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Journal articles on the topic 'Window detection'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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1

Alfadeel, Hajer. "Impact of CT Stroke Window Settings on Acute Stroke Detection." Scientific Journal of University of Benghazi 38, no. 1 (2025): 193–214. https://doi.org/10.37376/sjuob.v38i1.7328.

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Non-contrast CT is the most important imaging modality in the evaluation of suspected acute stroke by excluding intracranial haemorrhage and directly visualizing early ischemic changes. These changes are challenging to detect on non-contrast CT due to the small reduction in the attenuation value of ischemic tissue from normal. The study’s objective was to assess the use of stroke window settings for improving the detection of acute stroke. This retrospective study included forty-nine patients in whom non-contrast CT were performed for suspected acute stroke within 24 hours from symptom onset.

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Yang, Zhifa, Yu Zhu, Haodong Zhang, Zhuo Yu, Shiwu Li, and Chao Wang. "Moving-Vehicle Identification Based on Hierarchical Detection Algorithm." Sustainability 14, no. 1 (2021): 264. http://dx.doi.org/10.3390/su14010264.

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The vehicle detection method plays an important role in the driver assistance system. Therefore, it is very important to improve the real-time performance of the detection algorithm. Nowadays, the most popular method is the scanning method based on sliding window search, which detects the vehicle from the image to be detected. However, the existing sliding window detection algorithm has many drawbacks, such as large calculation amount and poor real-time performance, and it is impossible to detect the target vehicle in real time during the motion process. Therefore, this paper proposes an impro

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IMRAN, T. "Anomaly Detection in ELI-NP Front-End Laser Energy Data Using an Optimized Moving Average Method." Romanian Journal of Physics 70, no. 3-4 (2025): 902. https://doi.org/10.59277/romjphys.2025.70.902.

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Anomaly detection in time-series data is critical for ensuring stability in high-power laser systems, where deviations can indicate potential failures. This study optimizes a moving average-based methodology for anomaly detection accuracy by evaluating window sizes (3, 6, 9, 12, and 15) and threshold multipliers (1.0, 1.5, and 2.0). The analysis integrates Mean Squared Error (MSE), correlation analysis, and graphical evaluations, including anomaly distribution, moving average trends, and parameter sensitivity plots. Results indicate that smaller window sizes effectively detect short-term fluct

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Hou, Guozhong, Zhiwei Dong, Sheng Zhang, Zhibin Zhang, and Yuanqin Xia. "TPF imaging of Rhodamine B at different detection windows." Modern Physics Letters B 33, no. 23 (2019): 1950268. http://dx.doi.org/10.1142/s0217984919502683.

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Broadband two-photon fluorescence (TPF) imaging system based on femtosecond oscillator is built. Broadband TPF signal generated from Rhodamine B molecule is detected at different detection windows. Both TPF signals detected at short wavelength detection window of 545–615 nm and long wavelength detection window of 642–708 nm are used for TPF imaging. Through switching detection window from short wavelength to long wavelength, deepened imaging depth is achieved. The TPF imaging results, with single [Formula: see text] pixels frame taking time of 4–8 s, demonstrate high performance and the good r

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Wang, Ya Hui, Qiang Wang, Bo Chang Zhang, and Bo Liang. "Measurement of Thermo-Radiation Characteristics of IR Window Materials." Advanced Materials Research 1083 (January 2015): 104–10. http://dx.doi.org/10.4028/www.scientific.net/amr.1083.104.

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When aircrafts have hypersonic flights in the atmosphere, high-temperature IR windows become the main factor of complicated aero-thermo-radiation effects, which reduce the performance of IR detection systems, or even make these detection systems fail. Consequently, measuring thermo-radiation characteristics of IR window material is essential for the assessment of aero-thermo-radiation effect. By analyzing thermal radiation transfer in IR windows, a method is proposed to measure thermo-radiation characteristics of IR window materials, and an experimental platform is established. Based on the pl

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Cao, Qing Kui, and Qian Zhang. "A Task Conflict Detection Model of Logistics Distribution." Advanced Materials Research 452-453 (January 2012): 736–40. http://dx.doi.org/10.4028/www.scientific.net/amr.452-453.736.

