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Search results for: lossless compression

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</div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: lossless compression</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">916</span> Image Compression Using Block Power Method for SVD Decomposition</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=El%20Asnaoui%20Khalid">El Asnaoui Khalid</a>, <a href="https://publications.waset.org/abstracts/search?q=Chawki%20Youness"> Chawki Youness</a>, <a href="https://publications.waset.org/abstracts/search?q=Aksasse%20Brahim"> Aksasse Brahim</a>, <a href="https://publications.waset.org/abstracts/search?q=Ouanan%20Mohammed"> Ouanan Mohammed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In these recent decades, the important and fast growth in the development and demand of multimedia products is contributing to an insufficient in the bandwidth of device and network storage memory. Consequently, the theory of data compression becomes more significant for reducing the data redundancy in order to save more transfer and storage of data. In this context, this paper addresses the problem of the lossless and the near-lossless compression of images. This proposed method is based on Block SVD Power Method that overcomes the disadvantages of Matlab's SVD function. The experimental results show that the proposed algorithm has a better compression performance compared with the existing compression algorithms that use the Matlab's SVD function. In addition, the proposed approach is simple and can provide different degrees of error resilience, which gives, in a short execution time, a better image compression. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20compression" title="image compression">image compression</a>, <a href="https://publications.waset.org/abstracts/search?q=SVD" title=" SVD"> SVD</a>, <a href="https://publications.waset.org/abstracts/search?q=block%20SVD%20power%20method" title=" block SVD power method"> block SVD power method</a>, <a href="https://publications.waset.org/abstracts/search?q=lossless%20compression" title=" lossless compression"> lossless compression</a>, <a href="https://publications.waset.org/abstracts/search?q=near%20lossless" title=" near lossless"> near lossless</a> </p> <a href="https://publications.waset.org/abstracts/34041/image-compression-using-block-power-method-for-svd-decomposition" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/34041.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">387</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">915</span> A Survey on Lossless Compression of Bayer Color Filter Array Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alina%20Trifan">Alina Trifan</a>, <a href="https://publications.waset.org/abstracts/search?q=Ant%C3%B3nio%20J.%20R.%20Neves"> Ant贸nio J. R. Neves</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Although most digital cameras acquire images in a raw format, based on a Color Filter Array that arranges RGB color filters on a square grid of photosensors, most image compression techniques do not use the raw data; instead, they use the rgb result of an interpolation algorithm of the raw data. This approach is inefficient and by performing a lossless compression of the raw data, followed by pixel interpolation, digital cameras could be more power efficient and provide images with increased resolution given that the interpolation step could be shifted to an external processing unit. In this paper, we conduct a survey on the use of lossless compression algorithms with raw Bayer images. Moreover, in order to reduce the effect of the transition between colors that increase the entropy of the raw Bayer image, we split the image into three new images corresponding to each channel (red, green and blue) and we study the same compression algorithms applied to each one individually. This simple pre-processing stage allows an improvement of more than 15% in predictive based methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bayer%20image" title="bayer image">bayer image</a>, <a href="https://publications.waset.org/abstracts/search?q=CFA" title=" CFA"> CFA</a>, <a href="https://publications.waset.org/abstracts/search?q=lossless%20compression" title=" lossless compression"> lossless compression</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20coding%20standards" title=" image coding standards"> image coding standards</a> </p> <a href="https://publications.waset.org/abstracts/39918/a-survey-on-lossless-compression-of-bayer-color-filter-array-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39918.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">320</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">914</span> An Online 3D Modeling Method Based on a Lossless Compression Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jiankang%20Wang">Jiankang Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Hongyang%20Yu"> Hongyang Yu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper proposes a portable online 3D modeling method. The method first utilizes a depth camera to collect data and compresses the depth data using a frame-by-frame lossless data compression method. The color image is encoded using the H.264 encoding format. After the cloud obtains the color image and depth image, a 3D modeling method based on bundlefusion is used to complete the 3D modeling. The results of this study indicate that this method has the characteristics of portability, online, and high efficiency and has a wide range of application prospects. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=3D%20reconstruction" title="3D reconstruction">3D reconstruction</a>, <a href="https://publications.waset.org/abstracts/search?q=bundlefusion" title=" bundlefusion"> bundlefusion</a>, <a href="https://publications.waset.org/abstracts/search?q=lossless%20compression" title=" lossless compression"> lossless compression</a>, <a href="https://publications.waset.org/abstracts/search?q=depth%20image" title=" depth image"> depth image</a> </p> <a href="https://publications.waset.org/abstracts/163266/an-online-3d-modeling-method-based-on-a-lossless-compression-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/163266.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">82</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">913</span> Image Compression on Region of Interest Based on SPIHT Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sudeepti%20Dayal">Sudeepti Dayal</a>, <a href="https://publications.waset.org/abstracts/search?q=Neelesh%20Gupta"> Neelesh Gupta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Image abbreviation is utilized for reducing the size of a file without demeaning the quality of the image to an objectionable level. The depletion in file size permits more images to be deposited in a given number of spaces. It also minimizes the time necessary for images to be transferred. Storage of medical images is a most researched area in the current scenario. To store a medical image, there are two parameters on which the image is divided, regions of interest and non-regions of interest. The best way to store an image is to compress it in such a way that no important information is lost. Compression can be done in two ways, namely lossy, and lossless compression. Under that, several compression algorithms are applied. In the paper, two algorithms are used which are, discrete cosine transform, applied to non-region of interest (lossy), and discrete wavelet transform, applied to regions of interest (lossless). The paper introduces SPIHT (set partitioning hierarchical tree) algorithm which is applied onto the wavelet transform to obtain good compression ratio from which an image can be stored efficiently. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Compression%20ratio" title="Compression ratio">Compression ratio</a>, <a href="https://publications.waset.org/abstracts/search?q=DWT" title=" DWT"> DWT</a>, <a href="https://publications.waset.org/abstracts/search?q=SPIHT" title=" SPIHT"> SPIHT</a>, <a href="https://publications.waset.org/abstracts/search?q=DCT" title=" DCT"> DCT</a> </p> <a href="https://publications.waset.org/abstracts/43377/image-compression-on-region-of-interest-based-on-spiht-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43377.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">349</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">912</span> PEINS: A Generic Compression Scheme Using Probabilistic Encoding and Irrational Number Storage</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=P.