The recent development of communication devices and wireless network technologies continues to advance the new era of the Internet and telecommunications. The various “things”, which include not only communication devices but also every other physical object on the planet, are also going to be connected to the Internet, and controlled through wireless networks. This concept, which is referred to as the “Internet of Things (IoT)”, has attracted much attention from many researchers in recent years. The concept of IoT can be associated with multiple research areas such as body area networks, Device-to-Device (D2D) communications networks, home area networks, Unmanned Aerial Vehicle (UAV) networks, satellite networks, and so forth. Also, there are various kinds of applications created by using IoT technologies. Thus, the concept of the IoT is expected to be integrated into our society and support our daily life in the near future. In this paper, we introduce different classifications of IoT with examples of utilizing IoT technologies. In addition, as an example of a practical system using IoT, a tsunami detection system (which is composed of a satellite, sensor terminals, and an active monitoring system for real-time simultaneous utilization of the devices) is introduced. Furthermore, the requirements of the next generation systems with the IoT are delineated in the paper.

This paper presents an efficient multi-service allocation scheme for the digital television terrestrial broadcasting systems in which the fixed service is modulated by orthogonal frequency division multiplexing and quadrature amplitude modulation (OFDM/QAM) with larger FFT size and the added mobile service is modulated by OFDM and offset quadrature amplitude modulation (OQAM) with smaller FFT size. The two different types of services share one 8MHz broadcasting channel. The isotropic orthogonal transform algorithm (IOTA) is chosen as the shaping filter for OQAM because of its isotropic convergence in time and frequency domain and the proper FFT size is selected to maximum the transmission capacity under mobile environment. The corresponding transceiver architecture is also proposed and analyzed. Simulations show that the newly added mobile service generates much less out-of-band interference to the fixed service and has a better performance under fast fading wireless channels.

This paper describes the breathing phantom built to test a six-degree-of freedom sensing device designed for use in Respiratory-Gated Radiotherapy (RGRT). It is focussed on the construction of a test bed that was designed to address tumour motion issues while, at the same time, behaving in much the same way as the human tissues when irradiated. The phantom can produce respiratory movement in three dimensions. Shift differences between the motion axes can be introduced. The position error in the worst case scenario is not greater that 0.4 mm. Emphasis is made on the technical limitations of current sensing technologies, especially with regard to acceleration sensitivity. This study demonstrates that the sensitivity of accelerometers used to sense tumour motion should be 0.05 mG or less.

The increase in the advanced location based services such as traffic coordination and management necessitates the need for advanced models tracking the positions of Moving Objects (MOs) like vehicles. Due to computer processing limitations, it is impossible for MOs to continuously update their locations. This results in the uncertainty nature of a MO's location between any two reported positions. Efficiently managing and quantifying the uncertainty regions of MOs are needed in order to support different types of queries and to improve query response time. This challenging problem of modeling uncertainty regions associated with MO was recently addressed by researchers and resulted in models that ranged from linear which require few properties of MOs as input to the models, to non-linear that are able to more accurately represent uncertainty regions by considering higher degree input. This paper summarizes and discusses approaches in modeling uncertainty regions associated with MOs. It further illustrates the need for appropriate approximations especially in the case of non-linear models as the uncertainty regions become rather irregularly shaped and difficult to manage. Finally, we demonstrate through several experimental sets the advantage of non-linear models over linear models when the uncertainty regions of MOs are approximated by two different approximations; the Minimum Bounding Box (MBB) and the Tilted Minimum Bounding Box (TMBB).

In the symbiotic cognitive radio (CR) networks, the CR users (CUs) may assist the primary transmission in a cooperation time, and obtain an incentive time for their own data transmission. In this letter, we study the throughput maximization problem in the symbiotic CR networks. Under the symbiosis and transmit power constraints, we aim to find the optimal cooperation time to assist the primary transmission and power allocations among the CUs. Given the cooperation time, the optimal power allocations can be solved by multi-level water-filling (MWF) with individual volume limits. A theoretical analysis is presented on the cooperation time and a modified bisection algorithm with low complexity is proposed to find the sub-optimal cooperation time. Simulation results show that the spectrum usage efficiency can be significantly improved as the number of CUs increases.

Since a radio frequency identification (RFID) transponder (tag) generates both location and time information when it enters and leaves a reader, the trajectory of a moving, tagged object can be traced. Due to the time intervals between entries to successive readers, during which tags are not tracked, accurate tracing of complete trajectories can be difficult. To overcome this problem, we propose a tag trajectory indexing scheme called TR-tree (R-tree-based tag trajectory index) that can trace tags by combining the local trajectories at each reader. In experiments, this scheme showed superior performance compared with other indices.

