Conferences related to Windows

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2021 IEEE Photovoltaic Specialists Conference (PVSC)

Photovoltaic materials, devices, systems and related science and technology


2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting

The joint meeting is intended to provide an international forum for the exchange of information on state of the art research in the area of antennas and propagation, electromagnetic engineering and radio science


2020 IEEE International Conference on Image Processing (ICIP)

The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.


2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)

All areas of ionizing radiation detection - detectors, signal processing, analysis of results, PET development, PET results, medical imaging using ionizing radiation


2020 IEEE Power & Energy Society General Meeting (PESGM)

The Annual IEEE PES General Meeting will bring together over 2900 attendees for technical sessions, administrative sessions, super sessions, poster sessions, student programs, awards ceremonies, committee meetings, tutorials and more


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Periodicals related to Windows

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Antennas and Propagation, IEEE Transactions on

Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.


Audio, Speech, and Language Processing, IEEE Transactions on

Speech analysis, synthesis, coding speech recognition, speaker recognition, language modeling, speech production and perception, speech enhancement. In audio, transducers, room acoustics, active sound control, human audition, analysis/synthesis/coding of music, and consumer audio. (8) (IEEE Guide for Authors) The scope for the proposed transactions includes SPEECH PROCESSING - Transmission and storage of Speech signals; speech coding; speech enhancement and noise reduction; ...


Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Broadcasting, IEEE Transactions on

Broadcast technology, including devices, equipment, techniques, and systems related to broadcast technology, including the production, distribution, transmission, and propagation aspects.


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Most published Xplore authors for Windows

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Xplore Articles related to Windows

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Influence of Car Body for Car Window Antenna

2018 IEEE International Workshop on Electromagnetics:Applications and Student Innovation Competition (iWEM), 2018

In this paper, we examine the influence of the car body on the antenna characteristics required for car window antenna design. In order to investigate the influence, we compare the model which is truncated only around the windshield with the whole car model. As a result, it is found that the analysis result equivalent to the whole car model can ...


Transient Identification: Shortening Identification Delay and Enhancing Identification Rate by Selecting the Optimal Moving Window Size

2018 IEEE International Conference on Big Data and Smart Computing (BigComp), 2018

Moving window mechanism is prevailingly adopted to deal with the serial correlations of sample data in the applications of data-driven methods for fault detection and diagnosis, such as dynamic principle component analysis, dynamic Fisher discriminant analysis and so on. Before preparing the data set for subsequent processing, it is very important to determine a suitable size of a moving window, ...


The Window Size in Residential House Facades After the Current and New CEN Standard

2018 VII. Lighting Conference of the Visegrad Countries (Lumen V4), 2018

Nowadays daylight apertures in buildings are designed on the bases of overcast sky conditions in wintertime in Slovakia and Czech Republic. The criterion is the relative value of the Daylight Factor in its average 0.9% in two reference points in the middle depth of the room. Commonly, in practice as a consequence are designed windows roughly 1.5 - 1.7 m ...


System Requirements

Indoor Wireless Communications: From Theory to Implementation, None

An indoor wireless system is based on a set of requirements that should be met if the system is to deliver the required quality‐of‐service (QoS) for each of the offered services. This chapter describes the definition of such requirements in a general context for any wireless communication system. It highlights and explains specific requirements depending on technology may vary and ...


Image Operator Learning Coupled with CNN Classification and Its Application to Staff Line Removal

2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), 2017

Many image transformations can be modeled by image operators that are characterized by pixel-wise local functions defined on a finite support window. In image operator learning, these functions are estimated from training data using machine learning techniques. Input size is usually a critical issue when using learning algorithms, and it limits the size of practicable windows. We propose the use ...


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Educational Resources on Windows

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IEEE-USA E-Books

  • Influence of Car Body for Car Window Antenna

    In this paper, we examine the influence of the car body on the antenna characteristics required for car window antenna design. In order to investigate the influence, we compare the model which is truncated only around the windshield with the whole car model. As a result, it is found that the analysis result equivalent to the whole car model can be obtained and it can be analyzed with less computational cost by using the truncated model.

