Relevant bibliographies by topics / Processing window

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Processing window'

Author: Grafiati
Published: 14 July 2021
Last updated: 11 February 2022

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Journal articles on the topic "Processing window"

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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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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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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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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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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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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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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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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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Dissertations / Theses on the topic "Processing window"

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Schultz, Steven Peter. "Attentional Window and Global/Local Processing." Scholar Commons, 2016. http://scholarcommons.usf.edu/etd/6383.

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How does the focus of attention influence the encoding of information? Research has shown that size and allocation of the attentional window has an influence on what information is attended to or missed. The size-scale of features also effects processing of visual information. Previous research involving hierarchical stimuli suggests precedence for global features. In the present experiment, I investigated the influence of attentional window size on accuracy of encoding hierarchical stimuli at the global and local level. Here I introduce a new method for manipulating the size of the attentional window and for collecting unconstrained responses. At the start of each trial, observers tracked a dashed-line rectangular box, which either broadened or narrowed in size after onset. This sequence was immediately followed by a brief presentation of two hierarchical letters presented simultaneously on the left and right sides of the screen. The box preceding the hierarchical letters either broadened to a size large enough to include both letters at the global level, or narrowed to a size small enough to include a maximum of two letters at the local level at either side of the screen. Observers reported all letters they were able to identify. Results from two experiments indicate an overall precedence of global letters. However, a narrow attentional window reduced global precedence, as would be expected with more focused attention. The narrow windows also produced more same-side identifications of both global and local letters. The second experiment also showed that reducing the processing time decreased the global advantage.
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Golab, Lukasz. "Sliding Window Query Processing over Data Streams." Thesis, University of Waterloo, 2006. http://hdl.handle.net/10012/2930.

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Database management systems (DBMSs) have been used successfully in traditional business applications that require persistent data storage and an efficient querying mechanism. Typically, it is assumed that the data are static, unless explicitly modified or deleted by a user or application. Database queries are executed when issued and their answers reflect the current state of the data. However, emerging applications, such as sensor networks, real-time Internet traffic analysis, and on-line financial trading, require support for processing of unbounded data streams. The fundamental assumption of a data stream management system (DSMS) is that new data are generated continually, making it infeasible to store a stream in its entirety. At best, a sliding window of recently arrived data may be maintained, meaning that old data must be removed as time goes on. Furthermore, as the contents of the sliding windows evolve over time, it makes sense for users to ask a query once and receive updated answers over time.

This dissertation begins with the observation that the two fundamental requirements of a DSMS are dealing with transient (time-evolving) rather than static data and answering persistent rather than transient queries. One implication of the first requirement is that data maintenance costs have a significant effect on the performance of a DSMS. Additionally, traditional query processing algorithms must be re-engineered for the sliding window model because queries may need to re-process expired data and "undo" previously generated results. The second requirement suggests that a DSMS may execute a large number of persistent queries at the same time, therefore there exist opportunities for resource sharing among similar queries.

The purpose of this dissertation is to develop solutions for efficient query processing over sliding windows by focusing on these two fundamental properties. In terms of the transient nature of streaming data, this dissertation is based upon the following insight. Although the data keep changing over time as the windows slide forward, the changes are not random; on the contrary, the inputs and outputs of a DSMS exhibit patterns in the way the data are inserted and deleted. It will be shown that the knowledge of these patterns leads to an understanding of the semantics of persistent queries, lower window maintenance costs, as well as novel query processing, query optimization, and concurrency control strategies. In the context of the persistent nature of DSMS queries, the insight behind the proposed solution is that various queries may need to be refreshed at different times, therefore synchronizing the refresh schedules of similar queries creates more opportunities for resource sharing.
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Wei, Mingrui. "Multi-Mode Stream Processing For Hopping Window Queries." Digital WPI, 2008. https://digitalcommons.wpi.edu/etd-theses/769.

