1-x) and a heuristic algorithm to locate the majority of wide periodic windows are proposed. Accurate rigorous bounds of positions of all periodic windows with periods below 37 and the majority of wide periodic windows with longer periods are found. Based on these results, we prove that the measure of the set of regular parameters in the interval [3,4] is above 0.613960137. The properties of periodic windows are studied numerically. The results of the analysis are used to estimate that the true value of the measure of the set of regular parameters is close to 0.6139603.

Investigation of Indonesian Traditional Houses through CFD Simulation

Modern buildings in Indonesia rely mostly on artificial lighting, heating, cooling and ventilation. It means more energy is used to drive mechanical appliances, and presumably not sustainable. Meanwhile modern buildings consume much energy, traditional architectures are known as the source of knowledge for sustainable, energy efficient and climate responsive design. Noticeably, one of the differences between modern and traditional buildings in Indonesia is shown in their strategy to provide thermal comfort to the user. Traditional buildings use natural ventilation, but modern buildings use mechanical air conditioning. By focusing on wind-driven ventilation, the study aims to investigate natural ventilation strategy of Indonesian traditional house, and their potential improvement to be used in modern Indonesian buildings. Three traditional houses are studied in this research, representing west, central, and east Indonesia. The houses are Lampung traditional house, Javanese traditional house, and Toraja traditional house. CFD simulation is conducted to simulate wind-driven ventilation behaviour and the temperature of the buildings. Concisely, the wind-natural ventilation of case study houses is potential to provide thermal comfort inside the houses. However, the strategy still can be optimized by adding some other passive design strategies: sun-shading; vegetation; or buildings arrangement in the traditional dwelling. Consideration about the roof’s shape and windows position to the roof is important as well to create a uniform air distribution.

Deflection characteristic of flame with the airflow induced by stack effect

A set of experiments was conducted in a small scale high-rise building model with 12 floors to study the deflection characteristic of flame with the airflow induced by the stack effect. The results show that the position of the open window influences the location of the neutral plane, which determines the airflow velocity induced by the stack effect, and a correlation is proposed for their relationship. The airflow has a significant impact on the burning rate. The stack effect would cause a separation of flame base from the pan at the windward side, resulting in the exposure of part of the fuel surface to the cold air. The dimensionless flame height (Hf/D) and length (Lf/D) of leaned heptane flame are proportional to 1/4 power of the dimensionless heat release rate (Q*). The temperature rise (ΔT) at the continuous flame zone is lower under the stack effect than that of a free burning case at open space due to the cooling of airflow. The flame of pool fire is stretched and the lengths of continuous and intermittent flame zones are much greater than those obtained at the open space. The ratio of L/Q2/5 in the intermittent flame zone ranges from 0.12 to 0.25 in the current research whereas it ranges from 0.08 to 0.2 at the open space.

Atomic scale imaging of structural changes in solid electrolyte lanthanum lithium niobate upon annealing

La(1-x)/3LixNbO3 (LLNbO) is a promising electrolyte material for solid-state lithium-ion batteries because it is stable in contact with Li metal and contains a high concentration of intrinsic Li-ion vacancies. One strategy for improving its ionic conductivity and making it more competitive with other solid-state Li-ion electrolytes is to disorder the Li-ion vacancies by appropriate post-synthesis heat treatment, e.g., annealing. In this study, we examine the effects of annealing on single crystals of LLNbO with Li contents x = 0.07 and 0.13 based on simultaneous atomic resolution high angle annular dark field and annular bright field imaging methods using state-of-the-art aberration corrected scanning transmission electron microscopes. It is found that La modulation within A1 layers of the cation-deficient layered perovskite structure becomes more diffuse after annealing. In addition, some La atoms move to A-site positions and O4 window positions in the nominally vacant A2 layer, while O atom columns in this layer become rumpled in the [001]p direction, indicating that the NbO6 octahedra are more heavily distorted after annealing. The observed crystal structure differences between as-prepared and annealed single crystals explain the drop in Li-ion conductivities of LLNbO single crystals after heat treatment.