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Based on the time window in the vehicle scheduling problem(VSP), we propose the concept of time windows of delivery tasks(TWDT) in the distribution center, and describe the TWDT in a kind of three-tuple. Transferring time windows constraint of multiple tasks to a simple temporal constraint network, we simplify the problem of checking the time constraint of multiple tasks to the problem of checking the temporal constraint network’s consistency. According to the characteristic of delivery task and simple temporal constraint network, we proposed the model of time window conflict checking of deliv

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Yokesh Babu S, Vansh Harkut, Himanshu Sharma, and Vishal. "Tint Detection Using Image Analysis." International Research Journal on Advanced Engineering Hub (IRJAEH) 3, no. 03 (2025): 502–10. https://doi.org/10.47392/irjaeh.2025.0070.

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This paper introduces an automated Tint Detection System designed to meet regulatory requirements for vehicle window tinting through advanced image analysis techniques. Excessive tinting on vehicle windows can impair visibility, affecting road safety and law enforcement’s ability to monitor vehicles. Traditional manual inspections are time-intensive, costly, and prone to error. This project proposes a system that automates tint detection in real-time using a modular pipeline incorporating YOLOv5 for vehicle detection, U-Net for window segmentation, and a Convolutional Neural Network (CNN) for

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Sheremetov, L., and N. Zarate-Guzmán. "A MOVING WINDOW APPROACH TO IDENTIFICATION OF PATTERNS IN MULTIVARIATE TIME SERIES: APPLICATION TO THE MULTIVARIATE FAULT DETECTION OF ELECTRICAL SUBMERSIBLE PUMPS." Danish scientific journal, no. 63 (August 26, 2022): 25–31. https://doi.org/10.5281/zenodo.7038257.

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<strong>Abstract</strong> The paper describes a multivariate time series pattern recognition method based on reference windows and used for the detection of fault patterns of electric submersible pumps caused by scales formed during production process in petroleum wells. Through a “moving window” strategy, the algorithm finds and selects reference windows in a long time series and computes the similarity between each selected window and the reference one (smaller time series) using the Euclidean distance. This method can simultaneously get the results of fault detection and fault d

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Jancee, B. Victoria, and S. Radha. "Online Detection of Change on Information Streams in Wireless Sensor Network Modeled Using Gaussian Distribution." Modelling and Simulation in Engineering 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/658302.

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Wireless sensor network (WSN) is deployed to monitor certain physical quantities in a region. This monitoring problem could be stated as the problem of detecting a change in the parameters of a static or dynamic stochastic system. A moving window procedure is proposed to detect the systematic error, which occurs at an unknown time. It can detect the deviation in the mean of sensor measurements keeping variance as constant. The performance measures, such as the average run length (ARL) to detection delay and false alarms are computed for various window sizes. The performance comparison is done

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Drauschke, M., and H. Mayer. "THE POTENTIAL OF SPECULAR REFLECTIONS FOR FAÇADE IMAGE ANALYSIS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-3/W4 (March 11, 2015): 33–40. http://dx.doi.org/10.5194/isprsannals-ii-3-w4-33-2015.

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Several approaches for window detection have been proposed in recent years, which all use the window size, shape or position within the façade as characteristics for the detection. In this paper another property of windows is proposed for their detection: Windows are made of glass, so they tend to specularly reflect sun light, while the surrounding wall diffusely reflects it. To this end, colour values in multiple views are analysed to detect specular reflections. In the experiments, walls often show a high homogeneity of small colour differences, and many windows are clearly visible in the fo

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Tervonen, Jaakko, Kati Pettersson, and Jani Mäntyjärvi. "Ultra-Short Window Length and Feature Importance Analysis for Cognitive Load Detection from Wearable Sensors." Electronics 10, no. 5 (2021): 613. http://dx.doi.org/10.3390/electronics10050613.

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Human cognitive capabilities are under constant pressure in the modern information society. Cognitive load detection would be beneficial in several applications of human–computer interaction, including attention management and user interface adaptation. However, current research into accurate and real-time biosignal-based cognitive load detection lacks understanding of the optimal and minimal window length in data segmentation which would allow for more timely, continuous state detection. This study presents a comparative analysis of ultra-short (30 s or less) window lengths in cognitive load

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Chua, Wei Png, and Chien Chern Cheah. "Deep-Learning-Based Automated Building Construction Progress Monitoring for Prefabricated Prefinished Volumetric Construction." Sensors 24, no. 21 (2024): 7074. http://dx.doi.org/10.3390/s24217074.