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Window constraints are mechanisms to bound the tuples processed by continuous queries specified over unbounded data streams. While sliding window queries move the constraint window upon the arrival of each individual tuple, hopping window queries instead move the window by a fixed amount after some period, thus periodically refreshing their results. We observe that for large hops, techniques liked delta result updating may not be efficient -- as large portions of the tuples in the current window will be different from the previous window and thus must be maintained. On the other hand, the complete result updating technique, which has been found to be less suitable for sliding windows queries. Compute the next result based on the complete current window now can be shown to be superior in performance for some hopping windows queries. A trade-off emerges between the complete result method which has a lower per tuple processes cost but potentially processing redundant results versus the delta result method which has no redundant processing but pays a higher per tuple processing cost. On top of that, strict non-monotonic operators such as difference operator, cause premature expiration due to operator semantics. Negative tuples are needed for this kind of special expiration. Such negative tuples added extra burden to the stream engine. Thus, in streaming processing, the difference operator is typically suggested to be placed on top of the query plan despite its potential ability to reduce cardinality of the stream. With this thesis, we introduce a whole solution for hopping window query processing which includes an optimizer for generalized hopping window query optimization that exploits both processing techniques within one integrated query plan alone with query plan rewriting. First, we design the query operators to be multi-mode, that is, to be able to take either a delta or a complete result as input, and produce either a delta result or complete result as output. Then we design a cost model to be able to chose the optimal mode for each operator. Thirdly, our optimizer targets to configure each operator within a query plan to work in the suitable mode to achieve minimum overall processing costs. Last but not least, two query optimization techniques have been adopted. One explores all possibilities of pushing the difference down past joins using dynamic programming and assigning optimal mode at the same time, the other applies heuristic difference push down rule. The proposed techniques has been implemented within the WPI stream query engine, called CAPE. Finally, we show the benefit of our solution with a vast number of experimental results.
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Zhang, Xin. "Developing Image Processing Tools in X Window System." PDXScholar, 1992. https://pdxscholar.library.pdx.edu/open_access_etds/4571.

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The X Window System is an industry-standard software system which facilitates programmers to develop portable graphical user interfaces. This thesis describes an image processing tool developed under the X Window System. A multiwindow image display software with image editing and improvement functions is developed. The software has four modules: environment generation, image creation, image editing and image improvement. The environment generation module creates working windows, scrollbars, dialogbox and pulldown menu buttons, and tracks mouse cursor positions. The working windows are three adjacent windows allowing display of three different images simultaneously. The dialogbox provides an interface between the user and the program, such as input new image and parameters. The pulldown menus offer various selections of image processing functions. A pair of scrollbars are also added to allow users to move the magnified image up, down, left and right so that the full picture can be viewed. The image creation module can build colormap, load image data file, convert pixel values to screen color values, create image, and display image on the screen of a workstation. The program can read either sun.rasterfile format or a plain data file. If a plain data file is detected, the software can transform it to sun.rasterfile by adding an appropriate header and a colormap. There are two kinds file saving features: screen capture and store. The screen capture allows the user to save that part of image displayed on the screen. The store function saves the entire image which may be either the screen size or bigger size image (e.g. merged or zoomed image). The image editing module is equipped with the functions for zooming (in or out) , merging, rotating and restoring images. The merge function constructs a new image based on the user selected or input image from the dialogbox. The rotation center of an image can be any point selected by user's clicking mouse button, and the rotation angle is supplied by user in the dialogbox. The image improvement module consists of some image point transformation and image enhancement functions. This software package is easier to use than existing tools for image processing. It has been used in the image processing projects and related educational purposes. The software provides a framework and can be easily extended to other potential applications.
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Silva, Asima. "Multiple continuous query processing with relative window predicates "Juggler"." Link to electronic thesis, 2004. http://www.wpi.edu/Pubs/ETD/Available/etd-0527104-223456/.

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Thesis (M.S.)--Worcester Polytechnic Institute.
Keywords: reordering predicates; multi-join operator; sliding windows; window predicates; join algorithm; continuous queries. Includes bibliographical references (p. 101-103).
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Spinosa, Vittoria. "Motor auditory interaction: a window towards associative and predictive processing." Doctoral thesis, Universitat de Barcelona, 2019. http://hdl.handle.net/10803/669916.

