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Journal articles on the topic 'Processing window'

Author: Grafiati

Published: 14 July 2021

Last updated: 11 February 2022

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1

Pachauri, Rahul, Rajiv Saxena, and Sanjeev N. Sharma. "Studies on Z-Window Based FIR Filters." ISRN Signal Processing 2013 (September 1, 2013): 1–8. http://dx.doi.org/10.1155/2013/148646.

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As per classification of the window functions, the Z-windows are grouped in the category of steerable side-lobe dip (SSLD) windows. In this work, the application of these windows for the design of FIR filters with improved filter parameters has been explored. The numbers of dips with their respective positions in the side-lobe region have been compositely used to tailor the window shape. Filter design relationships have been established and included in this paper. Simultaneously, an application of these Z-window based FIR filters in designing two-channel quadrature mirror filter (QMF) bank has been presented. Better values of reconstruction and aliasing errors have been achieved in contrast to the Kaiser window based QMF bank.

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2

Mbachu, C. B. "Height Adjustable Sine (HAS) Window Function for Impulse Response Modification of Signal Processing Systems." European Journal of Engineering Research and Science 5, no. 3 (March 27, 2020): 367–74. http://dx.doi.org/10.24018/ejers.2020.5.3.1443.

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A widow function, in signal processing and statistics, is a mathematical function that has zero values outside its chosen interval or limit of sequence, normally symmetric around the middle of the interval. Usually the middle of the window is either maximum or near maximum and tappers smoothly as it moves away to the sides. When another function or sequence of data is mathematically multiplied by the window function the product assumes the appearance and characteristics of the window function. That is, the product is also zero-valued outside the interval and tapering from middle to the sides. The impulse response data of some systems used in signal processing truncate suddenly when being designed. Window functions convert the sudden truncation of these impulse response data to gradual truncation. Without this gradual truncation the processing system will degrade the integrity of complex signals when they are applied to them; the degradation appears in form of signal distortions. Windows are used to weight these impulse response data so as to reduce the degradation and distortions. Several windows are in existence and they include Hamming, rectangular, Han, Kaiser, Triangular, Blackman, Sine, Blackman-Harris, Gaussian, Doph-Chebyshev and Lanczos, windows. Others are Parzen, Nuttall, flat top, and Turkey, windows and others. The characteristics of the signal to be processed, types of systems to be implemented and quality of outputs desired determine the best window to weight any particular impulse response data. In this work a new window referred to as Height Adjustable Sine (HAS) window is developed to join the list of the existing windows. The quality of the window is tested by analysing its amplitude, magnitude and phase responses in frequency domain. Result shows that the window is stable and linear.

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3

Mbachu, C. B. "Height Adjustable Triangular (HAT) Window Function for Impulse Response Modification of Signal Processing Systems." European Journal of Engineering Research and Science 5, no. 3 (March 27, 2020): 358–66. http://dx.doi.org/10.24018/ejers.2020.5.3.1442.

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A widow function, in signal processing and statistics, is a mathematical function that has zero values outside its chosen interval or limit of sequence, normally symmetric around the middle of the interval. Usually the middle of the window is either maximum or near maximum and tappers smoothly as it moves away to the sides. When another function or sequence of data is mathematically multiplied by the window function it forces the product to assume its nature of zero-value outside the interval and tapering from middle to the sides. Windows are finite functions and their main function is to modify an infinite impulse response sequence so as to make it finite within its chosen interval in system design. Several windows are in existence and they include Hamming, rectangular, Han, Kaiser, Triangular, Blackman, Sine, Blackman-Harris, Gaussian, Doph-Chebyshev and Lanczos, windows. Others are Parzen, Nuttall, flat top, Turkey, windows and many more. The window to apply in the design depends on the characteristics of the signal to be processed, types of system to be implemented and quality of output desired. In this paper, a new window called Height Adjustable triangular (HAT) window function is developed and added to the list of windows for signal processing system designs. The effectiveness of the window is tested by examining its characteristics. The adjustment parameter varies the amplitude or height of the window. Result shows that it is stable and linear.

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4

Wu, Yu-Bin, and Ping Ji. "Due-Window Assignment Scheduling with Variable Job Processing Times." Scientific World Journal 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/740750.

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We consider a common due-window assignment scheduling problem jobs with variable job processing times on a single machine, where the processing time of a job is a function of its position in a sequence (i.e., learning effect) or its starting time (i.e., deteriorating effect). The problem is to determine the optimal due-windows, and the processing sequence simultaneously to minimize a cost function includes earliness, tardiness, the window location, window size, and weighted number of tardy jobs. We prove that the problem can be solved in polynomial time.