Development of a Predictive Equation for Ventilation in a Wall-Solar Chimney System

A solar chimney is a natural ventilation technique that has potential to save energy consumption as well as to maintain the air quality in a building. However, studies of buildings are often challenging due to their large sizes. The objective of this study was to determine the relationships between small- and full-scale solar chimney system models. Computational fluid dynamics (CFD) was employed to model different building sizes with a wall-solar chimney utilizing a validated model. The window, which controls entrainment of ambient air for ventilation, was also studied to determine the effects of window position. A set of nondimensional parameters were identified to describe the important features of the chimney configuration, window configuration, temperature changes, and solar radiation. Regression analysis was employed to develop a mathematical model to predict velocity and air changes per hour, where the model agreed well with CFD results yielding a maximum relative error of 1.2% and with experiments for a maximum error of 3.1%. Additional wall-solar chimney data were tested using the mathematical model based on random conditions (e.g., geometry, solar intensity), and the overall relative error was less than 6%. The study demonstrated that the flow and thermal conditions in larger buildings can be predicted from the small-scale model, and that the newly developed mathematical equation can be used to predict ventilation conditions for a wall-solar chimney.

Statistical moments calculated via integral images in application to landmine detection from Ground Penetrating Radar 3D scans

Under study is an application of Ground Penetrating Radar (GPR) to landmine detection problem. We focus on the detection of antitank mines carried out in the 3D GPR images, so-called C-scans, by means of a machine learning approach. In that approach, we particularly pursue a technique for fast extraction of image features based on an initial calculation of multiple integral images. This allows later to calculate each feature in constant time, regardless of the scanning window position and size. The features we study are statistical moments formulated in their 3D variant. We present a comparison of detection results for different sizes and parameterizations of feature sets. All results are obtained from a prototype GPR system of our original construction in terms of both hardware and software.

Controlled EIT and signal storage in metamaterial with tripod structure

In the present paper we have discussed in detail electromagnetically induced transparency and signal storing in the case of one signal pulse propagating in a classical electric medium resembles this of four-level atoms in the tripod configuration. Our theoretical results confirm recently observed dependence of transparency windows position on coupling parameters. In the process of storing, the pulse energy is confined inside the metamaterial as electric charge oscillations, and after required time it is possible to switch the control fields on again and to release the trapped signal. By manipulating the driving fields, one can thus control the parameters of the released signal and even to divide it on demand into arbitrary parts.

Individual differences in judging the annoyance of the sounds of helicopters

A rarely used procedure for studying aviation noise annoyance is asking people ro rate indiviidual aircraft events experienced in their homes. Our study employs this procedure with five subjects who self-identified as “highly annoyed” by helicopters. Subjects lived within 400 m of each other. Flights were recorded at three homes over a 10 day survey period during which subjects registered their judgments on a cell phone app with which a subject initiated a survey by tapping “hear a helicopter.” Questions included location (indoors/outdoors), window position (open/closed), annoyance (5 pt scale), loudness (3 pt scale), and house rattles (3 pt scale). Recordings corresponding to completed surveys were analyzed for ASEL, CSEL, subjective and objective duration, loudness, loudness level, fluctuation strength, and roughness. Stepwise regression was used to find the most robust predictors of annoyance. The data confirmed the importance of ASEL and/or measures of loudness as predictors. Compared with in-home obs...

Study of the effect of sun patch on the transient thermal behaviour of a heating floor in Algeria

Solar radiation is a renewable non polluting energy source which can be used in buildings through various systems technologies. Thermal radiation, absorbed or transmitted by the walls and windows, creates a solar gain which has a direct impact on the thermal behavior in the building. Most existing thermal models neglect the effect of the evolution of the sun patch position on the heating floor which can have a great impact on the indoor thermal comfort.In this paper, we present numerical model to calculate the transient sun patch position and its influence on the heating floor model in order to evaluate its impact on the heating floor operating conditions and on the indoor air temperature, which has a great influence on thermal comfort under the climatic conditions of Oran city in Algeria. The sun patch is calculated using Ray Tracing model as proposed in FLUENT whereas the room and the heating floor are modelled with TRNSYS software.Using literature data, the two proposed models (sun patch model and heating floor model) are validated and used to simulate the cases with different geographic locations and different window orientations, surfaces, and positions. Our results suggest that the displacement of the sun patch on the heating floor lead to a superheating of the irradiated zone and it affects the indoor air temperature and thermal comfort too.