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Perception can be considered as the bridge necessary to interact with the surroundings. Indeed, through our senses we are continuously exchanging information between the physical world around us and our internal models, made of prior beliefs and expectations, which allow to constantly create meanings and interpretations about the events caused by external sources or by us. Illusions and cross-modal effects are proofs of the incessant and constructive activity of the human brain. By experience, we learn also to make action-effect associations and to predict the sensory consequences of each motor act. For instance, we learn that by touching a warm object we can get burnt, thus we can predict that this action can be dangerous and avoid making it in the future. Current research is attempting to investigate the mechanisms underlying associative and predictive processing, and how these mechanisms are modulated by the sensory experience. A great deal of this research is carried out with the electroencephalogram (EEG), and some intriguing results have suggested that a dysregulation of associative and predictive processing may underlie some clinical phenomena, such as psychosis. The present PhD thesis focuses on expectation effects arising from motor-auditory interactions, in order to investigate action-effect associative and predictive processing. Two independent studies were carried out in which behavioral (action timing and action force) and electrophysiological (event-related brain potentials, ERPs) measurements were collected while participants were instructed to press different buttons that were associated with either the presentation or the omission of a sound, and with violations of these associations. Study I focused on predictive processing and aimed to investigate the matching- and mismatching-related effects between an event and an established expectation. The findings suggest that these effects are manifestations of a unitary underlying process of prediction. Study II focused on associative processing and aimed to investigate the buildup of action-effect associations, in a context in which there were no stable regularities. The findings suggest that the repetition of an action-effect contingency can foster an expectation, and that the consequences of an action can modify the action itself. Overall, the results from this thesis suggest that associative and predictive processing arising from a motor act modulate behavior and neuronal activity in a close-loop manner. That is, the motor act causes specific consequences which modulate behavior and neuronal processing, and internal action-effect associations and predictions seem to affect, in turn, the neuronal processing and the action itself.
La percepción puede considerarse como el puente necesario para interactuar con el entorno. De hecho, estamos continuamente intercambiando información entre el mundo físico que nos rodea y nuestros modelos internos, formados a partir de creencias anteriores y expectativas, que permiten dar constantemente significado e interpretación a los sucesos causados por fuentes externas o por nosotros mismos. Por experiencia, aprendemos también a hacer asociaciones de acción-efecto y a predecir las consecuencias sensoriales de cada acto motor. Actualmente, se están estudiando los mecanismos subyacentes del procesamiento asociativo y predictivo, y la modulación de este procesamiento en la experiencia sensorial. En la presente tesis doctoral, nos centramos en los efectos de la expectativa derivados de la interacción motora-auditiva, con el fin de estudiar los procesos asociativos y predictivos entre acciones - efecto. Para alcanzar este objetivo, realizamos dos estudios independientes en los que registramos medidas de comportamiento (tiempo de acción y fuerza de la acción) y electrofisiológicas (potenciales evocados) mientras los participantes realizaron pulsaciones de botones que estaban asociadas con la presentación o la omisión de un sonido, y con las violaciones de estas asociaciones. El estudio I se centró en procesos predictivos consolidados y tuvo como objetivo investigar los efectos relacionados con la coincidencia y la falta de coincidencia entre un evento y una expectativa. Los resultados sugieren que estos efectos son manifestaciones del mismo proceso subyacente de predicción. El estudio II se centró en el procesamiento asociativo y tuvo como objetivo investigar la construcción de asociaciones de acción-efecto, en un contexto en el que no había regularidades establecidas. Los resultados sugieren que la repetición de una contingencia acción-efecto puede fomentar una expectativa, y que la consecuencia de una acción puede modificar la acción en sí. Los resultados sugieren que el procesamiento asociativo y predictivo que surge de un acto motor modula circularmente el comportamiento y la actividad neuronal. Es decir, el acto motor causa consecuencias específicas que modulan el comportamiento y el procesamiento neuronal, pero también las asociaciones de acción-efecto y las predicciones relacionadas parecen afectar el procesamiento neuronal y la acción en sí.
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Li, Jin. "Window Queries Over Data Streams." PDXScholar, 2008. https://pdxscholar.library.pdx.edu/open_access_etds/2675.

