This paper reports studies conducted on image processing with morphological methods. Morphological methods are based on mathematical morphology. These methods can analyze the spatial structure and shape of objects in a target image. We focused on the effectiveness of morphological methods for image processing on embedded processors. Several studies on this topic have been conducted and reported in -. The max-plus algebra-based morphological wavelet transform (MMT) is suitable for parallel processing on simple low-power embedded processors . The adaptive multidirectional max-plus algebra-based morphological wavelet transform (AM-MMT) captures directional features of objects in an image for data compression . MMT watermarking is a data-embedding algorithm for highly parallel processing . The morphological pattern spectrum used for detecting image manipulation extracts information on target objects in an image and detects several image manipulations -. Research on these topics opens up potential for various applications of morphological methods. We plan to continue research on morphological-method-based image-processing algorithms for embedded processors.
In this study, we propose a Peer-to-Peer (P2P) Video-on-Demand (VoD) streaming method which adjusts the receiving rate of pieces by considering the playback deadline of the pieces to reduce interrupted playback. P2P VoD streaming methods based on BitTorrent, such as BitTorrent Streaming (BiToS) and BiToS + Immediacy and Scarcity (BIS), have been proposed to support streaming. In the piece selection strategies of these two methods, a peer probabilistically selects a piece considering immediacy and/or scarcity (i.e., rarity) and receives the selected piece to reduce interrupted playback. However, the piece selection mechanisms still cause interrupted playback owing to probabilistic piece selection. In our proposed P2P VoD streaming method, a peer sequentially selects a piece, starting from the first piece and receives the selected piece at a transfer rate in time for predicted playback start time. As a result, the interrupted playback can be reduced further. In evaluation simulations, we show that the proposed streaming method outperforms previous streaming methods in terms of media playback continuity.
End-to-end available bandwidth estimation is very important for real-time services such as voice over internet protocol, videoconferencing and peer-to-peer streaming. Several available bandwidth estimation methods such as Pathload, IGI/PTR, pathChirp, Yaz and ASSOLO have been proposed. However, these methods have drawbacks in terms of accuracy of available bandwidth estimation and/or network load performance. In this paper, we present an available bandwidth estimation method comprised of two functions for providing high accurate estimation and low network load performance. One function is the available bandwidth estimation function that directly calculates the available bandwidth using the end-to-end delay increase rate. The other function is the rate adjustment algorithm that adjusts the error between the actual available bandwidth and the available bandwidth calculated using the available bandwidth estimation function. The rate adjustment algorithm of the proposed method is based on that of Pathload because Pathload provides high accuracy in estimating available bandwidth. Finally, we compare the proposed method with Pathload in terms of estimation accuracy and network load performance using computer simulation and demonstrate the effectiveness of the proposed method.
Wireless sensor networks (WSN) consist of a large number of sensor nodes to collect various data such as temperature, humidity, speed, acceleration, and so on. In these networks, sensor nodes are usually driven by battery energy and distributed over extensive and large areas. Thus, running out of battery energy is a serious problem. For this reason, it is important to extend the lifetime of WSN. To extend the lifetime, the method of low-energy adaptive clustering hierarchy (LEACH) has been proposed. In LEACH, a cluster head (CH) is chosen without considering the residual energy of each node. Energy-harvesting technology in WSN has also been proposed. However, energy harvesting has some problems. Equipping energy-harvesting devices increases the system cost. Also, the amount of generated energy is unstable in real situations. To solve these problems, this paper proposes LEACH with partial energy harvesting (LPEH), extended LEACH with energy harvesting (ELEH), and ELEH with a sleep operation. In LPEH, the number of energy-harvesting nodes is limited to avoid increasing cost. In ELEH, a CH is chosen from the energy-harvesting nodes to extend the lifetime effectively. In ELEH with the sleep operation, each node becomes an active mode or sleep mode after consideration of the amount of remaining battery energy. In these methods, the coverage area is not considered. Thus, this paper proposes ELEH with the sleep operation considering node positions (ESNP) and ELEH with the sleep operation considering surrounding area condition (ESSA). In ESNP and ESSA, each node enters the sleep mode depending on the distance from adjacent nodes and the surrounding sensing condition, respectively, to reduce the overlapped sensing area. Thus, the unrequested data collected by other nodes becomes low and the energy consumption is reduced. As a result, the coverage area remains large in the long term.
To apply circuit theory to quantum theory, we review the problems of circuit theory described in the past sessions. In concrete, the physical properties of circuits, such as losslessness, steady-state response, and reactive power, are reexamined. It is shown that the Laplace transform is more advantageous than Heaviside's operational calculus and that active power can be conserved when a lossless circuit is used. It is also demonstrated that a forward wave exp(-jβx) travels clockwise because exp(jωt) in the Laplace transform is required for separating the variables of partial differential equations related to waves.