%20Jayashree">P. Jayashree</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Rajkumar"> S. Rajkumar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With social networks and smart devices generating a multitude of data, effective data management is the need of the hour for networks and cloud applications. Some applications need effective storage while some other applications need effective communication over networks and data reduction comes as a handy solution to meet out both requirements. Most of the data compression techniques are based on data statistics and may result in either lossy or lossless data reductions. Though lossy reductions produce better compression ratios compared to lossless methods, many applications require data accuracy and miniature details to be preserved. A variety of data compression algorithms does exist in the literature for different forms of data like text, image, and multimedia data. In the proposed work, a generic progressive compression algorithm, based on probabilistic encoding, called PEINS is projected as an enhancement over irrational number stored coding technique to cater to storage issues of increasing data volumes as a cost effective solution, which also offers data security as a secondary outcome to some extent. The proposed work reveals cost effectiveness in terms of better compression ratio with no deterioration in compression time. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=compression%20ratio" title="compression ratio">compression ratio</a>, <a href="https://publications.waset.org/abstracts/search?q=generic%20compression" title=" generic compression"> generic compression</a>, <a href="https://publications.waset.org/abstracts/search?q=irrational%20number%20storage" title=" irrational number storage"> irrational number storage</a>, <a href="https://publications.waset.org/abstracts/search?q=probabilistic%20encoding" title=" probabilistic encoding"> probabilistic encoding</a> </p> <a href="https://publications.waset.org/abstracts/60542/peins-a-generic-compression-scheme-using-probabilistic-encoding-and-irrational-number-storage" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/60542.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">294</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">911</span> A QoS Aware Cluster Based Routing Algorithm for Wireless Mesh Network Using LZW Lossless Compression</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=J.%20S.%20Saini">J. S. Saini</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20P.%20K.%20Sandhu"> P. P. K. Sandhu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The multi-hop nature of Wireless Mesh Networks and the hasty progression of throughput demands results in multi- channels and multi-radios structures in mesh networks, but the main problem of co-channels interference reduces the total throughput, specifically in multi-hop networks. Quality of Service mentions a vast collection of networking technologies and techniques that guarantee the ability of a network to make available desired services with predictable results. Quality of Service (QoS) can be directed at a network interface, towards a specific server or router's performance, or in specific applications. Due to interference among various transmissions, the QoS routing in multi-hop wireless networks is formidable task. In case of multi-channel wireless network, since two transmissions using the same channel may interfere with each other. This paper has considered the Destination Sequenced Distance Vector (DSDV) routing protocol to locate the secure and optimised path. The proposed technique also utilizes the Lempel鈥揨iv鈥揥elch (LZW) based lossless data compression and intra cluster data aggregation to enhance the communication between the source and the destination. The use of clustering has the ability to aggregate the multiple packets and locates a single route using the clusters to improve the intra cluster data aggregation. The use of the LZW based lossless data compression has ability to reduce the data packet size and hence it will consume less energy, thus increasing the network QoS. The MATLAB tool has been used to evaluate the effectiveness of the projected technique. The comparative analysis has shown that the proposed technique outperforms over the existing techniques. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=WMNS" title="WMNS">WMNS</a>, <a href="https://publications.waset.org/abstracts/search?q=QOS" title=" QOS"> QOS</a>, <a href="https://publications.waset.org/abstracts/search?q=flooding" title=" flooding"> flooding</a>, <a href="https://publications.waset.org/abstracts/search?q=collision%20avoidance" title=" collision avoidance"> collision avoidance</a>, <a href="https://publications.waset.org/abstracts/search?q=LZW" title=" LZW"> LZW</a>, <a href="https://publications.waset.org/abstracts/search?q=congestion%20control" title=" congestion control"> congestion control</a> </p> <a href="https://publications.waset.org/abstracts/31412/a-qos-aware-cluster-based-routing-algorithm-for-wireless-mesh-network-using-lzw-lossless-compression" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31412.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">338</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">910</span> Scintigraphic Image Coding of Region of Interest Based on SPIHT Algorithm Using Global Thresholding and Huffman Coding</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Seddiki">A. Seddiki</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Djebbouri"> M. Djebbouri</a>, <a href="https://publications.waset.org/abstracts/search?q=D.%20Guerchi"> D. Guerchi </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Medical imaging produces human body pictures in digital form. Since these imaging techniques produce prohibitive amounts of data, compression is necessary for storage and communication purposes. Many current compression schemes provide a very high compression rate but with considerable loss of quality. On the other hand, in some areas in medicine, it may be sufficient to maintain high image quality only in region of interest (ROI). This paper discusses a contribution to the lossless compression in the region of interest of Scintigraphic images based on SPIHT algorithm and global transform thresholding using Huffman coding. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=global%20thresholding%20transform" title="global thresholding transform">global thresholding transform</a>, <a href="https://publications.waset.org/abstracts/search?q=huffman%20coding" title=" huffman coding"> huffman coding</a>, <a href="https://publications.waset.org/abstracts/search?q=region%20of%20interest" title=" region of interest"> region of interest</a>, <a href="https://publications.waset.org/abstracts/search?q=SPIHT%20coding" title=" SPIHT coding"> SPIHT coding</a>, <a href="https://publications.waset.org/abstracts/search?q=scintigraphic%20images" title=" scintigraphic images"> scintigraphic images</a> </p> <a href="https://publications.waset.org/abstracts/17067/scintigraphic-image-coding-of-region-of-interest-based-on-spiht-algorithm-using-global-thresholding-and-huffman-coding" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17067.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">367</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">909</span> Lossless Secret Image Sharing Based on Integer Discrete Cosine Transform</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Li%20Li">Li Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmed%20A.%20Abd%20El-Latif"> Ahmed A. Abd El-Latif</a>, <a href="https://publications.waset.org/abstracts/search?q=Aya%20El-Fatyany"> Aya El-Fatyany</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Amin"> Mohamed Amin </a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper proposes a new secret image sharing method based on integer discrete cosine transform (IntDCT). It first transforms the original image into the frequency domain (DCT coefficients) using IntDCT, which are operated on each block with size 8*8. Then, it generates shares among each DCT coefficients in the same place of each block, that is, all the DC components are used to generate DC shares, the ith AC component in each block are utilized to generate ith AC shares, and so on. The DC and AC shares components with the same number are combined together to generate DCT shadows. Experimental results and analyses show that the proposed method can recover the original image lossless than those methods based on traditional DCT and is more sensitive to tiny change in both the coefficients and the content of the image. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=secret%20image%20sharing" title="secret image sharing">secret image sharing</a>, <a href="https://publications.waset.org/abstracts/search?q=integer%20DCT" title=" integer DCT"> integer DCT</a>, <a href="https://publications.waset.org/abstracts/search?q=lossless%20recovery" title=" lossless recovery"> lossless recovery</a>, <a href="https://publications.waset.org/abstracts/search?q=sensitivity" title=" sensitivity"> sensitivity</a> </p> <a href="https://publications.waset.org/abstracts/36824/lossless-secret-image-sharing-based-on-integer-discrete-cosine-transform" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/36824.