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Prefabricated prefinished volumetric construction (PPVC) is a relatively new technique that has recently gained popularity for its ability to improve flexibility in scheduling and resource management. Given the modular nature of PPVC assembly and the large amounts of visual data amassed throughout a construction project today, PPVC building construction progress monitoring can be conducted by quantifying assembled PPVC modules within images or videos. As manually processing high volumes of visual data can be extremely time consuming and tedious, building construction progress monitoring can be

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Li, Zhenhua, Tinghe Hu, and Ahmed Abu-Siada. "A Minimum Side-Lobe Optimization Window Function and Its Application in Harmonic Detection of an Electricity Gird." Energies 12, no. 13 (2019): 2619. http://dx.doi.org/10.3390/en12132619.

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Several window functions are currently applied to improve the performance of the discrete Fourier transform (DFT) harmonic detection method. These window functions exhibit poor accuracy in measuring the harmonic contents of a signal with high-order and weak-amplitude components when the power frequency fluctuates within a small range. In this paper, a minimum side-lobe optimization window function that is aimed at overcoming the abovementioned issue is proposed. Moreover, an improved DFT harmonic detection algorithm based on the six-term minimum side-lobe optimization window and four-spectrum-

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14

Yuan, Wei, Lei Qiao, and Liu Tang. "Forest Wildfire Detection from Images Captured by Drones Using Window Transformer without Shift." Forests 15, no. 8 (2024): 1337. http://dx.doi.org/10.3390/f15081337.

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Cameras, especially those carried by drones, are the main tools used to detect wildfires in forests because cameras have much longer detection ranges than smoke sensors. Currently, deep learning is main method used for fire detection in images, and Transformer is the best algorithm. Swin Transformer restricts the computation to a fixed-size window, which reduces the amount of computation to a certain extent, but to allow pixel communication between windows, it adopts a shift window approach. Therefore, Swin Transformer requires multiple shifts to extend the receptive field to the entire image.

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15

Maheshwari, Sudhanshu. "Current Conveyor Based Window Comparator Circuits." Advances in Electrical Engineering 2016 (December 7, 2016): 1–8. http://dx.doi.org/10.1155/2016/6356203.

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This paper introduces a new window comparator circuit utilizing a new current conveyor and two diodes, operable at ±1.25 V and capable of accurately detecting the voltage windows. Another modified circuit with distinct binary levels suited for automatic control applications is also suggested. Exhaustive simulation results showing detection of windows, as small as 50 mV and as high as 1 V, are included. Comparisons are further drawn with the traditional operational amplifier based circuit and the new circuit is found to benefit from the use of current-mode active element, namely, Extra-X Curren

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Li, Hening, Ran Liao, Hailong Zhang, et al. "Stress Detection of Conical Frustum Windows in Submersibles Based on Polarization Imaging." Sensors 22, no. 6 (2022): 2282. http://dx.doi.org/10.3390/s22062282.

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Stress detection of the conical frustum window is a very important issue to ensure the safety of deep manned submersibles. In this paper, we propose a method based on polarization imaging to evaluate the stress accumulation and recovery in the conical frustum window. An experimental setup of Mueller matrix polarimetry is built, and the samples are made by referring to the typical conical frustum windows in submersibles. By pressurizing different pressures on the samples, we can find the changes of their Mueller matrix images and further derived polarization parameters. The results show that th

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17

Zhao, Jun, Ming Jiang, Tiange Zhuang, and Ge Wang. "Minimum detection window and inter-helix PI-line with triple-source helical cone-beam scanning." Journal of X-Ray Science and Technology: Clinical Applications of Diagnosis and Therapeutics 14, no. 2 (2006): 95–107. http://dx.doi.org/10.3233/xst-2006-00153.

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In this paper, we propose a helical cone-beam scanning configuration of triple symmetrically located X-ray sources, and study minimum detection windows to extend the traditional Tam-Danielsson window for exact image reconstruction. For three longitudinally displaced scanning helices of the same radius and a source location on any helix, the corresponding minimum detection window is bounded by the most adjacent turns respectively selected from the other two helices. The height of our proposed minimum detector window is only 1/3 of that in the single helix case. Associated with proposed minimum

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18

Malihi, Shirin, Mohammad Valadan Zoej, Michael Hahn, and Mehdi Mokhtarzade. "Window Detection from UAS-Derived Photogrammetric Point Cloud Employing Density-Based Filtering and Perceptual Organization." Remote Sensing 10, no. 8 (2018): 1320. http://dx.doi.org/10.3390/rs10081320.