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Lal, Devesh Kumar, and Ugrasen Suman. "SBASH Stack Based Allocation of Sheer Window Architecture for Real Time Stream Data Processing." International Journal of Data Analytics 1, no. 1 (January 2020): 1–21. http://dx.doi.org/10.4018/ijda.2020010101.

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The processing of real-time data streams is complex with large number of volume and variety. The volume and variety of data streams enhances a number of processing units to run in real time. The required number of processing units used for processing data streams are lowered by using a windowing mechanism. Therefore, the appropriate size of window selection is vital for stream data processing. The coarse size window will directly affect the overall processing time. On the other hand, a finely sized window has to deal with an increased number of management costs. In order to manage such streams of data, we have proposed a SBASH architecture, which can be helpful for determining a unipartite size of a sheer window. The sheer window reduces the overall latency of data stream processing by a certain extent. The time complexity to process such sheer window is equivalent to w log n w. These windows are allocated and retrieved in a stack-based manner, where stacks ≥ n, which is helpful in reducing the number of comparisons made during retrieval.

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6

Shaikh, Salman Ahmed, Akiyoshi Matono, and Kyoung-Sook Kim. "A Distance-Window Approach for the Continuous Processing of Spatial Data Streams." International Journal of Multimedia Data Engineering and Management 11, no. 2 (April 2020): 16–30. http://dx.doi.org/10.4018/ijmdem.2020040102.

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Real-time and continuous processing of citywide spatial data is an essential requirement of smart cities to guarantee the delivery of basic life necessities to its residents and to maintain law and order. To support real-time continuous processing of data streams, continuous queries (CQs) are used. CQs utilize windows to split the unbounded data streams into finite sets or windows. Existing stream processing engines either support time-based or count-based windows. However, these are not much useful for the spatial streams containing the trajectories of moving objects. Hence, this paper presents a distance-window based approach for the processing of spatial data streams, where the unbounded streams can be split with respect to the trajectory length. Since the window operation involves repeated computation, this work presents two incremental distance-based window approaches to avoid the repetition. A detailed experimental evaluation is presented to prove the effectiveness of the proposed incremental distance-based windows.

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7

Luo, Cheng Xin, and En Min Feng. "Multiple Common Due-Window Assignment Based on Common Flow Allowance and Resource-Dependent Processing Times." Applied Mechanics and Materials 644-650 (September 2014): 2026–29. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.2026.

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This paper studies a multiple common due-window assignment problem on a single machine. The job-dependent due-windows are obtained based on common flow allowance criteria. We assume that the processing time of a job is controllable by the resource amount assigned to it. The objective is to find the optimal size and location of the multiple common due-windows, the set of jobs assigned to each due window, the sequence of jobs and resource allocation scheme to minimize a cost function based on the window size and location, earliness and tardiness of jobs and resource cost. We propose an optimal algorithm to solve the problem.

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8

Foster, James, Michael Bevis, and Steven Businger. "GPS Meteorology: Sliding-Window Analysis*." Journal of Atmospheric and Oceanic Technology 22, no. 6 (June 1, 2005): 687–95. http://dx.doi.org/10.1175/jtech1717.1.

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Abstract The sliding-window technique uses a moving time window to select GPS data for processing. This makes it possible to routinely incorporate the most recently collected data and generate estimates for atmospheric delay or precipitable water in (near) real time. As a consequence of the technique several estimates may be generated for each time epoch, and these multiple estimates can be used to explore and analyze the characteristics of the atmospheric estimates and the effect of the processing model and parameters. Examples of some of the analyses that can be undertaken are presented. Insights into the phenomenology of the atmospheric estimates provided by sliding-window analysis permit the fine-tuning of the GPS processing as well as the possibility of both improving the accuracy of the near-real-time estimates themselves and constraining the errors associated with them. The overlapping data windows and the multiple estimates that characterize the sliding-window method can lead to ambiguity in the meaning of many terms and expressions commonly used in GPS meteorology. In order to prevent confusion in discussions of sliding-window processing, a nomenclature is proposed that formalizes the meaning of the primary terms and defines the geometric and physical relationships between them.

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Wise, Kevin, Saleem Alhabash, and Petya Eckler. "“Window” Shopping Online: Cognitive Processing of General and Specific Product Windows." Journal of Interactive Advertising 13, no. 2 (July 3, 2013): 88–96. http://dx.doi.org/10.1080/15252019.2013.826550.

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10

Dong, Yanping, and Ping Li. "Interpreting: A window into bilingual processing." Bilingualism: Language and Cognition 23, no. 4 (May 22, 2020): 703–5. http://dx.doi.org/10.1017/s1366728920000346.