  • Transient Identification: Shortening Identification Delay and Enhancing Identification Rate by Selecting the Optimal Moving Window Size

    Moving window mechanism is prevailingly adopted to deal with the serial correlations of sample data in the applications of data-driven methods for fault detection and diagnosis, such as dynamic principle component analysis, dynamic Fisher discriminant analysis and so on. Before preparing the data set for subsequent processing, it is very important to determine a suitable size of a moving window, as it potentially determines both the identification delay and the identification rate. For enhancing safety and achieving more economic benefits for the operation of nuclear power plants, it is very important to timely (i.e., to make the identification delay as short as possible) and correctly (i.e., to make the identification rate as high as possible) identify the transients. Therefore, this study investigates the effect of the size of moving window to identification result and proposes an algorithm to obtain the optimal size of a moving window. The proposed algorithm was verified to be effective to find out an optimal size, based on which the shortest identification delay and highest identification rate could be achieved. Moreover, the investigation results also showed the trend of the effect of the signal-to-noise rate (SNR) to the selection of optimal moving window size. The verifications were carried out using our previously proposed identification method based on linear representation and the sample data were from the simulator of Chinese High Temperature gas-cooled Reactor Pebble-bed Module (HTR-PM) project.

  • The Window Size in Residential House Facades After the Current and New CEN Standard

    Nowadays daylight apertures in buildings are designed on the bases of overcast sky conditions in wintertime in Slovakia and Czech Republic. The criterion is the relative value of the Daylight Factor in its average 0.9% in two reference points in the middle depth of the room. Commonly, in practice as a consequence are designed windows roughly 1.5 - 1.7 m high in living rooms. The proposed European standard FprEN17037 is introducing a new criterion median exterior horizontal illuminance with the required indoor illuminance 300 lx in the middle of the room depth or 100 lx as minimum close to the rear wall. This study discusses problems of the design of window size in residential buildings and consequences of the new median criterion as well as the required interior illuminance in absolute lux values.

  • System Requirements

    An indoor wireless system is based on a set of requirements that should be met if the system is to deliver the required quality‐of‐service (QoS) for each of the offered services. This chapter describes the definition of such requirements in a general context for any wireless communication system. It highlights and explains specific requirements depending on technology may vary and differences. Many of these requirements are established on the basis that a minimum signal quality is expected in the wireless system, for sound performance. There are many factors which should be taken into account when specifying requirements. The chapter summarizes these factors. One key aspect to take into consideration when performing system upgrades in an indoor system is the type of traffic that needs to be handled. In the early days of mobile communications, voice was the main driver and all efforts were around the provision of good voice quality to customers.

  • Image Operator Learning Coupled with CNN Classification and Its Application to Staff Line Removal

    Many image transformations can be modeled by image operators that are characterized by pixel-wise local functions defined on a finite support window. In image operator learning, these functions are estimated from training data using machine learning techniques. Input size is usually a critical issue when using learning algorithms, and it limits the size of practicable windows. We propose the use of convolutional neural networks (CNNs) to overcome this limitation. The problem of removing staff-lines in music score images is chosen to evaluate the effects of window and convolutional mask sizes on the learned image operator performance. Results show that the CNN based solution outperforms previous ones obtained using conventional learning algorithms or heuristic algorithms, indicating the potential of CNNs as base classifiers in image operator learning. The implementations will be made available on the TRIOSlib project site.

  • A Fast Uyghur Text Detector for Complex Background Images

    Uyghur text localization in images with complex backgrounds is a challenging yet important task for many applications. Generally, Uyghur characters in images consist of strokes with uniform features, and they are distinct from backgrounds in color, intensity, and texture. Based on these differences, we propose a FASTroke keypoint extractor, which is fast and stroke-specific. Compared with the commonly used MSER detector, FASTroke produces less than twice the amount of components and recognizes at least 10% more characters. While the characters in a line usually have uniform features such as size, color, and stroke width, a component similarity based clustering is presented without component-level classification. It incurs no extra errors by incorporating a component-level classifier while the computing cost is drastically reduced. The experiments show that the proposed method can achieve the best performance on the UICBI-500 benchmark dataset.