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Point clouds with ever-increasing volume are regular data in 3D city modelling, in which building reconstruction is a significant part. The photogrammetric point cloud, generated from UAS (Unmanned Aerial System) imagery, is a novel type of data in building reconstruction. Its positive characteristics, alongside its challenging qualities, provoke discussions on this theme of research. In this paper, patch-wise detection of the points of window frames on facades and roofs are undertaken using this kind of data. A density-based multi-scale filter is devised in the feature space of normal vectors

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Ali, Abdulrazzak, Nurul Akmar Emran, Safiza Suhana Kamal Baharin, et al. "Improving the efficiency of clustering algorithm for duplicates detection." Indonesian Journal of Electrical Engineering and Computer Science 30, no. 3 (2023): 1586. http://dx.doi.org/10.11591/ijeecs.v30.i3.pp1586-1595.

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Clustering method is a technique used for comparisons reduction between the candidates records in the duplicate detection process. The process of clustering records is affected by the quality of data. The more error-free the data, the more efficient the clustering algorithm, as data errors cause data to be placed in incorrect groups. Window algorithms suffer from the window size. The larger the window, the greater the number of unnecessary comparisons, and the smaller the window size may prevent the detection of duplicates that are supposed to be within the window. In this paper, we propose a

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Abdulrazzak, Ali, Akmar Emran Nurul, Suhana Kamal Baharin Safiza, et al. "Improving the efficiency of clustering algorithm for duplicates detection." Improving the efficiency of clustering algorithm for duplicates detection 30, no. 3 (2023): 1586–95. https://doi.org/10.11591/ijeecs.v30.i3.pp1586-1595.

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Clustering method is a technique used for comparisons reduction between the candidates records in the duplicate detection process. The process of clustering records is affected by the quality of data. The more error-free the data, the more efficient the clustering algorithm, as data errors cause data to be placed in incorrect groups. Window algorithms suffer from the window size. The larger the window, the greater the number of unnecessary comparisons, and the smaller the window size may prevent the detection of duplicates that are supposed to be within the window. In this paper, we propose a

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Nasir, Muflah, Muhammad Shahid Farid, Zobia Suhail, and Muhammad Hassan Khan. "Optimal Thresholding for Multi-Window Computed Tomography (CT) to Predict Lung Cancer." Applied Sciences 13, no. 12 (2023): 7256. http://dx.doi.org/10.3390/app13127256.

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Lung cancer is the world’s second-largest cause of cancer mortality. Patients’ lives can be saved if this malignancy is detected early. Doctors, however, encounter difficulties in detecting cancer in computed tomography (CT) images. In recent years, significant research has been devoted to producing automated lung nodule detection methods that can help radiologists. Most of them use only the lung window in their analysis and generally do not consider the mediastinal windows, which, according to recent research, carry important information. In this paper, we propose a simple yet effective algor

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Sriram T.V.S, Navya K, Jaya Siva Balaji Y, Aftab Aalam MD, Girendra P, and Sai Deepak M. "Voice – command detection system for remote window management using mobile and desktop app." World Journal of Advanced Engineering Technology and Sciences 15, no. 1 (2025): 2519–24. https://doi.org/10.30574/wjaets.2025.15.1.0395.

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Smart home automation has expanded rapidly in recent years, particularly incorporating voice and IoT. The project aims to develop a Voice-Controlled IoT System for Managing Windows Remotely that controls window functions, such as open, close, and adjust for the mobile and desktop apps. This system is a combination of some IoT hardware components and cloud services that enable end-to-end communication between user devices and the window control unit of the building. Based on voice assistants (such as Google Assistant or Proprietary Voice Recognition models) so that system captures voice command

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Fernández-López, Lucía, María Falcón Romero, Gemma Prieto-Bonete, et al. "Improving detection window of scopolamine." Forensic Science International 287 (June 2018): e10. http://dx.doi.org/10.1016/j.forsciint.2018.04.011.