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11

Adams, J. W. "A new optimal window (signal processing)." IEEE Transactions on Signal Processing 39, no. 8 (1991): 1753–69. http://dx.doi.org/10.1109/78.91146.

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12

Trofimiuk, Grigorii, and Peter Trifonov. "Window Processing of Binary Polarization Kernels." IEEE Transactions on Communications 69, no. 7 (July 2021): 4294–305. http://dx.doi.org/10.1109/tcomm.2021.3072730.

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13

Hariyama, Masanori, and Michitaka Kameyama. "Stereo Vision VLSI Processor Based on Pixel-Serial and Window-Parallel Architecture." Journal of Robotics and Mechatronics 12, no. 5 (October 20, 2000): 521–26. http://dx.doi.org/10.20965/jrm.2000.p0521.

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This article presents a stereo-matching algorithm to establish reliable correspondence between images by selecting a desirable window size for SAD (Sum of Absolute Differences) computation. In SAD computation, parallelism between pixels in a window changes depending on its window size, while parallelism between windows is predetermined by the input-image size. Based on this consideration, a window-parallel and pixel-serial architecture is proposed to achieve 100% utilization of processing elements. Performance of the VLSI processor is evaluated to be more than 10,000 times higher than that of a general-purpose processor.

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14

Samad, Md Abdus, Jia Uddin, and Md Razu Ahmed. "FIR Filter Design Using Modified Lanczos Window Function." Advanced Materials Research 566 (September 2012): 49–56. http://dx.doi.org/10.4028/www.scientific.net/amr.566.49.

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Attenuated side lobe peak in the range of around ~-45dB is required in many applications of signal processing and measurements. However, the problem is usual window based FIR filter design lies in its side lobes amplitudes that are higher than the requirement of application. We propose a modified Lanczos window function by heuristic by examining the Lanczos window, which has better performance like equiripple, minimum side lobe compared to the several commonly used windows. The proposed window has slightly larger main lobe width of the commonly used Hamming window, while featuring 5.1~18.5 dB smaller side lobe peak. The proposed modified Lanczos window maintains its maximum side lobe peak about -55.2~-51.9 dB compared to -39~-36.7 dB of Hamming window for M=10~14, while offering roughly equal main lobe width. Our simulated results also show significant performance upgrading of the proposed modified Lanczos window compared to the Kaiser, Gaussian, and Lanczos windows. The proposed modified Lanczos window also shows better performance than Dolph-Chebyshev window. Finally, the example of designed low pass FIR filter confirms the efficiency of the proposed modified Lanczos window.

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Werner, Tobias, and Thomas Brinkhoff. "Window Operators for Processing Spatio-Temporal Data Streams on Unmanned Vehicles." AGILE: GIScience Series 1 (July 15, 2020): 1–23. http://dx.doi.org/10.5194/agile-giss-1-21-2020.

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Abstract. Unmanned aerial and submersible vehicles are used in an increasing number of applications especially for data collection in misanthropic environments. During a mission, such vehicles generate multiple spatio-temporal data streams suitable to be processed by data stream management systems (DSMS). The main approach of a DSMS is limiting the elements of a stream by using sliding and tilting windows with time intervals as temporal condition. However, due to varying vehicle speed and limited on-board resources, such temporal windows do not provide adequate support for spatio-temporal problems. For solving this problem, we propose a set of six new spatio-temporal window operators in this paper. This set comprises of sliding distance, tilting distance, tilting waypoint, session distance, jumping distance and an area window to limit stream elements based on spatial conditions. Each of the listed operators provides an individual behaviour to support sophisticated applications like spatial interpolation and forecasting. An evaluation based on an example trajectory shows the benefit of the presented operators for spatio-temporal applications.

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Luo, Cheng Xin. "Optimal Due-Window Assignment Based on Common Flow Allowance under Linear Deteriorating and Resource-Dependent Processing Times." Applied Mechanics and Materials 344 (July 2013): 275–78. http://dx.doi.org/10.4028/www.scientific.net/amm.344.275.

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This paper studies a due-window assignment problem on a single machine. The job-dependent due-windows are obtained by the common flow allowance criterion. We assume that the processing time of a job is a linear function of its starting time and decreasing function of the resource amount assigned to it. The objective is to find the optimal size and location of the due-windows, the sequence of jobs and resource allocation scheme to minimize a cost function based on the window size and location, the earliness and tardiness of jobs and resource cost. We propose an algorithm to solve the problem.

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KIM, Hyeon-Gyu, Woo-Lam KANG, and Myoung-Ho KIM. "Efficient Window Processing over Disordered Data Streams." IEICE Transactions on Information and Systems E93-D, no. 3 (2010): 635–38. http://dx.doi.org/10.1587/transinf.e93.d.635.