In the centralized polling mode in IEEE 802.16e, a base station (BS) polls mobile stations (MSs) for bandwidth reservation in one of three polling modes; unicast, multicast, or broadcast pollings. In unicast polling, the BS polls each individual MS to allow to transmit a bandwidth request packet. This paper presents an analytical model for the unicast polling of bandwidth request in IEEE 802.16e networks over Gilbert-Elliot error channel. We derive the probability distribution for the delay of bandwidth requests due to wireless transmission errors and find the loss probability of request packets due to finite retransmission attempts. By using the delay distribution and the loss probability, we optimize the number of polling slots within a frame and the maximum retransmission number while satisfying QoS on the total loss probability which combines two losses: packet loss due to the excess of maximum retransmission and delay outage loss due to the maximum tolerable delay bound. In addition, we obtain the utilization of polling slots, which is defined as the ratio of the number of polling slots used for the MS's successful transmission to the total number of polling slots used by the MS over a long run time. Analysis results are shown to well match with simulation results. Numerical results give examples of the optimal number of polling slots within a frame and the optimal maximum retransmission number depending on delay bounds, the number of MSs, and the channel conditions.

In this paper, we analyze the robustness for low-density parity-check (LDPC) codes over the Gilbert-Elliott (GE) channel. For this purpose we propose a density evolution method for the case where LDPC decoder uses the mismatched parameters for the GE channel. Using this method, we derive the region of tuples of true parameters and mismatched decoding parameters for the GE channel, where the decoding error probability approaches asymptotically to zero.

Based on the clonal selection principle proposed by Burnet, in the immune response process there is no crossover of genetic material between members of the repertoire, i.e., there is no knowledge communication during different elite pools in the previous clonal selection models. As a result, the search performance of these models is ineffective. To solve this problem, inspired by the concept of the idiotypic network theory, an expanded lateral interactive clonal selection algorithm (LICS) is put forward. In LICS, an antibody is matured not only through the somatic hypermutation and the receptor editing from the B cell, but also through the stimuli from other antibodies. The stimuli is realized by memorizing some common gene segment on the idiotypes, based on which a lateral interactive receptor editing operator is also introduced. Then, LICS is applied to several benchmark instances of the traveling salesman problem. Simulation results show the efficiency and robustness of LICS when compared to other traditional algorithms.

This paper presents a simple abdomen model of pregnant women and the evaluation of the specific absorption rate (SAR) inside the proposed model close to normal mode helical antennas (NHAs), which are replacing the portable radio terminals for business at 150 MHz. First, dielectric properties of amniotic fluid and those of fetus of rabbit, which have about the same electrical properties as human, are measured. As a result, the conductivity of amniotic fluid is 1.8 times and that of fetus is 1.3 times higher than that of adult muscle at 150 MHz. The result also suggests the modeling of pregnant women including the amniotic fluid and the fetus is necessary. Next, a simple abdomen model of pregnant women based on the measurements of magnetic resonance (MR) images of Japanese women in the late period of pregnancy is proposed. Finally, the SAR inside the proposed abdomen model close to 0.11λ and 0.18λ NHAs is calculated using the finite-difference time-domain (FDTD) method. As a result, we have confirmed that the 10-g average SAR in the fetus is sufficiently less than 2 W/kg, when the output power of NHAs is 5 W, which is the maximum power of portable radio terminals in Japan.

This paper considers the problem of recursive filtering for linear discrete-time systems with uncertain observation. A new approximate adaptive filter with a parallel structure is herein proposed. It is based on the optimal mean square combination of arbitrary number of correlated estimates which is also derived. The equation for error covariance characterizing the mean-square accuracy of the new filter is derived. In consequence of parallel structure of the filtering equations the parallel computers can be used for their design. It is shown that this filter is very effective for multisensor systems containing different types of sensors. A practical implementation issue to consider this filter is also addressed. Example demonstrates the accuracy and efficiency of the proposed filter.

A flooding algorithm is an indispensable and fundamental network control mechanism for achieving some tasks, such notifying all nodes of some information, transferring data with high reliability, getting some information from all nodes, or to reserve a route by flooding the messages in the network. In particular, the flooding algorithm is greatly effective in the heterogeneous and dynamic network environment such as so-called ubiquitous networks, whose topology is indefinite or changes dynamically and whose nodal function may be simple and less intelligent. Actually, it is applied to grasp the network topology in a sensor network or an ad-hoc network, or to retrieve content information by mobile agent systems. A flooding algorithm has the advantages of robustness and optimality by parallel processing of messages. However, the flooding mechanism has a fundamental disadvantages: it causes the message congestion in the network, and eventually increases the processing time until the flooding control is finished. In this paper, we propose and evaluate methods for producing a more efficient flooding algorithm by adopting the growth processes of primitive creatures, such as molds or microbes.

This paper describes the design concept and implementation of a software platform for realization of symbiotic robots that interact intelligently with human in symbiosis manner. Such robots require proper combination of various technologies on a common platform that allows them to work co-operatively. "SPAK" has been developed to serve this purpose. It is a Java-based software platform to support knowledge processing and co-ordination of tasks among several software modules and agents representing the robotic hardware connected on a network. SPAK features frame-based knowledge system, a GUI knowledge building tool, forward and backward chaining engines, networking support, and class libraries for building software agent components. Beside the robotic applications, SPAK can be used as a general-purpose frame system as well. An experimental application of SPAK in human-robot interaction is also given.