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Farheen and Rajeev Kumar. "Sliding Window-Based Anomaly Detection." Procedia Computer Science 258 (2025): 2520–29. https://doi.org/10.1016/j.procs.2025.04.514.

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Zhu, Jinlin, Xingke Gao, and Zheng Zhang. "Attention-Based Two-Dimensional Dynamic-Scale Graph Autoencoder for Batch Process Monitoring." Processes 12, no. 3 (2024): 513. http://dx.doi.org/10.3390/pr12030513.

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Traditional two-dimensional dynamic fault detection methods describe nonlinear dynamics by constructing a two-dimensional sliding window in the batch and time directions. However, determining the shape of a two-dimensional sliding window for different phases can be challenging. Samples in the two-dimensional sliding windows are assigned equal importance before being utilized for feature engineering and statistical control. This will inevitably lead to redundancy in the input, complicating fault detection. This paper proposes a novel method named attention-based two-dimensional dynamic-scale gr

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Hussein, Ameer M., Adel A. Obed, Rana H. A. Zubo, et al. "Detection and Diagnosis of Stator and Rotor Electrical Faults for Three-Phase Induction Motor via Wavelet Energy Approach." Electronics 11, no. 8 (2022): 1253. http://dx.doi.org/10.3390/electronics11081253.

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This paper presents a fault detection method in three-phase induction motors using Wavelet Packet Transform (WPT). The proposed algorithm takes a frame of samples from the three-phase supply current of an induction motor. The three phase current samples are then combined to generate a single current signal by computing the Root Mean Square (RMS) value of the three phase current samples at each time stamp. The resulting current samples are then divided into windows of 64 samples. Each resulting window of samples is then processed separately. The proposed algorithm uses two methods to create win

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Cao, Shun, and Hiroki Sayama. "Detecting Dynamic States of Temporal Networks Using Connection Series Tensors." Complexity 2020 (December 21, 2020): 1–15. http://dx.doi.org/10.1155/2020/9649310.

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Many temporal networks exhibit multiple system states, such as weekday and weekend patterns in social contact networks. The detection of such distinct states in temporal network data has recently been studied as it helps reveal underlying dynamical processes. A commonly used method is network aggregation over a time window, which aggregates a subsequence of multiple network snapshots into one static network. This method, however, necessarily discards temporal dynamics within the time window. Here we propose a new method for detecting dynamic states in temporal networks using connection series

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Perkins, Raymond T., David D. Allred, Larry V. Knight, and James M. Thorne. "Design of High Performance Soft X-ray Windows." Advances in X-ray Analysis 33 (1989): 615–22. http://dx.doi.org/10.1154/s0376030800020085.

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X-ray windows are used in sources and detectors to separate the neighborhood of the x-ray generation or detection from the use environment. While each use has its own requirements, there are some principles that should be used in designing an optimal x-ray window. Because x rays are absorbed to some extent by all materials, minimizing absorption is one criterion in preparing windows. Also, for most uses there is a pressure difference across the window so that ensuring pinhole-free structure and sufficient mechanical strength to support the differential is another criterion for window design. T

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Zhang, Yaowen, Linsheng Huo, and Hongnan Li. "Automated Recognition of a Wall between Windows from a Single Image." Journal of Sensors 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/7051931.

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To avoid the time-consuming, costly, and expert-dependent traditional assessment of earthquake damaged structures, image-based automatic methods have been developed recently. Since automated recognition of structure elements is the basis by which these methods achieve automatic detection, this study proposes a method to recognize the wall between windows from a single image automatically. It begins from detection of line segments with further selection and linking to obtain longer line segments. The color features of the two sides of each long line segment are employed to pick out line segment

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Wu, Lu, Xiaoyun Xie, and Yinglong Wang. "ECG Enhancement and R-Peak Detection Based on Window Variability." Healthcare 9, no. 2 (2021): 227. http://dx.doi.org/10.3390/healthcare9020227.