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18

Chen, Chan Tung, and Tien Shou Lei. "The Processing Window for Austempering Ductile Iron." Materials Transactions, JIM 40, no. 1 (1999): 82–85. http://dx.doi.org/10.2320/matertrans1989.40.82.

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19

Filipovic-Djurdjevic, Dusica, Petar Milin, and Laurie Feldman. "Bi-alphabetism: A window on phonological processing." Psihologija 46, no. 4 (2013): 421–38. http://dx.doi.org/10.2298/psi1304421f.

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In Serbian, lexical decision latencies to words composed of letters that exist in both the Roman and Cyrillic alphabets (some of which have different phonemic interpretations in each) are slower than for the unique alphabet transcription of those same words. In this study, we use the effect of phonological ambiguity to explore the time course of semantic facilitation. Targets are either the phonologically ambiguous forms (e.g., PETAK meaning ?Friday? when pronounced as a Roman string /petak/ but without meaning when pronounced in Cyrillic as /retak/) or the unique alphabet transcription of the same word (?ETAK). We manipulate alphabet match and semantic relatedness of prime to target. In addition to replicating slowing due to phonological ambiguity, we show 1) greater alphabet switch cost for bivalent then for unambiguous targets as well as for unrelated then for related prime-target pairs and 2) greater semantic facilitation as the number of shared common letters between prime and target increases. Results reveal the interaction of phonological and semantic processes in Serbian. The findings are discussed in terms of a triangle model of language processing, which hypothesizes a division of labor between an orthography-to-semantics, and an orthographyto-phonology-to-semantics route and their simultaneous contribution to activation of meaning.

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20

Kulkarni, R. G. "Synthesis of a new signal processing window." Electronics Letters 55, no. 20 (October 2019): 1108–10. http://dx.doi.org/10.1049/el.2019.2116.

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21

Berard, Mark T., and Don A. Ventresca. "Processing window in impact-modified rigid PVC." Journal of Vinyl and Additive Technology 4, no. 3 (September 1998): 174–78. http://dx.doi.org/10.1002/vnl.10037.

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22

Tian-Hu Yu and S. Mitra. "A new two-dimensional window." IEEE Transactions on Acoustics, Speech, and Signal Processing 33, no. 4 (August 1985): 1058–61. http://dx.doi.org/10.1109/tassp.1985.1164668.

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23

M. Alatwi, Aadel, Ahmed Nabih Zaki Rashed, Ahmed M. El-Eraki, and Iraj Sadegh Amiri. "Best candidate routing algorithms integrated with minimum processing time and low blocking probability for modern parallel computing systems." Indonesian Journal of Electrical Engineering and Computer Science 19, no. 2 (August 1, 2020): 847. http://dx.doi.org/10.11591/ijeecs.v19.i2.pp847-854.

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<p>This study has clarified the best candidate routing algorithms integrated with minimum processing times and low blocking probabilities for modern parallel computing systems. Different methods were employed, such as the fast window method (FWM), fast bitwise window method (FBWM), and fast improved window method (FIWM), to upgrade the processing time and reduce the network delay time. In addition, different algorithms were studied such as the fast window ascending, the fast window descending, the fast window sequential algorithm, and the fast window sequential down algorithms; these were studied to show the numerical results of the networks’ blocking probabilities, processing times, and delay times.</p>

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Liu, Shang-Chia. "Common Due-Window Assignment and Group Scheduling with Position-Dependent Processing Times." Asia-Pacific Journal of Operational Research 32, no. 06 (December 2015): 1550045. http://dx.doi.org/10.1142/s0217595915500451.

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This paper investigates a single-machine scheduling problem involving both the due-window assignment and position-dependent processing times under a group technology environment. By position-dependent processing times, we mean that the processing time of a job is dependent of its processing position in the job sequence within the group it belongs to. A setup time is incurred whenever the single machine transfers job processing from a group to another group. Each group is assigned an assignable common due-window. A job completed earlier (respectively, later) than the common due-window of the group it belongs to will incur an earliness (respectively, tardiness) penalty. The objective is to determine the optimal group sequence, the optimal job sequence, and the optimal due-window assignment so as to minimize the total cost including the earliness and tardiness (or weighted number of tardy jobs) penalties, black and the due-window starting time and due-window size costs. We show that both the problems can be solved in polynomial times.

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25

Wang, Hua, and Min-Fang Ren. "Electrical properties of Pt/SrBi2Ta2O9/Bi4Ti3O12/p-Si heterostructure prepared by sol-gel processing." Journal of Materials Research 21, no. 7 (July 1, 2006): 1782–86. http://dx.doi.org/10.1557/jmr.2006.0218.

