This aim of this study is to assess the Tigris River sediments and utilize them as a new abrasive for the preparation of polished surface of magnetite ore to be studied under reflected light ore microscope. Such polishing process was tested using 250, 125, 71, 45, 25 and 18μm grain sizes of the river sediments. For the completion of the polishing and to obtain a glossy perfect polished surface, the 7 and 2.5 μm sized standard diamond pastes were used. After each polishing stage, the reflectance and roughness of these surfaces were measured as an evaluation step for the polishing efficiency. The reflectance values (R%) of the magnetite surface were found to be reversely proportioned to the abrasive grain size; while the surface roughnes

In this paper, we present multiple bit error correction coding scheme based on extended Hamming product code combined with type II HARQ using shared resources for on chip interconnect. The shared resources reduce the hardware complexity of the encoder and decoder compared to the existing three stages iterative decoding method for on chip interconnects. The proposed method of decoding achieves 20% and 28% reduction in area and power consumption respectively, with only small increase in decoder delay compared to the existing three stage iterative decoding scheme for multiple bit error correction. The proposed code also achieves excellent improvement in residual flit error rate and up to 58% of total power consumption compared to the other err

Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

    Manufacturing high-efficiency polymeric materials to moderate fast neutrons by converting them into slow or thermal neutrons. These materials absorb thermal neutrons as well as gamma rays associated with neutrons. Materials of small mass number are used to slow down fast neutrons because neutrons have a high cross-section when they interact with these materials. Materials of high mass number absorb gamma rays. Polyurethane and epoxy were mixed in various ratios to create a blend to serve as neutrons shield, lead (Pb) was then added to the blend at weight percentages of 20%, 30%, 40%, 50%, and 70% to produce a polymer composite.

    Polymeric materials reinforced with lead in various ratios were tested to select the best

The performance quality and searching speed of Block Matching (BM) algorithm are affected by shapes and sizes of the search patterns used in the algorithm. In this paper, Kite Cross Hexagonal Search (KCHS) is proposed. This algorithm uses different search patterns (kite, cross, and hexagonal) to search for the best Motion Vector (MV). In first step, KCHS uses cross search pattern. In second step, it uses one of kite search patterns (up, down, left, or right depending on the first step). In subsequent steps, it uses large/small Hexagonal Search (HS) patterns. This new algorithm is compared with several known fast block matching algorithms. Comparisons are based on search points and Peak Signal to Noise Ratio (PSNR). According to resul

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

In the midst of the public narrative film , we discussed the issue of dealing with the current narrative more specialized which its future dimension form shift and twist on the level of construction narrative film in some of its diverse and renewable trends in its two ways theoretical and practical and non-give important implications for the modes of operation of the renewable narrative structures and the fact that the cinema is an arts which always open to ideas in neighboring fields and this come naturally as a result of the continuing intellectual and knowledge sharing between cinema and other science . our current research has already begun to address the issue in a stream of consciousness narrative structure film based on all that t