3 sonuçlar
Arama Sonuçları
Listeleniyor 1 - 3 / 3
Yayın The sectoral sweeper scheme for wireless sensor networks: Adaptive antenna array based sensor node management and location estimation(Kluwer Academic Publishers-Plenum Publishers, 2006-12) Erdoğan, Ayhan; Coşkun, Vedat; Kavak, AdnanWe introduce a novel sensor node management and location estimation method referred as sectoral sweeper (SS) scheme that uses an adaptive antenna array (AAA) at a central node in wireless sensor networks (WSNs). With the SS scheme, the central node can activate or deactivate the nodes in a desired region which is specified by beam direction and beam width of the transmit beam and also by minimum and maximum thresholds (R (min) and R (max)) for the received signal strength indicator (RSSI) of signals received by the nodes. In order to perform a specified task that is associated with a Task_id, two different beams are transmitted, which are task region beam and routing region beam to switch the nodes into active or routing modes. Since our scheme does not require any additional software or hardware for node management and location estimation in sensor nodes, the deficiencies of tiny sensors are effectively eliminated. The proposed scheme is shown to reduce the number of sensing nodes and the amount of data traffic in the network, thus leading to considerable savings in energy consumption and prolonged sensor lifetime.Yayın A novel image compression method based on classified energy and pattern building blocks(Springer International Publishing AG, 2011) Güz, ÜmitIn this paper, a novel image compression method based on generation of the so-called classified energy and pattern blocks (CEPB) is introduced and evaluation results are presented. The CEPB is constructed using the training images and then located at both the transmitter and receiver sides of the communication system. Then the energy and pattern blocks of input images to be reconstructed are determined by the same way in the construction of the CEPB. This process is also associated with a matching procedure to determine the index numbers of the classified energy and pattern blocks in the CEPB which best represents (matches) the energy and pattern blocks of the input images. Encoding parameters are block scaling coefficient and index numbers of energy and pattern blocks determined for each block of the input images. These parameters are sent from the transmitter part to the receiver part and the classified energy and pattern blocks associated with the index numbers are pulled from the CEPB. Then the input image is reconstructed block by block in the receiver part using a mathematical model that is proposed. Evaluation results show that the method provides considerable image compression ratios and image quality even at low bit rates.Yayın Compression of the biomedical images using quadtree-based partitioned universally classified energy and pattern blocks(Springer London, 2019-03-15) Gezer, Murat; Gargari, Sepideh Nahavandi; Güz, Ümit; Gürkan, HakanIn this work, an efficient low bit rate image coding/compression method based on the quadtree-based partitioned universally classified energy and pattern building blocks (QB-UCEPB) is introduced. The proposed method combines low bit rate robustness and variable-sized quantization benefits of the well-known classified energy and pattern blocks (CEPB) method and quadtree-based (QB) partitioning technique, respectively. In the new method, first, the QB-UCEPB is constructed in the form of variable length block size thanks to the quadtree-based partitioning rather than fixed block size partitioning which was employed in the conventional CEPB method. The QB-UCEPB is then placed to the transmitter side as well as receiver side of the communication channel as a universal codebook manner. Every quadtree-based partitioned block of the input image is encoded using three quantities: image block scaling coefficient, the index number of the QB-UCEB and the index number of the QB-UCPB. These quantities are sent from the transmitter part to the receiver part through the communication channel. Then, the quadtree-based partitioned input image blocks are reconstructed in the receiver part using a decoding algorithm, which exploits the mathematical model that is proposed. Experimental results show that using the new method, the computational complexity of the classical CEPB is substantially reduced. Furthermore, higher compression ratios, PSNR and SSIM levels are achieved even at low bit rates compared to the classical CEPB and conventional methods such as SPIHT, EZW and JPEG2000