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Low-temperature processing as low as 550–700 °C of Pt/SrBi2Ta2O9 (SBT)/Bi4Ti3O12 (BIT)/p-Si heterostructure has been performed by a sol-gel method. The effects of annealing temperature on current density, C-V characteristics, and memory windows of Pt/SBT/BIT/p-Si heterostructure were investigated. The SBT/BIT multilayer films were polycrystalline with no pyrochlore phase and no preferred orientation. The leakage current density was under 3 × 10−7 A/cm2 at 5 V with asymmetry hysteresis loops for Pt/SBT/BIT/p-Si heterostructure. Although all C-V curves showed clockwise ferroelectric hysteresis loops and the memory window reached a maximum of 0.78 V at a sweep voltage of 5 V, the memory window changed asymmetrically with the variation of annealing temperature and sweep voltage. The maximum memory window of Pt/SBT/BIT/p-Si heterostructure prepared at lower temperatures was narrower at lower sweep voltage. The asymmetric behavior of the C-V characteristics was discussed in terms of electron injection from Si and the ferroelectric polarization effect.

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26

Chew, Kim Mey, Rubita Sudirman, Norhudah Seman, and Ching Yee Yong. "Signal Processing of Microwave Imaging Brain Tumor Detection Using Superposition Windowing." Applied Mechanics and Materials 654 (October 2014): 321–26. http://dx.doi.org/10.4028/www.scientific.net/amm.654.321.

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This paper discusses the selection of window function for signal processing in microwave imaging brain tumor detection. Most of the window functions are non-negative bell-shaped curves. This paper proposed a superposition windowing function for better time series data analyses and enhancement. The performance of the selected five window functions (Hamming, Blackman-Harris, Parzen, Chebyshev and Bartlett-Hanning) and the proposed superposition window were compared and evaluated. The results show the superposition window function is potentially reduce the unwanted noise and preserve important information of the signals.

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27

Wu, Juan, and Min Bai. "Adaptive rank-reduction method for seismic data reconstruction." Journal of Geophysics and Engineering 15, no. 4 (May 16, 2018): 1688–703. http://dx.doi.org/10.1093/jge/aabc74.

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Abstract Seismic data reconstruction plays an important role in the whole seismic data processing and imaging workflow, especially for those data that are acquired from severe field environment and are missing a large portion of the reflection signals. The rank-reduction method is considered to be a very effective method for interpolating data that are of small curvature, e.g. the post-stack data. However, when the data are more complicated, the rank-reduction method may fail to achieve acceptable performance. A useful strategy is to use local windows to process the data so that the data in each local window satisfy the plane-wave assumption of the rank-reduction method. However, the rank in each window requires a careful selection. Traditional methods select a global rank for all windows. We have proposed an automatic algorithm to select the rank in each processing window. The energy ratio between two consecutive singular values is chosen as the criterion to define the optimal rank. We apply this strategy to seismic data interpolation and use both synthetic and field data examples to demonstrate its potential in practical applications.

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Xiao, Fuyuan, Cheng Zhan, Hong Lai, Li Tao, and Zhiguo Qu. "New parallel processing strategies in complex event processing systems with data streams." International Journal of Distributed Sensor Networks 13, no. 8 (August 2017): 155014771772862. http://dx.doi.org/10.1177/1550147717728626.

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Sensor network–based application has gained increasing attention where data streams gathered from distributed sensors need to be processed and analyzed with timely responses. Distributed complex event processing is an effective technology to handle these data streams by matching of incoming events to persistent pattern queries. Therefore, a well-managed parallel processing scheme is required to improve both system performance and the quality-of-service guarantees of the system. However, the specific properties of pattern operators increase the difficulties of implementing parallel processing. To address this issue, a new parallelization model and three parallel processing strategies are proposed for distributed complex event processing systems. The effects of temporal constraints, for example, sliding windows, are included in the new parallelization model to enable the processing load for the overlap between windows of a batch induced by each input event to be shared by the downstream machines to avoid events that may result in wrong decisions. The proposed parallel strategies can keep the complex event processing system working stably and continuously during the elapsed time. Finally, the application of our work is demonstrated using experiments on the StreamBase system regardless of the increased input rate of the stream or the increased time window size of the operator.

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Mottaghi-Kashtiban, M., and M. G. Shayesteh. "New efficient window function, replacement for the Hamming window." IET Signal Processing 5, no. 5 (2011): 499. http://dx.doi.org/10.1049/iet-spr.2010.0272.

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Chang, Jieh-Ren, You-Shyang Chen, Chih-Min Lo, and Huan-Chung Chen. "An Advanced AFWMF Model for Identifying High Random-Valued Impulse Noise for Image Processing." Applied Sciences 11, no. 15 (July 30, 2021): 7037. http://dx.doi.org/10.3390/app11157037.