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In ECG applications, the correct recognition of R-peaks is extremely important for detecting abnormalities, such as arrhythmia and ventricular hypertrophy. In this work, a novel ECG enhancement and R-peak detection method based on window variability is presented, and abbreviated as SQRS. Firstly, the ECG signal corrupted by various high or low-frequency noises is denoised by moving-average filtering. Secondly, the window variance transform technique is used to enhance the QRS complex and suppress the other components in the ECG, such as P/T waves and noise. Finally, the signal, converted by wi

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Voloshyn, Denys, and Serhii Bulba. "Intelligent UAV Spoofing Detection Method." Advanced Information Systems 6, no. 1 (2022): 88–96. http://dx.doi.org/10.20998/2522-9052.2022.1.15.

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The paper presents an intelligent method for detecting UAV spoofing. A distinctive feature of the method is the use of subtrajectory calculation technology based on visual odometry subtrajectories and GPS positions in a sliding window, taking into account the intelligent estimation of the optical flow and the formation of UAV “Ego-movement” descriptors. In the course of the study, an analysis and comparative studies of a wide range of UAV spoofing methods were carried out, the most frequently recommended and practically used methods were identified. The conclusion is made about the relevance o

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Zhang, Yanshun, Yunqiang Xiong, Yixin Wang, Chunyu Li, and Zhanqing Wang. "An Adaptive Dual-Window Step Detection Method for a Waist-Worn Inertial Navigation System." Journal of Navigation 69, no. 3 (2015): 659–72. http://dx.doi.org/10.1017/s0373463315000867.

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In waist-worn pedestrian navigation systems, the periodic vertical acceleration peak signal at body centre of gravity is widely used for detecting steps. Due to vibration and waist shaking interference, accelerometer output signals contain false peaks and thus reduce step detection accuracy. This paper analyses the relationship between periodic acceleration at pedestrian centre of gravity and walking stance during walking. An adaptive dual-window step detection method is proposed based on this analysis. The peak signal is detected by a dual-window and the window length is adjusted according to

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Noori-Asl, Mahsa, and Hoora Hosseinifar. "Reduction of contribution of scattered photons by optimization of energy window settings in ²⁰¹Tl SPECT imaging: a simulation study." Journal of Instrumentation 17, no. 08 (2022): P08017. http://dx.doi.org/10.1088/1748-0221/17/08/p08017.

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Abstract Introduction and Objectives: detection of Compton scattered photons is one of the effective factors in reducing the quality of SPECT images. The aim of this study is to reduce the contribution of scattered counts included in the main energy window for 201Tl SPECT imaging in two steps: first step, by determining the location and width of the optimal main energy window, and second step, by using the optimal correction methods. Materials and Methods: in this study, the Monte Carlo program is used to simulate the required phantoms (a cylindrical phantom consist of two small cylinders with

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Sharma, Surya, and Adam Hoover. "Top-Down Detection of Eating Episodes by Analyzing Large Windows of Wrist Motion Using a Convolutional Neural Network." Bioengineering 9, no. 2 (2022): 70. http://dx.doi.org/10.3390/bioengineering9020070.

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In this work, we describe a new method to detect periods of eating by tracking wrist motion during everyday life. Eating uses hand-to-mouth gestures for ingestion, each of which lasts a few seconds. Previous works have detected these gestures individually and then aggregated them to identify meals. The novelty of our approach is that we analyze a much longer window (0.5–15 min) using a convolutional neural network. Longer windows can contain other gestures related to eating, such as cutting or manipulating food, preparing foods for consumption, and resting between ingestion events. The context

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Song, Zishen, Dong Wang, Lizhong Xiao, Yongjian Zhu, Guogang Cao, and Yuli Wang. "DaylilyNet: A Multi-Task Learning Method for Daylily Leaf Disease Detection." Sensors 23, no. 18 (2023): 7879. http://dx.doi.org/10.3390/s23187879.

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Timely detection and management of daylily diseases are crucial to prevent yield reduction. However, detection models often struggle with handling the interference of complex backgrounds, leading to low accuracy, especially in detecting small targets. To address this problem, we propose DaylilyNet, an object detection algorithm that uses multi-task learning to optimize the detection process. By incorporating a semantic segmentation loss function, the model focuses its attention on diseased leaf regions, while a spatial global feature extractor enhances interactions between leaf and background

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Khaki, Saeed, Hieu Pham, Ye Han, Andy Kuhl, Wade Kent, and Lizhi Wang. "Convolutional Neural Networks for Image-Based Corn Kernel Detection and Counting." Sensors 20, no. 9 (2020): 2721. http://dx.doi.org/10.3390/s20092721.

