4. The performance of the proposed methods should be competitive with the conventional scheme which should open the possibility of extensive uses of JPEGXR.
The main contributions of this thesis to the JPEGXR encoding process are the precise and efficient control of the objective quality which should support high dynamic range floating data as well. The standard JPEGXR encoder scheme previously mentioned offers features including subjective qualitycontrol  and high dynamic range coding , but no qualitycontrol is supported to obtain stable images with given objective quality parameters like SNR and bit rate. Another limitation of built-in floating coding is low efficiency in the lossy mode. Although a number of methods were proposed to control the image compression ratio , these algorithms are format- related. In JPEGXR, only one proposed ratecontrol algorithm  mainly focused on the relationship between bit rate and distortion and is not precise enough.
In a closely related paper, Cicco et al.  measured the responsiveness of Skype video calls to bandwidth variations. They conclude that Skype’s response time to bandwidth in- crease is long. However, they only presented some empir- ical data, and did not systematically measure and model the stationary behaviors of Skype. We conducted extensive measurement of Skype under different network settings of packet losses, packet delays and available network bandwidth. Based on the measurements, we propose the models for Skype video calls’ ratecontrol, FEC redundancy, and video quality. There have been some other related studies on investigating the impact of user behaviors on network stability , . In , Tay et al. studied how TCP user aborts enable a network sustain a higher demand without causing congestion collapse. Bu et al. proposed in  that the user back-offs in VoIP will help maintain the network stability. They assumed
Due to the increasing demand for amazing graphic design in low-band applications (e.g. web sites) on the one hand and in heavy duty applications such as GIS on the other, image compression has gained great attention over the last two decades. Many standard generic compression techniques have effectively been employed for image compression. However, due to the peculiar nature of image data new image-oriented techniques have been devised. In particular, lossy compression has gained increasing popularity since the release of the JPEG standard  whose coding pipeline is considered a general standard scheme for high-performance coding. The same scheme is used by the JPEG2000 standard with minor structural modifications. Before entropy coding the data stream is pre-processed in order to reduce its entropy (see Figure 1). A linear transform is used to obtain a representation of the input image in a different domain. A (possibly uneven) quantisation is carried out on the transformed coefficients in order to smooth out high frequencies. The rationale for this is that the human vision system is little sensitive to high frequencies. Since high frequencies carry a high information content, quantisation considerably reduces the signal entropy while retaining perceptual quality. The transformed data is re-ordered so as to reduce the relative difference between quantised coefficients. This pre-processed stream is finally entropy coded using standard techniques (e.g. Huffman + run-length is used by JPEG). A compression ratecontrol is sometimes added.
Where appropriate, we highlight the differences of the respective approach when applied to JPEGXR instead to earlier formats. All algorithms are thoroughly evaluated by discussing possible compression impact, by estimating the provided security level (e.g. available key space, even- tual security breaches), and by assessing their respective applicability in real-world scenarios. Last but not least, format-compliant encryption methods allow for a visual security evaluation of encrypted images (i.e. the deter- mination of visual quality and the intelligibility of visual content). For this purpose, besides providing visual exam- ples of encrypted imagery, we use objective image quality metrics in combination with a public image database to assess the visual security of encrypted images and we rate the extent of control an encryption scheme provides to generate various levels of content protection.
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6. Experimental results
6.1 Region of interest (ROI) and tiling
Services for high definition image browsing on mobile devices require a careful design since the user experience is heavily depending on the network bandwidth, processing delay, display resolution, image quality. Modern applications require coding technologies providing tools for resolution and quality scalability, for accessing spatial regions of interest (ROI), for reducing the domain of the coding algorithm decomposing large images into tiles. This need occurs primarily in medical imaging applications, video surveillance systems, historical and GIS (Geographic Information System) images and in a considerable number of internet applications.