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In this study, a novel adaptive fuzzy weighted mean filter (AFWMF) model based on the directional median technique and fuzzy inference is presented for solving the restoring high-ratio random-valued noise in image processing. This study aims, not only to obtain information from each direction of the filtering window, but also to gain information from every pixel of the filtering windows completely. Thus, in order to implement preserving details and textures for better restoration in high-noise cases, this study utilizes the directional median to build the membership function in fuzzy inference dynamically, then calculates the weighted window corresponding to the filtering window using fuzzy inference to represent the importance of valuable pixels. Finally, the restoration pixel is calculated using the weighted window and the filtering window for the weighted mean. Subsequently, this new AFWMF model significantly improves performances in the measurement of the peak signal to noise ratio (PSNR) value for preserving detail and fixed image in noise density within the range of 20–70% for the five well-known experimental images. In extensive experiments, this study also shows the better performance of identifying the proposed peak signal-to-removal noise ratio (PSRNR) and evaluating psycho-visual tests than other listed filter methods. Furthermore, the proposed AFWMF model also has a better structural similarity index measure (SSIM) value of another indicator. Conclusively, two interesting and meaning findings are identified: (1) the proposed AFWMF model is generally the best model among the 10 listed filtering methods for image processing in terms of the measurement of two quantitative indicators for both the PSNR and SSIM values; (2) different impulse noise densities should be made for different filtering methods, and thus, this is an important and interesting issue when aiming to identify an appropriate filtering model from a variety of images for processing various noise densities.

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Kapoor, Piyush, and Sarabjeet Singh Bedi. "Weather Forecasting Using Sliding Window Algorithm." ISRN Signal Processing 2013 (December 10, 2013): 1–5. http://dx.doi.org/10.1155/2013/156540.

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RAJNOVIC, D., O. ERIC, and L. SIDJANIN. "The standard processing window of alloyed ADI materials." Metallic Materials 50, no. 03 (2012): 199–208. http://dx.doi.org/10.4149/km_2012_3_199.

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Hammad, Moustafa A., Walid G. Aref, and Ahmed K. Elmagarmid. "Query processing of multi-way stream window joins." VLDB Journal 17, no. 3 (September 29, 2006): 469–88. http://dx.doi.org/10.1007/s00778-006-0017-y.

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Kumaran, Dharshan, and Eleanor A. Maguire. "Novelty signals: a window into hippocampal information processing." Trends in Cognitive Sciences 13, no. 2 (February 2009): 47–54. http://dx.doi.org/10.1016/j.tics.2008.11.004.

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He, Xianghang, Menglu Shen, Rong Cui, Haiyan Zheng, Xiaowei Ruan, Zhong-Lin Lu, and Fang Hou. "The Temporal Window of Visual Processing in Aging." Investigative Opthalmology & Visual Science 61, no. 5 (May 28, 2020): 60. http://dx.doi.org/10.1167/iovs.61.5.60.

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36

Girish, G., and V. Anandakrishnan. "Determination of friction stir processing window for AA7075." Materials Today: Proceedings 21 (2020): 557–62. http://dx.doi.org/10.1016/j.matpr.2019.06.706.

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CHANDRAIAH, G., and REDDY T. SREENIVASULU. "ATMOSPHERIC RADAR SIGNAL PROCESSING USING HYBRID WINDOW FUNCTIONS." i-manager’s Journal on Electronics Engineering 9, no. 1 (2018): 14. http://dx.doi.org/10.26634/jele.9.1.14427.

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Fais, Laurel, Julia Leibowich, Ladan Hamadani, and Lana Ohira. "Infant movement as a window into language processing." Gesture and Multimodal Development 10, no. 2-3 (December 31, 2010): 222–50. http://dx.doi.org/10.1075/gest.10.2-3.06fai.

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We demonstrate differential, systematic, cross-modal responses to language by contrasting the regularities of infant movement behavior in contexts in which infants are presented with language stimuli, with those exhibited in the context of music. Using a detailed coding system, we show that infants recognize the social underpinnings of language and respond to language stimuli with vocal, gaze, head, and torso, (but not arm or manual) movements that differ from those exhibited to music stimuli. We propose that measures of these sorts of bodily gestures can not only provide a reliable supplement to looking time measures for gauging infant language abilities, but also uncover novel, richly textured nuances to our understanding of infant language acquisition.

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Mosheiov, Gur, and Daniel Oron. "Due-window assignment with unit processing-time jobs." Naval Research Logistics 51, no. 7 (2004): 1005–17. http://dx.doi.org/10.1002/nav.20039.