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">398</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">908</span> Embedded Digital Image System </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dawei%20Li">Dawei Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Cheng%20Liu"> Cheng Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Yiteng%20Liu"> Yiteng Liu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper introduces an embedded digital image system for Chinese space environment vertical exploration sounding rocket. In order to record the flight status of the sounding rocket as well as the payloads, an onboard embedded image processing system based on ADV212, a JPEG2000 compression chip, is designed in this paper. Since the sounding rocket is not designed to be recovered, all image data should be transmitted to the ground station before the re-entry while the downlink band used for the image transmission is only about 600 kbps. Under the same condition of compression ratio compared with other algorithm, JPEG2000 standard algorithm can achieve better image quality. So JPEG2000 image compression is applied under this condition with a limited downlink data band. This embedded image system supports lossless to 200:1 real time compression, with two cameras to monitor nose ejection and motor separation, and two cameras to monitor boom deployment. The encoder, ADV7182, receives PAL signal from the camera, then output the ITU-R BT.656 signal to ADV212. ADV7182 switches between four input video channels as the program sequence. Two SRAMs are used for Ping-pong operation and one 512 Mb SDRAM for buffering high frame-rate images. The whole image system has the characteristics of low power dissipation, low cost, small size and high reliability, which is rather suitable for this sounding rocket application. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ADV212" title="ADV212">ADV212</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20system" title=" image system"> image system</a>, <a href="https://publications.waset.org/abstracts/search?q=JPEG2000" title=" JPEG2000"> JPEG2000</a>, <a href="https://publications.waset.org/abstracts/search?q=sounding%20rocket" title=" sounding rocket"> sounding rocket</a> </p> <a href="https://publications.waset.org/abstracts/37615/embedded-digital-image-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/37615.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">421</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">907</span> Bitplanes Gray-Level Image Encryption Approach Using Arnold Transform</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ali%20Abdrhman%20M.%20Ukasha">Ali Abdrhman M. Ukasha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Data security needed in data transmission, storage, and communication to ensure the security. The single step parallel contour extraction (SSPCE) method is used to create the edge map as a key image from the different Gray level/Binary image. Performing the X-OR operation between the key image and each bit plane of the original image for image pixel values change purpose. The Arnold transform used to changes the locations of image pixels as image scrambling process. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Gary level image and completely reconstructed without any distortion. Also shown that the analyzed algorithm have extremely large security against some attacks like salt & pepper and JPEG compression. Its proof that the Gray level image can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=SSPCE%20method" title="SSPCE method">SSPCE method</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20compression-salt-%20peppers%20attacks" title=" image compression-salt- peppers attacks"> image compression-salt- peppers attacks</a>, <a href="https://publications.waset.org/abstracts/search?q=bitplanes%20decomposition" title=" bitplanes decomposition"> bitplanes decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=Arnold%20transform" title=" Arnold transform"> Arnold transform</a>, <a href="https://publications.waset.org/abstracts/search?q=lossless%20image%20encryption" title=" lossless image encryption"> lossless image encryption</a> </p> <a href="https://publications.waset.org/abstracts/14573/bitplanes-gray-level-image-encryption-approach-using-arnold-transform" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14573.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">435</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">906</span> GPU Accelerated Fractal Image Compression for Medical Imaging in Parallel Computing Platform</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Md.%20Enamul%20Haque">Md. Enamul Haque</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdullah%20Al%20Kaisan"> Abdullah Al Kaisan</a>, <a href="https://publications.waset.org/abstracts/search?q=Mahmudur%20R.%20Saniat"> Mahmudur R. Saniat</a>, <a href="https://publications.waset.org/abstracts/search?q=Aminur%20Rahman"> Aminur Rahman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we have implemented both sequential and parallel version of fractal image compression algorithms using CUDA (Compute Unified Device Architecture) programming model for parallelizing the program in Graphics Processing Unit for medical images, as they are highly similar within the image itself. There is several improvements in the implementation of the algorithm as well. Fractal image compression is based on the self similarity of an image, meaning an image having similarity in majority of the regions. We take this opportunity to implement the compression algorithm and monitor the effect of it using both parallel and sequential implementation. Fractal compression has the property of high compression rate and the dimensionless scheme. Compression scheme for fractal image is of two kinds, one is encoding and another is decoding. Encoding is very much computational expensive. On the other hand decoding is less computational. The application of fractal compression to medical images would allow obtaining much higher compression ratios. While the fractal magnification an inseparable feature of the fractal compression would be very useful in presenting the reconstructed image in a highly readable form. However, like all irreversible methods, the fractal compression is connected with the problem of information loss, which is especially troublesome in the medical imaging. A very time consuming encoding process, which can last even several hours, is another bothersome drawback of the fractal compression. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=accelerated%20GPU" title="accelerated GPU">accelerated GPU</a>, <a href="https://publications.waset.org/abstracts/search?q=CUDA" title=" CUDA"> CUDA</a>, <a href="https://publications.waset.org/abstracts/search?q=parallel%20computing" title=" parallel computing"> parallel computing</a>, <a href="https://publications.waset.org/abstracts/search?q=fractal%20image%20compression" title=" fractal image compression"> fractal image compression</a> </p> <a href="https://publications.waset.org/abstracts/5645/gpu-accelerated-fractal-image-compression-for-medical-imaging-in-parallel-computing-platform" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5645.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">335</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">905</span> Bitplanes Image Encryption/Decryption Using Edge Map (SSPCE Method) and Arnold Transform</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ali%20A.%20Ukasha">Ali A. Ukasha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Data security needed in data transmission, storage, and communication to ensure the security. The single step parallel contour extraction (SSPCE) method is used to create the edge map as a key image from the different Gray level/Binary image. Performing the X-OR operation between the key image and each bit plane of the original image for image pixel values change purpose. The Arnold transform used to changes the locations of image pixels as image scrambling process. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Gary level image and completely reconstructed without any distortion. Also shown that the analyzed algorithm have extremely large security against some attacks like salt & pepper and JPEG compression. Its proof that the Gray level image can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=SSPCE%20method" title="SSPCE method">SSPCE method</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20compression" title=" image compression"> image compression</a>, <a href="https://publications.waset.org/abstracts/search?q=salt%20and%0D%0Apeppers%20attacks" title=" salt and peppers attacks"> salt and peppers attacks</a>, <a href="https://publications.waset.org/abstracts/search?q=bitplanes%20decomposition" title=" bitplanes decomposition"> bitplanes decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=Arnold%20transform" title=" Arnold transform"> Arnold transform</a>, <a href="https://publications.waset.org/abstracts/search?q=lossless%20image%20encryption" title=" lossless image encryption"> lossless image encryption</a> </p> <a href="https://publications.waset.org/abstracts/14570/bitplanes-image-encryptiondecryption-using-edge-map-sspce-method-and-arnold-transform" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14570.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">497</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">904</span> Equivalent Circuit Representation of Lossless and Lossy Power Transmission Systems Including Discrete Sampler</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yuichi%20Kida">Yuichi Kida</a>, <a href="https://publications.waset.org/abstracts/search?q=Takuro%20Kida"> Takuro Kida</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In a new smart society supported by the recent development of 5G and 6G Communication systems, the im- portance of wireless power transmission is increasing. These systems contain discrete sampling systems in the middle of the transmission path and equivalent circuit representation of lossless or lossy power transmission through these systems is an important issue in circuit theory. In this paper, for the given weight function, we show that a lossless power transmission system with the given weight is expressed by an equivalent circuit representation of the Kida鈥檚 optimal signal prediction system followed by a reactance multi-port circuit behind it. Further, it is shown that, when the system is lossy, the system has an equivalent circuit in the form of connecting a multi-port positive-real circuit behind the Kida鈥檚 optimal signal prediction system. Also, for the convenience of the reader, in this paper, the equivalent circuit expression of the reactance multi-port circuit and the positive- real multi-port circuit by Cauer and Ohno, whose information is currently being lost even in the world of the Internet. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=signal%20prediction" title="signal prediction">signal prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=pseudo%20inverse%20matrix" title=" pseudo inverse matrix"> pseudo inverse matrix</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20%20intelligence" title=" artificial intelligence"> artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=power%20transmission" title=" power transmission"> power transmission</a> </p> <a href="https://publications.waset.org/abstracts/144600/equivalent-circuit-representation-of-lossless-and-lossy-power-transmission-systems-including-discrete-sampler" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/144600.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">122</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">903</span> Comparison of Compression Properties of Stretchable Knitted Fabrics and Bi-Stretch Woven Fabrics for Compression Garments</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Maqsood">Muhammad Maqsood</a>, <a href="https://publications.waset.org/abstracts/search?q=Yasir%20Nawab"> Yasir Nawab</a>, <a href="https://publications.waset.org/abstracts/search?q=Syed%20Talha%20Ali%20Hamdani"> Syed Talha Ali Hamdani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Stretchable fabrics have diverse applications ranging from casual apparel to performance sportswear and compression therapy. Compression therapy is the universally accepted treatment for the management of hypertrophic scarring after severe burns. Mostly stretchable knitted fabrics are used in compression therapy but in the recent past, some studies have also been found on bi-stretch woven fabrics being used as compression garments as they also have been found quite effective in the treatment of oedema. Therefore, the objective of the present study is to compare the compression properties of stretchable knitted and bi-stretch woven fabrics for compression garments. For this purpose four woven structures and four knitted structures were produced having the same areal density and their compression, comfort and mechanical properties were compared before and after 5, 10 and 15 washes. Four knitted structures used were single jersey, single locaste, plain pique and the honeycomb, whereas four woven structures produced were 1/1 plain, 2/1 twill, 3/1 twill and 4/1 twill. The compression properties of the produced samples were tested by using kikuhime pressure sensor and it was found that bi-stretch woven fabrics possessed better compression properties before and after washes and retain their durability after repeated use, whereas knitted stretchable fabrics lost their compression ability after repeated use and the required sub garment pressure of the knitted structures after 15 washes was almost half to that of woven bi-stretch fabrics. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=compression%20garments" title="compression garments">compression garments</a>, <a href="https://publications.waset.org/abstracts/search?q=knitted%20structures" title=" knitted structures"> knitted structures</a>, <a href="https://publications.waset.org/abstracts/search?q=medical%20textiles" title=" medical textiles"> medical textiles</a>, <a href="https://publications.waset.org/abstracts/search?q=woven%20bi-stretch" title=" woven bi-stretch"> woven bi-stretch</a> </p> <a href="https://publications.waset.org/abstracts/39769/comparison-of-compression-properties-of-stretchable-knitted-fabrics-and-bi-stretch-woven-fabrics-for-compression-garments" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39769.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">411</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">902</span> A High Compression Ratio for a Losseless Image Compression Based on the Arithmetic Coding with the Sorted Run Length Coding: Meteosat Second Generation Image Compression</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Cherifi%20Mehdi">Cherifi Mehdi</a>, <a href="https://publications.waset.org/abstracts/search?q=Lahdir%20Mourad"> Lahdir Mourad</a>, <a href="https://publications.waset.org/abstracts/search?q=Ameur%20Soltane"> Ameur Soltane</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Image compression is the heart of several multimedia techniques. It is used to reduce the number of bits required to represent an image. Meteosat Second Generation (MSG) satellite allows the acquisition of 12 image files every 15 minutes and that results in a large databases sizes. In this paper, a novel image compression method based on the arithmetic coding with the sorted Run Length Coding (SRLC) for MSG images is proposed. The SRLC allows us to find the occurrence of the consecutive pixels of the original image to create a sorted run. The arithmetic coding allows the encoding of the sorted data of the previous stage to retrieve a unique code word that represents a binary code stream in the sorted order to boost the compression ratio. Through this article, we show that our method can perform the best results concerning compression ratio and bit rate unlike the method based on the Run Length Coding (RLC) and the arithmetic coding. Evaluation criteria like the compression ratio and the bit rate allow the confirmation of the efficiency of our method of image compression. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20compression" title="image compression">image compression</a>, <a href="https://publications.waset.org/abstracts/search?q=arithmetic%20coding" title=" arithmetic coding"> arithmetic coding</a>, <a href="https://publications.waset.org/abstracts/search?q=Run%20Length%20Coding" title=" Run Length Coding"> Run Length Coding</a>, <a href="https://publications.waset.org/abstracts/search?q=RLC" title=" RLC"> RLC</a>, <a href="https://publications.waset.org/abstracts/search?q=Sorted%20Run%20Length%20Coding" title=" Sorted Run Length Coding"> Sorted Run Length Coding</a>, <a href="https://publications.waset.org/abstracts/search?q=SRLC" title=" SRLC"> SRLC</a>, <a href="https://publications.waset.org/abstracts/search?q=Meteosat%20Second%20Generation" title=" Meteosat Second Generation"> Meteosat Second Generation</a>, <a href="https://publications.waset.org/abstracts/search?q=MSG" title=" MSG"> MSG</a> </p> <a href="https://publications.waset.org/abstracts/16704/a-high-compression-ratio-for-a-losseless-image-compression-based-on-the-arithmetic-coding-with-the-sorted-run-length-coding-meteosat-second-generation-image-compression" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16704.