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Precise in-season corn grain yield estimates enable farmers to make real-time accurate harvest and grain marketing decisions minimizing possible losses of profitability. A well developed corn ear can have up to 800 kernels, but manually counting the kernels on an ear of corn is labor-intensive, time consuming and prone to human error. From an algorithmic perspective, the detection of the kernels from a single corn ear image is challenging due to the large number of kernels at different angles and very small distance among the kernels. In this paper, we propose a kernel detection and counting m

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Xu, Ying, Guofeng Li, Zeyu Li, et al. "Smartphone-Based Unconstrained Step Detection Fusing a Variable Sliding Window and an Adaptive Threshold." Remote Sensing 14, no. 12 (2022): 2926. http://dx.doi.org/10.3390/rs14122926.

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Step detection for smartphones plays an important role in the pedestrian dead reckoning (PDR) for indoor positioning. Aiming at the problem of low step detection accuracy of smartphones in complex unconstrained states in PDR, smartphone-based unconstrained step detection method fusing a variable sliding window and an adaptive threshold is proposed. In this method, the dynamic updating algorithm of a peak threshold is developed, and the minimum peak value filtered after a sliding window filter is used as the adaptive peak threshold, which solves the problem that the peak threshold of different

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Lee, Jong-Won. "Workflow for Window Composition Detection to Aid Energy-Efficient Renovation in Low-Income Housing in Korea." Buildings 14, no. 4 (2024): 966. http://dx.doi.org/10.3390/buildings14040966.

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Enhancing the efficiency of windows is important for improving the energy efficiency of buildings. The Korean government has performed numerous building renovation projects to reduce greenhouse gas emissions and mitigate energy poverty. To reduce the costs and manpower requirements of conventional field surveys, this study presents a deep-learning model to examine the insulation performance of windows using photographs taken in low-income housing. A smartphone application using crowdsourcing was developed for data collection. The insulation performance of windows was determined based on U-valu

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Byrski, Jędrzej, and Witold Byrski. "A double window state observer for detection and isolation of abrupt changes in parameters." International Journal of Applied Mathematics and Computer Science 26, no. 3 (2016): 585–602. http://dx.doi.org/10.1515/amcs-2016-0041.

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Abstract The paper presents a new method for diagnosis of a process fault which takes the form of an abrupt change in some real parameter of a time-continuous linear system. The abrupt fault in the process real parameter is reflected in step changes in many parameters of the input/output model as well as in step changes in canonical state variables of the system. Detection of these state changes will enable localization of the faulty parameter in the system. For detecting state changes, a special type of exact state observer will be used. The canonical state will be represented by the derivati

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Zhang, Tao, and Haibin Chen. "A Review of Research on Testing Methods for Window Air Tightness, Water Tightness, and Wind Pressure Resistance Performance." Academic Journal of Science and Technology 14, no. 3 (2025): 39–42. https://doi.org/10.54097/vnccjz63.

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This paper comprehensively reviews testing methods for window air tightness, water tightness, and wind pressure resistance. It elaborates on the importance and basic concepts of these three performance aspects, systematically introduces corresponding detection standards, methods, and specific procedures, and analyzes critical points in the testing process. The aim is to provide a comprehensive reference for the door and window performance testing field, promote quality improvement of windows and doors, and advance the development of related industries.

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Weinberg, Graham V. "An Invariant Sliding Window Detection Process." IEEE Signal Processing Letters 24, no. 7 (2017): 1093–97. http://dx.doi.org/10.1109/lsp.2017.2710344.

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Hershler, O., T. Golan, S. Bentin, and S. Hochstein. "The wide window of face detection." Journal of Vision 10, no. 10 (2010): 21. http://dx.doi.org/10.1167/10.10.21.

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Neuhausen, Marcel, and Markus König. "Automatic window detection in facade images." Automation in Construction 96 (December 2018): 527–39. http://dx.doi.org/10.1016/j.autcon.2018.10.007.

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OSTERWEIL, NEIL. "Longer ICD Detection Window Prevented Shocks." Cardiology News 10, no. 6 (2012): 16. https://doi.org/10.1016/s1544-8800(12)70168-9.