Robust tracking of multiple persons in real-time video

In this paper, we present a robust person tracking method that the particle swarm optimization (PSO) algorithm is used as the tracking strategy. The method is divided into two procedures: object/background segmentation and tracking. For object/background segmentation, we use the temporal differencing to detect the regions of interest. For tracking, the PSO algorithm is used for overcome the robustness problem in the high noisy background and multiple moving persons and/or under occlusion. The particles in PSO represent the position, width and height of the search window, and the fitness function is calculated by the distance of the color feature vector and the histogram intersection. When occluded, we add the motion vector plus the previous position of the tracking model. The particles fly around the search region to obtain an optimal match of the target. The experiments show that the proposed method can track the single person, multiple people even when occluded, and is more efficient and accurate than the conventional particle filter method.

Effects of window position on natural cross ventilation in vernacular architecture of mazandaran (case study: SARI)

Among the most effective architectures is vernacular architecture of Mazandaran whose incorporation in nature is so delicate that appears to be an essential part of it. Paying more attention to vernacular architecture and promoting it can be helpful in reducing energy consumption. Increasing use of fossil fuels in heating and cooling systems of buildings that come with excessive costs can result from inattention to vernacular architecture principles. However taking them into consideration can be an effective solution for reducing energy consumption. This research aimed to study the effects of window position on natural cross ventilation in Vernacular architecture of Mazandaran applying Descriptive - analytical approach. For this reason, a number of vernacular buildings, located in Sari, were studied regarding numbers and sizes of bilateral opening and its function in ventilation. Variables in this research were tested using SPSS and Regression correlation coefficient; additionally, all 3 formulas suggested in the results were evaluated to achieve an optimal model. In this study, for a desirable ventilator, for every percent added to the room area, the windows showed a 0.87 percent increase in size, and for every additional story, the optimal ventilation grew 30 percent. On the other hand, in high-rise apartments, the protrusion contribution in ventilation system was highlighted. This research study aims to clarify the principles of proper ventilation in vernacular architecture which have long been forgotten. Keywords : natural ventilation; window; vernacular architecture; temperate and wet climate.

2D Image Recognition of Partially Occluded Objects Based on Adaptive Window Positioning and Dynamic Time Warping

The boundaries of computer vision are e specially challenged by partial occluded object recognition. In this paper, we proposed a new algorithm that used to recognize the partially occluded objects in 2 - D images. Two different cases of occlusion are considered. Firstly, when an object missing so me parts. Secondly, objects are overlapping each other. This approach uses contour of an object. Adaptive Window Positioning (AWP) uses to extract features from a contour. The proposed method uses the orientation field as features of the fragment. Dynamic Time Warping (DTW) works for matching and find the similarity between sub - images. As experiment result, the proposed recognition algorithm works without prior segmentation and robust to identify missing and overlapping objects and it can woks with strength occlusion.

Dynamic detection of window starting positions and its implementation within an activity recognition framework

Activity recognition is an intrinsic component of many pervasive computing and ambient intelligent solutions. This has been facilitated by an explosion of technological developments in the area of wireless sensor network, wearable and mobile computing. Yet, delivering robust activity recognition, which could be deployed at scale in a real world environment, still remains an active research challenge. Much of the existing literature to date has focused on applying machine learning techniques to pre-segmented data collected in controlled laboratory environments. Whilst this approach can provide valuable ground truth information from which to build recognition models, these techniques often do not function well when implemented in near real time applications. This paper presents the application of a multivariate online change detection algorithm to dynamically detect the starting position of windows for the purposes of activity recognition.