  • New Features in Data Protection

    This chapter contains sections titled:IntroductionSynthetic BackupsEvolution of Synthetic BackupsBenefits of Synthetic BackupsBuilding a Synthetic BackupTechnical Considerations and LimitationsDisk‐Based SolutionsDisk to DiskDisk StagingVirtual TapeDisk‐Based Data Protection Implementation IssuesConclusion

  • Co-Simulation of the Different Parameters Affecting Lighting Conditions and User Preferences in Working Environments

    This paper presents a co-simulation of the different parameters which affect the illuminance inside a working environment. A key factor in this analysis is the daylight illuminance that penetrates into the building skin and the variations that it presents for different days of the year and sky types. A second parameter that is examined is the lighting behavior of the users. Each user presents unique preferences which affect the use of manual blinds and artificial lights. The proper assessment of his/her preferences are in great importance and they should be taken into account by a future smart lighting system, considering that a personalized illumination level is the key to a better working environment. Based on measurements concerning internal illuminance in regard to work place occupancy and outdoor weather conditions, user preferences probability functions are presented. It is shown that subjective criteria, related to personal preferences, differentiate behavior patterns even for users with similar objective characteristics. These patterns, along with the simulated daylight penetration and the effect of manual blinds, can lead to the proper estimation of the energy demand for a user oriented lighting installation.

  • ARM: Toward Adaptive and Robust Model for Reputation Aggregation

    In dynamic, open, and service-oriented computing environments, e.g., e-commerce and crowdsourcing, service consumers must choose one of the services or items to complete their tasks. Due to the scale and dynamic characteristics of these environments, service consumers may have little or no experience with the available services. To this end, reputation systems are proposed and have played a crucial role in the success of online service- oriented transactions. In this paper, we study the current reputation systems used in commercial environments. In these rating-based reputation systems, we found they are not only resilient to the changes (time lag) but also vulnerable to unfair ratings. To address the problems in parallel, we propose an adaptive reputation model (ARM). ARM can dynamically adjust its model parameters to adapt the latest changes in a service. To tackle time lag, the proposed model generalizes the fixed sliding window, used in current commercial platforms, into a dynamic sliding window mechanism. Thus, the model can completely mitigate the influence of obsolete ratings. To detect unfair ratings, our model implements a statistical strategy based on hypothesis testing after transforming the ratings in the linear window into residuals. Experiments not only validate the effectiveness of the proposed model but also show that it outperforms the existing reputation system by 45% on average based on five test cases. The results also show that the proposed model can asymptotically converge to the underlying reputation value as ratings begin to accumulate.

  • Image Compressed Sensing Recovery based on Multi-scale Group Sparse Representation

    Compressed Sensing (CS) is intended to recover a high-dimensional but sparse vector by a small number of linear sampling. Seeking an appropriate domain is of great importance to achieve a high enough degree of sparsity. In this paper, we propose a new scheme for image Compressed Sensing using multiscale strategy and structural group sparse representation, which efficiently characterizes the sparsity and multi-scale self-similarity of natural images in an adaptive group domain. Then, the group sparsity constraint and multi- scale self-similarity are exploited simultaneously under a unified framework. A multi-scale image pyramid is generated to construct the group during reconstruction. Meanwhile, effective dictionaries for each group are trained from the recovery image itself by a group-adaptive dictionary learning algorithm. Experimental results demonstrate that the proposed algorithm increases image CS recovery quality significantly and outperforms the state- of-the-art methods.



Standards related to Windows

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IEEE Standard for Digital Test Interchange Format (DTIF)

This standard will define the test program set data embodied in a number of ASCII files for stimulus, response, and diagnostics of digital systems for use on digital Automatic Test Systems.


IEEE Standard Test Procedures for Semiconductor X-Ray Energy Spectrometers


Standard for Utility Industry End Device Data Tables

To develop a standard for utility end device application layer communications protocol and the functional data structures which it transports. It is to allow operation of end devices for utility distribution and customer applications.



Jobs related to Windows

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