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">354</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">901</span> Medical Image Compression Based on Region of Interest: A Review</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sudeepti%20Dayal">Sudeepti Dayal</a>, <a href="https://publications.waset.org/abstracts/search?q=Neelesh%20Gupta"> Neelesh Gupta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In terms of transmission, bigger the size of any image, longer the time the channel takes for transmission. It is understood that the bandwidth of the channel is fixed. Therefore, if the size of an image is reduced, a larger number of data or images can be transmitted over the channel. Compression is the technique used to reduce the size of an image. In terms of storage, compression reduces the file size which it occupies on the disk. Any image is based on two parameters, region of interest and non-region of interest. There are several algorithms of compression that compress the data more economically. In this paper we have reviewed region of interest and non-region of interest based compression techniques and the algorithms which compress the image most efficiently. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=compression%20ratio" title="compression ratio">compression ratio</a>, <a href="https://publications.waset.org/abstracts/search?q=region%20of%20interest" title=" region of interest"> region of interest</a>, <a href="https://publications.waset.org/abstracts/search?q=DCT" title=" DCT"> DCT</a>, <a href="https://publications.waset.org/abstracts/search?q=DWT" title=" DWT"> DWT</a> </p> <a href="https://publications.waset.org/abstracts/43380/medical-image-compression-based-on-region-of-interest-a-review" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43380.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">374</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">900</span> Perceptual Image Coding by Exploiting Internal Generative Mechanism</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kuo-Cheng%20Liu">Kuo-Cheng Liu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the perceptual image coding, the objective is to shape the coding distortion such that the amplitude of distortion does not exceed the error visibility threshold, or to remove perceptually redundant signals from the image. While most researches focus on color image coding, the perceptual-based quantizer developed for luminance signals are always directly applied to chrominance signals such that the color image compression methods are inefficient. In this paper, the internal generative mechanism is integrated into the design of a color image compression method. The internal generative mechanism working model based on the structure-based spatial masking is used to assess the subjective distortion visibility thresholds that are visually consistent to human eyes better. The estimation method of structure-based distortion visibility thresholds for color components is further presented in a locally adaptive way to design quantization process in the wavelet color image compression scheme. Since the lowest subband coefficient matrix of images in the wavelet domain preserves the local property of images in the spatial domain, the error visibility threshold inherent in each coefficient of the lowest subband for each color component is estimated by using the proposed spatial error visibility threshold assessment. The threshold inherent in each coefficient of other subbands for each color component is then estimated in a local adaptive fashion based on the distortion energy allocation. By considering that the error visibility thresholds are estimated using predicting and reconstructed signals of the color image, the coding scheme incorporated with locally adaptive perceptual color quantizer does not require side information. Experimental results show that the entropies of three color components obtained by using proposed IGM-based color image compression scheme are lower than that obtained by using the existing color image compression method at perceptually lossless visual quality. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=internal%20generative%20mechanism" title="internal generative mechanism">internal generative mechanism</a>, <a href="https://publications.waset.org/abstracts/search?q=structure-based%20spatial%20masking" title=" structure-based spatial masking"> structure-based spatial masking</a>, <a href="https://publications.waset.org/abstracts/search?q=visibility%20threshold" title=" visibility threshold"> visibility threshold</a>, <a href="https://publications.waset.org/abstracts/search?q=wavelet%20domain" title=" wavelet domain"> wavelet domain</a> </p> <a href="https://publications.waset.org/abstracts/75216/perceptual-image-coding-by-exploiting-internal-generative-mechanism" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/75216.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">248</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">899</span> Color Image Compression/Encryption/Contour Extraction using 3L-DWT and SSPCE Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ali%20A.%20Ukasha">Ali A. Ukasha</a>, <a href="https://publications.waset.org/abstracts/search?q=Majdi%20F.%20Elbireki"> Majdi F. Elbireki</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20F.%20Abdullah"> Mohammad F. Abdullah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Data security needed in data transmission, storage, and communication to ensure the security. This paper is divided into two parts. This work interests with the color image which is decomposed into red, green and blue channels. The blue and green channels are compressed using 3-levels discrete wavelet transform. The Arnold transform uses to changes the locations of red image channel pixels as image scrambling process. Then all these channels are encrypted separately using the key image that has same original size and are generating using private keys and modulo operations. Performing the X-OR and modulo operations between the encrypted channels images for image pixel values change purpose. The extracted contours from color images recovery can be obtained with accepted level of distortion using single step parallel contour extraction (SSPCE) method. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Color images and completely reconstructed without any distortion. Also shown that the analyzed algorithm has extremely large security against some attacks like salt and pepper and Jpeg compression. Its proof that the color images can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=SSPCE%20method" title="SSPCE method">SSPCE method</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20compression%20and%20salt%20and%20peppers%20attacks" title=" image compression and salt and peppers attacks"> image compression and salt and peppers attacks</a>, <a href="https://publications.waset.org/abstracts/search?q=bitplanes%20decomposition" title=" bitplanes decomposition"> bitplanes decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=Arnold%20transform" title=" Arnold transform"> Arnold transform</a>, <a href="https://publications.waset.org/abstracts/search?q=color%20image" title=" color image"> color image</a>, <a href="https://publications.waset.org/abstracts/search?q=wavelet%20transform" title=" wavelet transform"> wavelet transform</a>, <a href="https://publications.waset.org/abstracts/search?q=lossless%20image%20encryption" title=" lossless image encryption"> lossless image encryption</a> </p> <a href="https://publications.waset.org/abstracts/18519/color-image-compressionencryptioncontour-extraction-using-3l-dwt-and-sspce-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18519.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">518</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">898</span> QCARNet: Networks for Quality-Adaptive Compression Artifact</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Seung%20Ho%20Park">Seung Ho Park</a>, <a href="https://publications.waset.org/abstracts/search?q=Young%20Su%20Moon"> Young Su Moon</a>, <a href="https://publications.waset.org/abstracts/search?q=Nam%20Ik%20Cho"> Nam Ik Cho</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We propose a convolution neural network (CNN) for quality adaptive compression artifact reduction named QCARNet. The proposed method is different from the existing discriminative models that learn a specific model at a certain quality level. The method is composed of a quality estimation CNN (QECNN) and a compression artifact reduction CNN (CARCNN), which are two functionally separate CNNs. By connecting the QECNN and CARCNN, each CARCNN layer is able to adaptively reduce compression artifacts and preserve details depending on the estimated quality level map generated by the QECNN. We experimentally demonstrate that the proposed method achieves better performance compared to other state-of-the-art blind compression artifact reduction methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=compression%20artifact%20reduction" title="compression artifact reduction">compression artifact reduction</a>, <a href="https://publications.waset.org/abstracts/search?q=deblocking" title=" deblocking"> deblocking</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20denoising" title=" image denoising"> image denoising</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20restoration" title=" image restoration"> image restoration</a> </p> <a href="https://publications.waset.org/abstracts/108816/qcarnet-networks-for-quality-adaptive-compression-artifact" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/108816.