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Evaluating queries over data streams has become an appealing way to support various stream-processing applications. Window queries are commonly used in many stream applications. In a window query, certain query operators, especially blocking operators and stateful operators, appear in their windowed versions. Previous research work in evaluating window queries typically requires ordered streams and this order requirement limits the implementations of window operators and also carries performance penalties. This thesis presents efficient and flexible algorithms for evaluating window queries. We first present a new data model for streams, progressing streams, that separates stream progress from physical-arrival order. Then, we present our window semantic definitions for the most commonly used window operators—window aggregation and window join. Unlike previous research that often requires ordered streams when describing window semantics, our window semantic definitions do not rely on physical-stream arrival properties. Based on the window semantic definitions, we present new implementations of window aggregation and window join, WID and OA-Join. Compared to the existing implementations of stream query operators, our implementations do not require special stream-arrival properties, particularly stream order. In addition, for window aggregation, we present two other implementations extended from WID, Paned-WID and AdaptWID, to improve excution time by sharing sub-aggregates and to improve memory usage for input with data distribution skew, respectively. Leveraging our order-insenstive implementations of window operators, we present a new architecture for stream systems, OOP (Out-of- Order Processing). Instead of relying on ordered streams to indicate stream progress, OOP explicitly communicates stream progress to query operators, and thus is more flexible than the previous in-order processing (IOP) approach, which requires maintaining stream order. We implemented our order-insensitive window query operators and the OOP architecture in NiagaraST and Gigascope. Our performance study in both systems confirms the benefits of our window operator implementations and the OOP architecture compared to the commonly used approaches in terms of memory usage, execution time and latency.
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Zahiri, Saden H. (Saden Heshmatollah) 1966. "Prediction of the processing window and austemperability for austempered ductile iron." Monash University, School of Physics and Materials Engineering, 2002. http://arrow.monash.edu.au/hdl/1959.1/8408.

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Paul, Devashish. "Filterbank implementations of a window based Gabor transform for SAR processing." Thesis, University of Ottawa (Canada), 1995. http://hdl.handle.net/10393/9957.

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In this thesis a Window Based Gabor Transform (WBGT) is presented that is suitable for real time digital signal processing. Other Gabor Transform approaches presented in the literature such as the Orthogonal Like Discrete Gabor Transform (OLGT) are not suitable for real time processing. The reduction in analysis time using the WBGT instead of the OLGT is proportional to the ratio of the analysis window to the signal length. Using the WBGT the number of JTF coefficients required to accurately represent the original signal is far less than when using the STFT. Two filterbank implementations for the WBGT which reduce analysis times are developed, one using serial input and the second using a parallel input, each of which computes the frequency content of the signal using N parallel band pass filters. In the case of the parallel input filterbank, the analysis times are similar to those using a Short Time Fourier Transform with FFT. The parallel input filterbank can be implemented using a matrix formulation for the N band pass filters. This approach is suitable for software implementation and results in analysis times that are lower than when using an STFT or the parallel input implementation with the bank of band pass filters. The WBGT, along with the filterbank implementations result in very accurate JTF spectra. Near perfect reconstruction of the original signal from the JTF spectra was obtained for several cases for the Gabor Transform techniques presented in this thesis. Finally, the use of the parallel input filterbank in the context of SAR processing is presented and the hardware requirements are derived and shown to be achievable using commercially available products. (Abstract shortened by UMI.)
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Henderson, Drake Hall. "Accelerated partial window imaging in an integrated vision unit." Thesis, Georgia Institute of Technology, 1995. http://hdl.handle.net/1853/16630.

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Books on the topic "Processing window"

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Canada. Dept. of Fisheries and Oceans. An algorithm for bottom window echo processing. Halifax, N.S: Fisheries and Oceans, 1991.

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Clever cornices, valances, & unique window treatments. New York: Sterling Pub. Co., 1997.

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International School of Crystallographic Computing (13th 1992 Balatonfüred, Hungary). Crystallographic computing 6: A window on modern crystallography : papers presented at the International School of Crystallographic Computing held at Balatonfüred, Hungary 31 May-6 June 1992. [Chester, England]: International Union of Crystallography, 1993.

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Troop, Jane. WordPerfect for Windows. Wilsonville, Or: Franklin, Beedle & Associates, 1993.

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Ober, Scot. Gregg college keyboarding & document processing for Windows. 8th ed. New York: Glencoe, McGraw-Hill, 1997.

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Martin, Edward G. Word processing with WordPerfect 6.1 for Windows. Fort Worth: Dryden Press, 1995.

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Mason, Peter. Word processing with Microsoft Word for Windows. 2nd ed. Sheffield: University of Sheffield, Computing Services, 1993.