The updated format is based on the discrete wavelet transform (DWT), scalar quanti- zation, context modeling, arithmetic coding and post-compression rate allocation . The DWT can be implemented using either the reversible Le Gall (5,3) taps filter or the non- reversible Daubechies (9,7) taps biorthogonal filter . The latter provides higher compres- sion though does not support lossless coding. The quantizer remains independent for each sub-band while utilizing a dead-zone scalar technique. Each sub-band is partitioned into rectangular code-blocks, which are typically 64x64, and then entropy coded using context modeling and bit-plane arithmetic coding. Then the coded data is organized into layers of varying quality levels by using the post compression rate allocation, and finally output to the code-stream in packets .
same size across the three types of images. Whereas for mean square error (MSE), the difference between using 1 descriptor and 2 descriptors do not differ significantly. The other observations to note is the MSE difference between 1 descriptor and 2 descriptors are no more than 10%. This shows that the approach is suitable for even low bandwidth transmission. The experimental results also show that the use of horizontal pixel interleaving and vertical pixel interleaving give similar results. The difference between the two is less than 1dB for PSNR. Both methods are recommended for 2D DCT system. The other observation is on the choice of quantizers. The compression ratio for type II quantizer (in use for JPEG HA and VA model) is around twice better than type I quantizer ( in use for JPEG HH and VH model), the PSNR achieved is around 1.5 times poorer. Type II quantizer compresses an image by dividing every 2D DCT coefficients by a constant. The low frequency area is affected and hence the quality of re-constructed image. Type I quantizer successfully keep lower frequency coefficients without affecting it.
Eventually, besides improvements of detection accuracy, the second main contribution of present paper lies in the con- trol of the false-alarm probability (22). To show the rele- vance of the proposed methodology, Figure 3 contrasts the theoretical false alarm rate and the empirical ones over two different datasets of images, BOSSbase  and ALASKA base . One can note that the theoretical false-alarm rate deduced from CLT matches very well with empirical false- alarm rate up to below 10 −4 . Those results show both the rel- evance of the proposed approach, which allows setting a de- cision threshold as a function of the desired false-alarm rate, as well as the sharpness of the statistical model.
Creating, editing, and generating images in a very regular system today is a major priority. The original image data generated by the camera sensor is very large to store, so the efficiency is not high. Mobile or bandwidth- limited systems become particularly cumbersome, where the object is a conservative bandwidth cost, such as the World Wide Web. This situation requires the use of efficient image compression techniques, such as JPEG algorithm techniques, that perceive images with almost no loss of compressed image height. Today, the JPEG algorithm has become the actual standard for image compression. Can be the number of hardware MATLAB code output to the quantitative DCT version of the input image and technology used to achieve a fast way to investigate the JPEG algorithm. I. INTRODUCTION
At the Ninth AUN-BOT Meeting held on 12-13 November 2000 at Chulalongkorn University, Bangkok, Thailand, the Meeting hereby endorsed the Bangkok Accord on AUN-QA, which aims to promote the development of a quality assurance system as an instrument for maintaining, improving and enhancing teaching, research and the overall institutional academic standards of higher educational institutions of Member Universities. The Meeting recognized and respected the differences among Member Universities in their institutions and environment, including cultural as well as basic resources. In the spirit of collaboration, the Meeting agreed to develop standards and mechanisms for quality assurance in higher education, which could consequently lead to mutual recognition by Member Universities. In order to achieve this aim, AUN Board Members, who represent all AUN Member Universities in their countries, agreed:
Single screw extruders are selected for manufacture of HDPE pipe because they have adequate mixing capabilities; they also have the ability to overcome the considerable shear resistance of the molten resin at lower melt temperatures (than is the case for twin screw machines, also used for extrusion of plastics). Running between 75 and 150 rpm, outputs are in excess of 1500 lb/hr for the most common profiles. Single- screw extruders used in profile extrusion typically range from 1 to 6 inch diameters. The viscosity, melting point, thermal sensitivity and shear heating qualities of the molten resin all affect the quality of the extrudate. On leaving the die, the hot and flexible extrudate is shaped and cooled. Uniform and gradual cooling with air and chilled water inhibits unwanted variations in wall thickness and warpage of the end product.
are involved in the tests. Objective video quality metrics are often proposed because none of the QoS parameters can precisely define the QoE of multimedia services . These objective approaches are carried out by the use of algorithms and formulas. Peak Signal to Noise Ratio (PSNR) and Struc- tural Similarity (SSIM) are two full reference objective video quality metrics. They compare the original video with received (possibly distorted) video and calculate the MOS value. PSNR is mostly used for its simplicity and good correlation with the subjective video test result. PSNR tools are available to calculate the PSNR value. A possible mapping of PSNR to MOS is shown in Table I . However, this is a problematic approach as PSNR does not directly correspond to MOS . On the other hand, SSIM estimates the perceived quality frame by frame and is considered to have a higher correlation with subjective quality ratings . The SSIM index assumes that the human visual system is more oriented towards the identification of structural information in video sequences. It produces a score between 0 and 1 from original and received signals . The third approach is a hybrid between subjective and objective methods in which both the technical parameters as well as human rating are taken into account  . ITU recommends objective modeling of measurable technical performance and subjective testing with people .