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">139</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">897</span> Compression Index Estimation by Water Content and Liquid Limit and Void Ratio Using Statistics Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lizhou%20Chen">Lizhou Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdelhamid%20Belgaid"> Abdelhamid Belgaid</a>, <a href="https://publications.waset.org/abstracts/search?q=Assem%20Elsayed"> Assem Elsayed</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiaoming%20Yang"> Xiaoming Yang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Compression index is essential in foundation settlement calculation. The traditional method for determining compression index is consolidation test which is expensive and time consuming. Many researchers have used regression methods to develop empirical equations for predicting compression index from soil properties. Based on a large number of compression index data collected from consolidation tests, the accuracy of some popularly empirical equations were assessed. It was found that primary compression index is significantly overestimated in some equations while it is underestimated in others. The sensitivity analyses of soil parameters including water content, liquid limit and void ratio were performed. The results indicate that the compression index obtained from void ratio is most accurate. The ANOVA (analysis of variance) demonstrates that the equations with multiple soil parameters cannot provide better predictions than the equations with single soil parameter. In other words, it is not necessary to develop the relationships between compression index and multiple soil parameters. Meanwhile, it was noted that secondary compression index is approximately 0.7-5.0% of primary compression index with an average of 2.0%. In the end, the proposed prediction equations using power regression technique were provided that can provide more accurate predictions than those from existing equations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=compression%20index" title="compression index">compression index</a>, <a href="https://publications.waset.org/abstracts/search?q=clay" title=" clay"> clay</a>, <a href="https://publications.waset.org/abstracts/search?q=settlement" title=" settlement"> settlement</a>, <a href="https://publications.waset.org/abstracts/search?q=consolidation" title=" consolidation"> consolidation</a>, <a href="https://publications.waset.org/abstracts/search?q=secondary%20compression%20index" title=" secondary compression index"> secondary compression index</a>, <a href="https://publications.waset.org/abstracts/search?q=soil%20parameter" title=" soil parameter"> soil parameter</a> </p> <a href="https://publications.waset.org/abstracts/111582/compression-index-estimation-by-water-content-and-liquid-limit-and-void-ratio-using-statistics-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/111582.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">162</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">896</span> In-Situ Quasistatic Compression and Microstructural Characterization of Aluminium Foams of Different Cell Topology</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20A.%20Islam">M. A. Islam</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20J.%20Hazell"> P. J. Hazell</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20P.%20Escobedo"> J. P. Escobedo</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Saadatfar"> M. Saadatfar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Quasistatic compression and micro structural characterization of closed cell aluminium foams of different pore size and cell distributions has been carried out. Metallic foams have good potential for lightweight structures for impact and blast mitigation and therefore it is important to find out the optimized foam structure (i.e. cell size, shape, relative density, and distribution) to maximize energy absorption. In this paper, we present results for two different aluminium metal foams of density 0.5 g/cc and 0.7 g/cc respectively that have been tested in quasi-static compression. The influence of cell geometry and cell topology on quasistatic compression behavior has been investigated using computed tomography (micro-CT) analysis. The compression behavior and micro structural characterization will be presented. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=metal%20foams" title="metal foams">metal foams</a>, <a href="https://publications.waset.org/abstracts/search?q=micro-CT" title=" micro-CT"> micro-CT</a>, <a href="https://publications.waset.org/abstracts/search?q=cell%20topology" title=" cell topology"> cell topology</a>, <a href="https://publications.waset.org/abstracts/search?q=quasistatic%20compression" title=" quasistatic compression"> quasistatic compression</a> </p> <a href="https://publications.waset.org/abstracts/11025/in-situ-quasistatic-compression-and-microstructural-characterization-of-aluminium-foams-of-different-cell-topology" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11025.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">455</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">895</span> Meteosat Second Generation Image Compression Based on the Radon Transform and Linear Predictive Coding: Comparison and Performance </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Cherifi%20Mehdi">Cherifi Mehdi</a>, <a href="https://publications.waset.org/abstracts/search?q=Lahdir%20Mourad"> Lahdir Mourad</a>, <a href="https://publications.waset.org/abstracts/search?q=Ameur%20Soltane"> Ameur Soltane</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Image compression is used to reduce the number of bits required to represent an image. The Meteosat Second Generation satellite (MSG) allows the acquisition of 12 image files every 15 minutes. Which results a large databases sizes. The transform selected in the images compression should contribute to reduce the data representing the images. The Radon transform retrieves the Radon points that represent the sum of the pixels in a given angle for each direction. Linear predictive coding (LPC) with filtering provides a good decorrelation of Radon points using a Predictor constitute by the Symmetric Nearest Neighbor filter (SNN) coefficients, which result losses during decompression. Finally, Run Length Coding (RLC) gives us a high and fixed compression ratio regardless of the input image. In this paper, a novel image compression method based on the Radon transform and linear predictive coding (LPC) for MSG images is proposed. MSG image compression based on the Radon transform and the LPC provides a good compromise between compression and quality of reconstruction. A comparison of our method with other whose two based on DCT and one on DWT bi-orthogonal filtering is evaluated to show the power of the Radon transform in its resistibility against the quantization noise and to evaluate the performance of our method. Evaluation criteria like PSNR and the compression ratio allows showing the efficiency of our method of compression. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20compression" title="image compression">image compression</a>, <a href="https://publications.waset.org/abstracts/search?q=radon%20transform" title=" radon transform"> radon transform</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20predictive%20coding%20%28LPC%29" title=" linear predictive coding (LPC)"> linear predictive coding (LPC)</a>, <a href="https://publications.waset.org/abstracts/search?q=run%20lengthcoding%20%28RLC%29" title=" run lengthcoding (RLC)"> run lengthcoding (RLC)</a>, <a href="https://publications.waset.org/abstracts/search?q=meteosat%20second%20generation%20%28MSG%29" title=" meteosat second generation (MSG)"> meteosat second generation (MSG)</a> </p> <a href="https://publications.waset.org/abstracts/16434/meteosat-second-generation-image-compression-based-on-the-radon-transform-and-linear-predictive-coding-comparison-and-performance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16434.