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Khalvati, Farzad, Mark D. Aagaard, and Hamid R. Tizhoosh. "Window memoization: toward high-performance image processing software." Journal of Real-Time Image Processing 10, no. 1 (March 22, 2012): 5–25. http://dx.doi.org/10.1007/s11554-012-0247-8.

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Karlsson, Kristina, Roland Kádár, Mats Stading, and Mikael Rigdahl. "Processing window for extrusion foaming of hydroxypropyl methylcellulose." Cellulose 23, no. 3 (April 8, 2016): 1675–85. http://dx.doi.org/10.1007/s10570-016-0924-z.

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Chen, Antao, Xuchu Weng, Jiajin Yuan, Xu Lei, Jiang Qiu, Dezhong Yao, and Hong Li. "The Temporal Features of Self-referential Processing Evoked by Chinese Handwriting." Journal of Cognitive Neuroscience 20, no. 5 (May 2008): 816–27. http://dx.doi.org/10.1162/jocn.2008.20505.

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To explore the temporal features and underlying brain structures of self-referential processing, participants were shown examples of Chinese handwriting, half of which were their own and the other half belonged to others, and asked to judge whether the handwriting was their own. In Experiment 1, the task was to categorize the handwriting by pressing the correct key as quickly as possible. In Experiment 2, after the participants recognized the stimuli, they were required to gaze at the handwriting for 3000 msec before making a response rather than responding immediately after stimulus onset. The results showed prominent differences in event-related potentials elicited by own and other handwriting conditions in the 200–500 msec and 1000–2000 msec time windows. Dipole analyses of the difference waves, own minus other, were conducted in both of these time windows. There were two dipoles in the 200–500 msec time window localized to the medial-temporal lobe and the anterior cingulate cortex (ACC), and MTL activation preceded ACC activation. Only one dipole at the posterior cingulate cortex was fitted to the 1000–2000 msec time window. These structures were activated sequentially in a temporal course, which provides evidence that the cortex middle structures potentially form a specific self-related processing unit, which is involved in processing various aspects of the self.

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Peng, Emma Y., John Shon, and Christine Tan. "Market Reactions to XBRL-Formatted Financial Information: Empirical Evidence from China." International Journal of E-Business Research 10, no. 3 (July 2014): 1–17. http://dx.doi.org/10.4018/ijebr.2014070101.

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XBRL (eXtensible Business Reporting Language) facilitates the efficient processing/interpreting of corporate financial information by investors. This paper examines market reactions to financial statement filings in China in the period before and after the XBRL mandate in China to assess the extent to which XBRL may impact the processing of financial information. It finds that absolute price reactions of financial statement filings are larger (smaller) in the post-XBRL (pre-XBRL) period. This result holds for the cumulative 3-day window surrounding filings, as well as for each individual day during the event window. This paper also finds similar results for the average volume of trading around these event windows. Consistent with its expectations, its findings suggest XBRL financial statements play a significant role in investors' decision making process.

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Tran, Tri Minh, and Byung Suk Lee. "Distributed Adaptive Windowed Stream Join Processing." International Journal of Distributed Systems and Technologies 2, no. 2 (April 2011): 59–81. http://dx.doi.org/10.4018/jdst.2011040104.

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This paper presents an adaptive framework for processing a window-based multi-way join query over distributed data streams. The framework integrates distributed plan modification and distributed plan migration within the same scope by using a building block called the node operator set (NOS). An NOS is housed in each node that participates in the join execution, and specifies the set of atomic operations to be performed locally at the host node to execute its share of the global execution plan. The plan modification and migration techniques presented are for the case of updating the NOSs centralized at a single node and the case of updating them distributed at each node. The plan modification is triggered by the change of stream statistics and adjusts the join execution order and placement greedily to satisfy a cost invariant. The plan migration uses the distributed track strategy to accelerate the migration of window extents to new nodes. The migration of all window extents is synchronized. Experiments confirm the effectiveness of the developed adaptive framework on reducing the join execution cost and indicate a small additional adaptation-overhead for distributing the NOS update.

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Aminoff, Elissa M., and Michael J. Tarr. "Functional Context Affects Scene Processing." Journal of Cognitive Neuroscience 33, no. 5 (April 1, 2021): 933–45. http://dx.doi.org/10.1162/jocn_a_01694.