In a router running the Cisco IOS XR software, the time clock in the primary RP is synchronized with the other RPs, DRPs and LCs in the system. This synchronization ensures that the standby RP has an accurate time setting if it assumes the primary role, and that the events in logs between different RPs, LCs and DRPs can be easily correlated during debugging.
Within the QA/QC system, good practice provides for greater effort for key source categories and for those source categories where data and methodological changes have recently occurred, than for other source categories. It is unlikely that inventory agencies will have sufficient resources to conduct all the QA/QC procedures outlined in this chapter on all source categories. In addition, it is not necessary to conduct all of these procedures every year. For example, data collection processes conducted by national statistical agencies are not likely to change significantly from one year to the next. Once the inventory agency has identified what quality controls are in place, assessed the uncertainty of that data, and documented the details for future inventory reference, it is unnecessary to revisit this aspect of the QC procedure every year. However, it is good practice to check the validity of this information periodically as changes in sample size, methods of collection, or frequency of data collection may occur. The optimal frequency of such checks will depend on national circumstances. While focusing QA/QC activities on key source categories will lead to the most significant improvements in the overall inventory estimates, it is good practice to plan to conduct at least the general procedures outlined in Section 8.6, General QC Procedures (Tier 1), on all parts of the inventory over a period of time. Some source categories may require more frequent QA/QC than others because of their significance to the total inventory estimates, contribution to trends in emissions over time or changes in data or characteristics of the source category, including the level of uncertainty. For example, if technological advancements occur in an industrial source category, it is good practice to conduct a thorough QC check of the data sources and the compilation process to ensure that the inventory methods remain appropriate.
number between 0 and 100, used to parameterize a quantization matrix. The greater this number is, the less information is lost. The problem is that the QF value can influence the each image quality differently when the quality is assessed by Full- Reference measures [2, 8]. The paper  shows that when compressing different images by JPEG algorithm with the same compression factor, a different compression efficiency is obtained. In the paper  it was showed that the image qual- ity after processing by JPEG algorithm depends on the image content. The image quality was as- sessed by the following measures: Compression Ratio (CR), Signal to Noise Ratio (SNR), Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE)  and the Structural similarity (SSIM) index method .
Sometimes replicate samples may be run to check for consistency between samples – the same sample is run two or more times, usually at different stages in the batch of runs (and not one straight after the other).
A particular example of the use of replicates is in the analysis of samples taken from athletes as part of doping control. Each sample is split into two – the A and B samples. If sample A tests positive for a banned substance, then sample B is analysed, and, if this also tests positive, the athlete is considered to have tested positive for the banned substance.
0.7 determines the value of λ in Table 1. The third panel (plots (c) and (g)) shows the synchrogram for the entire interval of high-rate breathing. During the phase synchronization points on synchrogram demonstrate a plateau. Such plateaus represent one signal’s phase not changing by more than an entire period relative to the phase of the second signal. The final panel (plots (d) and (h)) are a representation of the heart and respiratory rates for a com- parison of instantaneous rates during episodes of synchronization with dynamics of phases. The dashed red lines represent the high variability of breathing rate even for controlled breathing- the larger this range, the more vari- able the breathing rate and thus the worse a volunteer maintained a constant rate. The solid red line is the average breathing rate, and the blue line demonstrates the dynamics of the instantaneous breathing rate throughout the interval. The black line in plots (d) and (h) corresponds to heart rate with removed high-frequency oscillations via applying moving average techniques. During episodes of phase synchronization, the black line is expected to fall wholly between the dashed red lines, representing the fact that the variability of heart rate is contained within the variability of breathing rate.