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">421</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">894</span> Video Compression Using Contourlet Transform</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Delara%20Kazempour">Delara Kazempour</a>, <a href="https://publications.waset.org/abstracts/search?q=Mashallah%20Abasi%20Dezfuli"> Mashallah Abasi Dezfuli</a>, <a href="https://publications.waset.org/abstracts/search?q=Reza%20Javidan"> Reza Javidan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Video compression used for channels with limited bandwidth and storage devices has limited storage capabilities. One of the most popular approaches in video compression is the usage of different transforms. Discrete cosine transform is one of the video compression methods that have some problems such as blocking, noising and high distortion inappropriate effect in compression ratio. wavelet transform is another approach is better than cosine transforms in balancing of compression and quality but the recognizing of curve curvature is so limit. Because of the importance of the compression and problems of the cosine and wavelet transforms, the contourlet transform is most popular in video compression. In the new proposed method, we used contourlet transform in video image compression. Contourlet transform can save details of the image better than the previous transforms because this transform is multi-scale and oriented. This transform can recognize discontinuity such as edges. In this approach we lost data less than previous approaches. Contourlet transform finds discrete space structure. This transform is useful for represented of two dimension smooth images. This transform, produces compressed images with high compression ratio along with texture and edge preservation. Finally, the results show that the majority of the images, the parameters of the mean square error and maximum signal-to-noise ratio of the new method based contourlet transform compared to wavelet transform are improved but in most of the images, the parameters of the mean square error and maximum signal-to-noise ratio in the cosine transform is better than the method based on contourlet transform. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=video%20compression" title="video compression">video compression</a>, <a href="https://publications.waset.org/abstracts/search?q=contourlet%20transform" title=" contourlet transform"> contourlet transform</a>, <a href="https://publications.waset.org/abstracts/search?q=discrete%20cosine%20transform" title=" discrete cosine transform"> discrete cosine transform</a>, <a href="https://publications.waset.org/abstracts/search?q=wavelet%20transform" title=" wavelet transform"> wavelet transform</a> </p> <a href="https://publications.waset.org/abstracts/6930/video-compression-using-contourlet-transform" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6930.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">443</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">893</span> Normalized Compression Distance Based Scene Alteration Analysis of a Video</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lakshay%20Kharbanda">Lakshay Kharbanda</a>, <a href="https://publications.waset.org/abstracts/search?q=Aabhas%20Chauhan"> Aabhas Chauhan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, an application of Normalized Compression Distance (NCD) to detect notable scene alterations occurring in videos is presented. Several research groups have been developing methods to perform image classification using NCD, a computable approximation to Normalized Information Distance (NID) by studying the degree of similarity in images. The timeframes where significant aberrations between the frames of a video have occurred have been identified by obtaining a threshold NCD value, using two compressors: LZMA and BZIP2 and defining scene alterations using Pixel Difference Percentage metrics. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20compression" title="image compression">image compression</a>, <a href="https://publications.waset.org/abstracts/search?q=Kolmogorov%20complexity" title=" Kolmogorov complexity"> Kolmogorov complexity</a>, <a href="https://publications.waset.org/abstracts/search?q=normalized%20compression%20distance" title=" normalized compression distance"> normalized compression distance</a>, <a href="https://publications.waset.org/abstracts/search?q=root%20mean%20square%20error" title=" root mean square error"> root mean square error</a> </p> <a href="https://publications.waset.org/abstracts/54601/normalized-compression-distance-based-scene-alteration-analysis-of-a-video" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54601.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">340</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">892</span> Learning Compression Techniques on Smart Phone</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Farouk%20Lawan%20Gambo">Farouk Lawan Gambo</a>, <a href="https://publications.waset.org/abstracts/search?q=Hamada%20Mohammad"> Hamada Mohammad </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Data compression shrinks files into fewer bits than their original presentation. It has more advantage on the internet because the smaller a file, the faster it can be transferred but learning most of the concepts in data compression are abstract in nature, therefore, making them difficult to digest by some students (engineers in particular). This paper studies the learning preference of engineering students who tend to have strong, active, sensing, visual and sequential learning preferences, the paper also studies the three shift of technology-aided that learning has experienced, which mobile learning has been considered to be the feature of learning that will integrate other form of the education process. Lastly, we propose a design and implementation of mobile learning application using software engineering methodology that will enhance the traditional teaching and learning of data compression techniques. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=data%20compression" title="data compression">data compression</a>, <a href="https://publications.waset.org/abstracts/search?q=learning%20preference" title=" learning preference"> learning preference</a>, <a href="https://publications.waset.org/abstracts/search?q=mobile%20learning" title=" mobile learning"> mobile learning</a>, <a href="https://publications.waset.org/abstracts/search?q=multimedia" title=" multimedia"> multimedia</a> </p> <a href="https://publications.waset.org/abstracts/66086/learning-compression-techniques-on-smart-phone" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/66086.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">447</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">891</span> Advantages of Electrifying Offshore Compression System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Siva%20Sankara%20Arudra">Siva Sankara Arudra</a>, <a href="https://publications.waset.org/abstracts/search?q=Kamaruzaman%20Baharuddin"> Kamaruzaman Baharuddin</a>, <a href="https://publications.waset.org/abstracts/search?q=Ir.%20Ahmed%20Fadzil%20Mustafa%20Kamal"> Ir. Ahmed Fadzil Mustafa Kamal</a>, <a href="https://publications.waset.org/abstracts/search?q=Ir.%20Abdul%20Latif%20Mohamed"> Ir. Abdul Latif Mohamed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The advancement of electrical and electronics technologies has rewarded the oil and gas industry with great opportunities to embed more environmentally solutions into design. Most offshore oil and gas producers have their engineering and production asset goals to promote greater use of environmentally friendly compression system technologies to eliminate hazardous emissions from conventional gas compressor drivers. Therefore, this paper comprehensively elaborates the parametric study conducted in integrating the latest electrical and electronics drives technology into the existing compression system. This study was conducted in aspects of layout, reliability & availability, maintainability, emission, and cost. An existing offshore facility that utilized gas turbines as the driver for gas compression was set as Conventional Case for this study. The Electrification Case will utilize electric motor drives as the driver for the compression system. Findings from this study indicate more advantages in driver electrification compared to conventional compression systems. The findings of this paper can be set as a benchmark for future offshore driver selection for gas compression systems of similar operating parameters and power range. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=turbomachinery" title="turbomachinery">turbomachinery</a>, <a href="https://publications.waset.org/abstracts/search?q=electrification" title=" electrification"> electrification</a>, <a href="https://publications.waset.org/abstracts/search?q=emission" title=" emission"> emission</a>, <a href="https://publications.waset.org/abstracts/search?q=compression%20system" title=" compression system"> compression system</a> </p> <a href="https://publications.waset.org/abstracts/146076/advantages-of-electrifying-offshore-compression-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/146076.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">150</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">890</span> Application of the Bionic Wavelet Transform and Psycho-Acoustic Model for Speech Compression </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chafik%20Barnoussi">Chafik Barnoussi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mourad%20Talbi"> Mourad Talbi</a>, <a href="https://publications.waset.org/abstracts/search?q=Adnane%20Cherif"> Adnane Cherif</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper we propose a new speech compression system based on the application of the Bionic Wavelet Transform (BWT) combined with the psychoacoustic model. This compression system is a modified version of the compression system using a MDCT (Modified Discrete Cosine Transform) filter banks of 32 filters each and the psychoacoustic model. This modification consists in replacing the banks of the MDCT filter banks by the bionic wavelet coefficients which are obtained from the application of the BWT to the speech signal to be compressed. These two methods are evaluated and compared with each other by computing bits before and bits after compression. They are tested on different speech signals and the obtained simulation results show that the proposed technique outperforms the second technique and this in term of compressed file size. In term of SNR, PSNR and NRMSE, the outputs speech signals of the proposed compression system are with acceptable quality. In term of PESQ and speech signal intelligibility, the proposed speech compression technique permits to obtain reconstructed speech signals with good quality. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=speech%20compression" title="speech compression">speech compression</a>, <a href="https://publications.waset.org/abstracts/search?q=bionic%20wavelet%20transform" title=" bionic wavelet transform"> bionic wavelet transform</a>, <a href="https://publications.waset.org/abstracts/search?q=filterbanks" title=" filterbanks"> filterbanks</a>, <a href="https://publications.waset.org/abstracts/search?q=psychoacoustic%20model" title=" psychoacoustic model"> psychoacoustic model</a> </p> <a href="https://publications.waset.org/abstracts/1921/application-of-the-bionic-wavelet-transform-and-psycho-acoustic-model-for-speech-compression" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/1921.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">384</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">889</span> A New Prediction Model for Soil Compression Index </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=D.%20Mohammadzadeh%20S.">D. Mohammadzadeh S.</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20Bolouri%20Bazaz"> J. Bolouri Bazaz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a new prediction model for compression index of fine-grained soils using multi-gene genetic programming (MGGP) technique. The proposed model relates the soil compression index to its liquid limit, plastic limit and void ratio. Several laboratory test results for fine-grained were used to develop the models. Various criteria were considered to check the validity of the model. The parametric and sensitivity analyses were performed and discussed. The MGGP method was found to be very effective for predicting the soil compression index. A comparative study was further performed to prove the superiority of the MGGP model to the existing soft computing and traditional empirical equations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=new%20prediction%20model" title="new prediction model">new prediction model</a>, <a href="https://publications.waset.org/abstracts/search?q=compression%20index%20soil" title=" compression index soil"> compression index soil</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-gene%20genetic%20programming" title=" multi-gene genetic programming"> multi-gene genetic programming</a>, <a href="https://publications.waset.org/abstracts/search?q=MGGP" title=" MGGP"> MGGP</a> </p> <a href="https://publications.waset.org/abstracts/35247/a-new-prediction-model-for-soil-compression-index" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35247.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">374</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">888</span> Comprehensive Study of X-Ray Emission by APF Plasma Focus Device</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Habibi">M. Habibi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The time-resolved studies of soft and hard X-ray were carried out over a wide range of argon pressures by employing an array of eight filtered photo PIN diodes and a scintillation detector, simultaneously. In 50% of the discharges, the soft X-ray is seen to be emitted in short multiple pulses corresponding to different compression, whereas it is a single pulse for hard X-rays corresponding to only the first strong compression. It should be stated that multiple compressions dominantly occur at low pressures and high pressures are mostly in the single compression regime. In 43% of the discharges, at all pressures except for optimum pressure, the first period is characterized by two or more sharp peaks.The X鈥搑ay signal intensity during the second and subsequent compressions is much smaller than the first compression. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=plasma%20focus%20device" title="plasma focus device">plasma focus device</a>, <a href="https://publications.waset.org/abstracts/search?q=SXR" title=" SXR"> SXR</a>, <a href="https://publications.waset.org/abstracts/search?q=HXR" title=" HXR"> HXR</a>, <a href="https://publications.waset.org/abstracts/search?q=Pin-diode" title=" Pin-diode"> Pin-diode</a>, <a href="https://publications.waset.org/abstracts/search?q=argon%20plasma" title=" argon plasma"> argon plasma</a> </p> <a href="https://publications.waset.org/abstracts/26796/comprehensive-study-of-x-ray-emission-by-apf-plasma-focus-device" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/26796.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">408</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">887</span> Response of Concrete Panels Subjected to Compression-Tension State of Stresses</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20F.%20Almograbi">Mohammed F. Almograbi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> For reinforced concrete panels the risk of failure due to compression -tension state of stresses, results from pure shear or torsion, can be a major problem. The present calculation methods for such stresses from multiple influences are without taking into account the softening of cracked concrete remains conservative. The non-linear finite element method has become an important and increasingly used tool for the analysis and assessment of the structures by including cracking softening and tension-stiffening. The aim of this paper is to test a computer program refined recently and to simulate the compression response of cracked concrete element and to compare with the available experimental results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=reinforced%20concrete%20panels" title="reinforced concrete panels">reinforced concrete panels</a>, <a href="https://publications.waset.org/abstracts/search?q=compression-tension" title=" compression-tension"> compression-tension</a>, <a href="https://publications.waset.org/abstracts/search?q=shear" title=" shear"> shear</a>, <a href="https://publications.waset.org/abstracts/search?q=torsion" title=" torsion"> torsion</a>, <a href="https://publications.waset.org/abstracts/search?q=compression%20softening" title=" compression softening"> compression softening</a>, <a href="https://publications.waset.org/abstracts/search?q=tension%20stiffening" title=" tension stiffening"> tension stiffening</a>, <a href="https://publications.waset.org/abstracts/search?q=non-linear%20finite%20element%20analysis" title=" non-linear finite element analysis"> non-linear finite element analysis</a> </p> <a href="https://publications.waset.org/abstracts/5311/response-of-concrete-panels-subjected-to-compression-tension-state-of-stresses" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5311.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">337</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=lossless%20compression&amp;page=2">2</a></li> <li class="page-item"><a class="page-link" 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