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M., Sathish, K. Harikrishnan V., and A. RamaKrishan |. P. Kavin Prof. "Automatic Car Window Opening System by using Oxygen and Sound Sensor." International Journal of Trend in Scientific Research and Development 2, no. 3 (2018): 272–75. https://doi.org/10.31142/ijtsrd10892.

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Now a day's maximum car interrupt on air condition will be attached that is condition may be reduction on oxygen in vehicle full closed system, the oxygen which detecting on less oxygen in vehicle will be there on human being automatic windows open system. The present invention comprises a system and method for automatic opening and closing system on the car windows. This method includes a higher sound and less oxygen element detection sensor which may human being safety consideration work in windows opening system the interior of the automobile by contacting the material when the automobi

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Zhang, Qiang, Jianze Liu, and Xuedong Jiang. "Lane Detection Algorithm in Curves Based on Multi-Sensor Fusion." Sensors 23, no. 12 (2023): 5751. http://dx.doi.org/10.3390/s23125751.

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Identifying lane markings is a key technology in assisted driving and autonomous driving. The traditional sliding window lane detection algorithm has good detection performance in straight lanes and curves with small curvature, but its detection and tracking performance is poor in curves with larger curvature. Large curvature curves are common scenes in traffic roads. Therefore, in response to the problem of poor lane detection performance of traditional sliding window lane detection algorithms in large curvature curves, this article improves the traditional sliding window algorithm and propos

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Rahman, Fathu, Taufik Edy Sutanto, and Nina Fitriyati. "Web Traffic Anomaly Detection using Stacked Long Short-Term Memory." InPrime: Indonesian Journal of Pure and Applied Mathematics 3, no. 2 (2021): 112–21. http://dx.doi.org/10.15408/inprime.v3i2.21879.

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AbstractAn example of anomaly detection is detecting behavioral deviations in internet use. This behavior can be seen from web traffic, which is the amount of data sent and received by people who visit websites. In this study, anomaly detection was carried out using stacked Long Short-Term Memory (LSTM). First, stacked LSTM is used to create forecasting models using training data. Then the error value generated from the prediction on test data is used to perform anomaly detection. We conduct hyperparameter optimization on sliding window parameter. Sliding window is a sub-sequential data of tim

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Gao, Liyan, and Rongfang Zong. "Design of Intelligent Window Automatic Monitoring System Based on Microcontroller Control." Journal of Electronic Research and Application 8, no. 4 (2024): 34–40. http://dx.doi.org/10.26689/jera.v8i4.7922.

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To ensure the safety of residents’ lives and property by using automatic opening and closing of ordinary windows, this article designs an intelligent window automatic monitoring system. The article proposes a software and hardware design scheme for the system, which comprises a microcontroller control module, temperature and humidity detection module, harmful gas detection module, rainfall detection module, human thermal radiation induction module, Organic Light-Emitting Diode (OLED) display module, stepper motor drive module, Wi-Fi communication module, etc. Users use this system to monitor e

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Whalen, Daniel J., and D. Clark Turner. "Effect of X-ray Tube Window Thickness on Detection Limits for Light Elements in XRF Analysis." Advances in X-ray Analysis 38 (1994): 299–305. http://dx.doi.org/10.1154/s0376030800017924.

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Abstract Widespread interest in light element analysis using XRF has stimulated the development of thin x-ray tube windows. Thinner windows enhance the soft x-ray output of the tube, which more efficiently excite the light elements in the sample. A computer program that calculates the effect of window thickness on light element sample fluorescence has been developed. The code uses an NIST algorithm to calculate the x-ray tube spectrum given various tube parameters such as beryllium window thickness, operating voyage, anode composition, and take-off angle. The interaction of the tube radiation

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Gâlmeanu, Honorius, and Răzvan Andonie. "Concept Drift Adaptation with Incremental–Decremental SVM." Applied Sciences 11, no. 20 (2021): 9644. http://dx.doi.org/10.3390/app11209644.

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Data classification in streams where the underlying distribution changes over time is known to be difficult. This problem—known as concept drift detection—involves two aspects: (i) detecting the concept drift and (ii) adapting the classifier. Online training only considers the most recent samples; they form the so-called shifting window. Dynamic adaptation to concept drift is performed by varying the width of the window. Defining an online Support Vector Machine (SVM) classifier able to cope with concept drift by dynamically changing the window size and avoiding retraining from scratch is curr

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