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Ericksen, Linda. WordPerfect 6.1 for Windows. Danvers, Mass: Boyd & Fraser Pub. Co., 1996.

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Shelly, Gary B. WordPerfect 6 for Windows. Danvers, Mass: Boyd & Fraser Pub. Co., 1995.

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Word for Windows first run. Carmel, IN: Que College, 1993.

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Book chapters on the topic "Processing window"

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Aref, Walid G. "Window-Based Query Processing." In Encyclopedia of Database Systems, 4695–700. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_468.

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Aref, Walid G. "Window-based Query Processing." In Encyclopedia of Database Systems, 3533–38. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_468.

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Aref, Walid G. "Window-Based Query Processing." In Encyclopedia of Database Systems, 1–6. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4899-7993-3_468-2.

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Lin, Chunbo, Jingdong Li, Xiaoling Wang, Xingjian Lu, and Ji Zhang. "WFApprox: Approximate Window Functions Processing." In Database Systems for Advanced Applications, 72–87. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59410-7_5.

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Chang, Chein-I. "Multiple Window Anomaly Detection." In Real-Time Progressive Hyperspectral Image Processing, 547–76. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4419-6187-7_17.

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Konstantopoulos, Charalampos, Andreas Svolos, and Christos Kaklamanis. "Sliding-Window Compression on the Hypercube." In Euro-Par 2000 Parallel Processing, 835–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-44520-x_115.

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Jin, Qianli, Jun Zhao, and Bo Xu. "Window-Based Method for Information Retrieval." In Natural Language Processing – IJCNLP 2004, 120–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-30211-7_13.

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Snytsar, Roman, and Yatish Turakhia. "Parallel Approach to Sliding Window Sums." In Algorithms and Architectures for Parallel Processing, 19–26. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38961-1_3.

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Hou, Cuiqin, Yingju Xia, Jun Sun, Jing Shang, Ryozo Takasu, and Masao Kondo. "A Width-Variable Window Attention Model for Environmental Sensors." In Neural Information Processing, 512–20. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70096-0_53.

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Iliopoulos, Costas S., Manal Mohamed, Solon P. Pissis, and Fatima Vayani. "Maximal Motif Discovery in a Sliding Window." In String Processing and Information Retrieval, 191–205. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00479-8_16.

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Conference papers on the topic "Processing window"

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Krutz, Andreas, Michael Frater, and Thomas Sikora. "Window-Based Image Registration using Variable Window Sizes." In 2007 IEEE International Conference on Image Processing. IEEE, 2007. http://dx.doi.org/10.1109/icip.2007.4379842.

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Bronez, T. P., and D. S. Brown. "Alternate windows for multi-window spectral analysis." In [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing. IEEE, 1992. http://dx.doi.org/10.1109/icassp.1992.226591.

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Xing Gao, J. Sustersic, and A. R. Hurson. "Window Query Processing with Proxy Cache." In 7th International Conference on Mobile Data Management (MDM'06). IEEE, 2006. http://dx.doi.org/10.1109/mdm.2006.166.

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Chakraborty, Debejyo, and Narayan Kovvali. "Generalized normal window for digital signal processing." In ICASSP 2013 - 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2013. http://dx.doi.org/10.1109/icassp.2013.6638833.

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Sandsten, Maria, Johan Brynolfsson, and Isabella Reinhold. "The Matched Window Reassignment." In 2018 26th European Signal Processing Conference (EUSIPCO). IEEE, 2018. http://dx.doi.org/10.23919/eusipco.2018.8553204.

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Wolf, Bernhard, and Mario Neugebauer. "Refining the window size of sliding window operations in running data processing systems." In Factory Automation (ETFA 2008). IEEE, 2008. http://dx.doi.org/10.1109/etfa.2008.4638405.

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Gong, Yuanhao, Bozhi Liu, Xianxu Hou, and Guoping Qiu. "Sub-window Box Filter." In 2018 IEEE Visual Communications and Image Processing (VCIP). IEEE, 2018. http://dx.doi.org/10.1109/vcip.2018.8698682.