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Abstract Rapid visual perception is often viewed as a bottom–up process. Category-preferred neural regions are often characterized as automatic, default processing mechanisms for visual inputs of their categorical preference. To explore the sensitivity of such regions to top–down information, we examined three scene-preferring brain regions, the occipital place area (OPA), the parahippocampal place area (PPA), and the retrosplenial complex (RSC), and tested whether the processing of outdoor scenes is influenced by the functional contexts in which they are seen. Context was manipulated by presenting real-world landscape images as if being viewed through a window or within a picture frame—manipulations that do not affect scene content but do affect one's functional knowledge regarding the scene. This manipulation influences neural scene processing (as measured by fMRI): The OPA and the PPA exhibited greater neural activity when participants viewed images as if through a window as compared with within a picture frame, whereas the RSC did not show this difference. In a separate behavioral experiment, functional context affected scene memory in predictable directions (boundary extension). Our interpretation is that the window context denotes three-dimensionality, therefore rendering the perceptual experience of viewing landscapes as more realistic. Conversely, the frame context denotes a 2-D image. As such, more spatially biased scene representations in the OPA and the PPA are influenced by differences in top–down, perceptual expectations generated from context. In contrast, more semantically biased scene representations in the RSC are likely to be less affected by top–down signals that carry information about the physical layout of a scene.

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Wang, Ji-Bo, and Ming-Zheng Wang. "Single-Machine Due-Window Assignment and Scheduling with Learning Effect and Resource-Dependent Processing Times." Asia-Pacific Journal of Operational Research 31, no. 05 (October 2014): 1450036. http://dx.doi.org/10.1142/s0217595914500365.

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We consider a single-machine common due-window assignment scheduling problem, in which the processing time of a job is a function of its position in a sequence and its resource allocation. The window location and size, along with the associated job schedule that minimizes a certain cost function, are to be determined. This function is made up of costs associated with the window location, window size, earliness, and tardiness. For two different processing time functions, we provide a polynomial time algorithm to find the optimal job sequence and resource allocation, respectively.

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Kumari, P. Kamala, and J. B. Seventline. "A Novel Approach For Identification Of Exon Locations In DNA Sequences Using GLC Window." International Journal of Biology and Biomedical Engineering 15 (March 30, 2021): 47–60. http://dx.doi.org/10.46300/91011.2021.15.7.

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The application of signal processing techniques for identification of exons in Deoxyribonucleic acid (DNA) sequence is a challenging task. The objective of this paper is to introduce a combinational window approach for locating exons in DNA sequence. In contrast to the traditional single window function for evaluation of short time Fourier transform (STFT), this work proposes a novel method for evaluating STFT coefficients using a combinational window function comprising of Gaussian, Lanczos and Chebyshev (GLC) windows. The chosen combinational window GLC has the highest relative side lobe attenuation values compared to other window functions introduced by various researchers. The proposed algorithm incorporates GLC window function for evaluating STFT coefficients and in the design of FIR bandpass filter. Simulation results revealed its effectiveness in improving the evaluation parameters like Sensitivity, Specificity, Accuracy, Area under curve (AUC), Discrimination Measure (DM). Furthermore, the proposed algorithm has been applied successfully to some universal benchmark datasets like C. elegans, Homosapiens, etc., The proposed method has shown to be an efficient approach for the prediction of protein coding regions compared to other existing methods. All the simulations are done using the MATLAB 2016a.

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Saxena, Sanjay, Nitu Kumari, and Swati Pattnaik. "Brain Tumour Segmentation in FLAIR MRI Using Sliding Window Texture Feature Extraction Followed by Fuzzy C-Means Clustering." International Journal of Healthcare Information Systems and Informatics 16, no. 3 (July 2021): 1–20. http://dx.doi.org/10.4018/ijhisi.20210701.oa1.

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In this paper, a hybrid approach using sliding window mechanism followed by fuzzy c means clustering is proposed for the automated brain tumour extraction. The proposed method consists three phases. The first phase is used for detecting the tumorous brain MR scans by implementing pre-processing techniques followed by texture features extraction and classification. Further, this phase also compares the performance of different classifiers. The second phase consists of the localization of the tumorous region using sliding window mechanism, in which a sized window sweeps through the whole tumorous MR scan and the window is classified as tumorous or non-tumorous. The third phase consists of fuzzy c means clustering to get the exact location of the tumour by removing the misclassified windows obtained from Phase 2. 2D single-spectral anatomical FLAIR MRI scans are considered for experiment. Outcomes demonstrate significant results in terms of sensitivity, specificity, accuracy, dice similarity coefficient in comparison with the other existing methods.

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Kim, Hyeon Gyu, and Myoung Ho Kim. "A Review of Window Query Processing for Data Streams." Journal of Computing Science and Engineering 7, no. 4 (December 30, 2013): 220–30. http://dx.doi.org/10.5626/jcse.2013.7.4.220.

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Vajda, Ferenc. "Application and implementation of window-based image processing algorithms." Microprocessing and Microprogramming 30, no. 1-5 (August 1990): 447–54. http://dx.doi.org/10.1016/0165-6074(90)90281-d.

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