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Waidelich, Wilhelm R. A., Peter J. Hutzler, and Raphaela M. Waidelich. "Detection of abnormal cells by optical image processing." In Laser Florence 2001: a Window on the Laser Medicine World, edited by Leonardo Longo, Alfons G. Hofstetter, Mihail-Lucian Pascu, and Wilhelm R. A. Waidelich. SPIE, 2002. http://dx.doi.org/10.1117/12.486607.

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Chandrakanth, V., C. Devendranath, and A. Shamnar. "VLSI implementation of sliding window DFT." In 2013 International Conference on Signal Processing, Image Processing, and Pattern Recognition (ICSIPR). IEEE, 2013. http://dx.doi.org/10.1109/icsipr.2013.6497934.

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Ali, Haider, Christin Seifert, Nitin Jindal, Lucas Paletta, and Gerhard Paar. "Window Detection in Facades." In 14th International Conference on Image Analysis and Processing (ICIAP 2007). IEEE, 2007. http://dx.doi.org/10.1109/iciap.2007.4362880.

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Reports on the topic "Processing window"

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Doerry, Armin Walter. Window taper functions for subaperture processing. Office of Scientific and Technical Information (OSTI), December 2013. http://dx.doi.org/10.2172/1121978.

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Zhang, Xin. Developing Image Processing Tools in X Window System. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.6455.

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Dietz, Nikolaus. Stabilization of Indium-Rich In1-xGaxN Heterostructures: The Exploration of a Common Processing Window. Fort Belvoir, VA: Defense Technical Information Center, April 2015. http://dx.doi.org/10.21236/ada624591.

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Fox, K., T. Tommy Edwards, and D. David Peeler. TECHNOLOGY DEMONSTRATION OF SLUDGE MASS REDUCTION VIA ALUMINUM DISSOLUTION: GLASS FORMULATION PROCESSING WINDOW PREDICTIONS FOR SB5. Office of Scientific and Technical Information (OSTI), December 2007. http://dx.doi.org/10.2172/923829.

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SAGE Electrochromics, Inc. Electrochromic Windows: Advanced Processing Technology. Office of Scientific and Technical Information (OSTI), December 2006. http://dx.doi.org/10.2172/896321.

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Bruder, Brittany L., Katherine L. Brodie, Tyler J. Hesser, Nicholas J. Spore, Matthew W. Farthing, and Alexander D. Renaud. guiBath y : A Graphical User Interface to Estimate Nearshore Bathymetry from Hovering Unmanned Aerial System Imagery. Engineer Research and Development Center (U.S.), February 2021. http://dx.doi.org/10.21079/11681/39700.

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Abstract:
This US Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory, technical report details guiBathy, a graphical user interface to estimate nearshore bathymetry from imagery collected via a hovering Unmanned Aerial System (UAS). guiBathy provides an end-to-end solution for non-subject-matter-experts to utilize commercia-off-the-shelf UAS to collect quantitative imagery of the nearshore by packaging robust photogrammetric and signal-processing algorithms into an easy-to-use software interface. This report begins by providing brief background on coastal imaging and the photogrammetry and bathymetric inversion algorithms guiBathy utilizes, as well as UAS data collection requirements. The report then describes guiBathy software specifications, features, and workflow. Example guiBathy applications conclude the report with UAS bathymetry measurements taken during the 2020 Atlantic Hurricane Season, which compare favorably (root mean square error = 0.44 to 0.72 m; bias = -0.35 to -0.11 m) with in situ survey measurements. guiBathy is a standalone executable software for Windows 10 platforms and will be freely available at www.github.com/erdc.
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Campbell, Sam, and Wiliam Dam. Evaluation of Mineral Deposits Along the Little Wind River, Riverton, WY, Processing Site. Office of Scientific and Technical Information (OSTI), December 2014. http://dx.doi.org/10.2172/1258486.

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Federal Information Processing Standards Publication: X window system version 11 release 3. Gaithersburg, MD: National Bureau of Standards, 1988. http://dx.doi.org/10.6028/nist.fips.158.

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Federal Information Processing Standards Publication: X window system version 11 release 5 (X window system protocol; Xlib-C langauge X interface; X toolkit intrinsics - C language interface; bitmap distribution format 2.1). Gaithersburg, MD: National Bureau of Standards, 1988. http://dx.doi.org/10.6028/nist.fips.158-1.

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