Spatiotemporal chaos in a multidomain regime in a Gunn-effect device is numerically investigated as an example of collective domain oscillations under global constraints. The dynamics of carrier densities are computed using a set of model partial differential equations. Numerical results reveal some distinctive and chaotic clustering features caused by the global coupling and boundary effects. The chaotic regime is then characterized in terms of a Lyapunov spectrum and Lyapunov dimension, the latter increasing with the size of the system.

We described short time span idiotype immune network reactions by rigorous mathematical equations. For each idiotype, we described the temporal changes in concentration of (1) single bound antibody, one of its two Fab arms has bound to the complemental receptor site on the B cell. (2) double bound antibody, both of its two Fab arms have bound to the complemental receptor sites on the B cell and (3) an immune complex which is a product of reaction among the antibodies. Stimulation and secretion processes of an antibody in the idiotype network were described by non linear differential equations characterized by the magnitude of cross-linking of the complemental antibody and B cell receptor. The affinity between the mutually complemental antibody and receptor was described by an weighted affinity matrix. The activating process was expressed by an exponential function with threshold. The rate constant for the linkage of the second Fab arm of an antibody was induced from the molecular diffusion process that was modified by the Coulomb repulsive force. By using reported experimental data, we integrated 60 non linear differential equations for the idiotype immune network to obtain the temporal behavior of concentrations of the species in hour span. The concentrations of the idiotype antibody and immune complex changed synchronously. The influence of a change in one rate constant extended to all the members of the idiotype network. The concentrations of the single bound antibody, double bound antibody and immune complex oscillated as functions of the concentration of the free antibody particularly at its low concentration. By comparing to the reported experimental data, the present computational approach seems to realize biological immune network reactions.

To estimate moving object velocity in an image sequence is useful for a variety of applications, such as velocity measurement, computer vision and monitoring systems. An effective way is to approach it in the transform/spatiotemporal mixed domain (MixeD), which transforms the 3-D signal processing problem into 1-D complex signal processing. But it remains a problem how to select several spatial frequency points in the MixeD which may influence the accuracy of velocity estimation and object detection. In this paper, a spatial frequency selection method has been proposed, which can choose the appropriate spatial frequency points out of a number of points in MixeD automatically. So the velocity estimation problem can be addressed by solving the coupled equations established over two selected appropriate points in 2-D spatial frequency domain other than searching for the spectral energy plane over a number of points selected by experience. In this method, evaluation functions corresponding to image sequence with one moving object and two moving objects are established firstly, and the selection is then achieved by using the established evaluation functions together with a threshold. The simulation results show that the proposed method is effective on the appropriate spatial frequency selection.

The Paper describes design and experiment of 2nd cyclotron harmonic peniotron at microwave region using a permanent magnet system. The magnet system using a cylindrical magnet magnetized along the cylindrical axis is designed and fabricated. The 2nd cyclotron harmonic peniotron operating at the π mode in a six vane magnetron waveguide resonator and at 5 GHz was constructed by using the magnet system. The peak electronic efficiency higher than 30% was achieved at the π mode in the resonator.

Patterns exist in many contexts and can be considered the useful information for decision making. However, many patterns are not directly visible without careful presentation. Here, we describe an interactive visualization approach for browsing patterns in a history of interacting with a computer system. While a user is carrying out his/her business using computers, activities with respect to time and location are captured to determine the situational interactions. We first integrate the timeline and geographical map to create a structure to visualize spatiotemporal events in the interaction history. The spiral-based interactive visualization technique, presented in this paper, is then used to derive patterns according to the user-specified different spatial viewpoints on the map. In this study, we demonstrate how patterns can be used as visual statements for the analysis of a spatiotemporal data set in the information visualization.

This paper describes an efficient simulation algorithm for the spatiotemporal pattern analysis of the continuous-time neural networks with the multivalued logic (multivalued continuous-time neural networks). The multivalued transfer function of neuron is approximated to the stepwise constant function which is constructed by the sum of the step functions with the different thresholds. By this approximation, the dynamics of the network can be formulated as a stepwise constant linear differential equation at each timestep and the optimal timestep for the numerical integration can be obtained analytically. Finally, it is shown that the proposed method is much faster than a variety of conventional simulators.

Three dimensional model based coding methods are proposed as next generation image coding methods. These new representations need 3D reconstruction techniques. This paper presents a method that extracts the surfaces of static objects that occlude other objects from a spatiotemporal image captured with straight-line camera motion. We propose the concept of occlusion types and show that the occlusion types are restricted to only eight patterns. Furthermore, we show occlusion type pairs contain information that confirms the existence of surfaces. Occlusion information gives strong cues for segmentation and representation. The method can estimate not only the 3D positions of edge points but also the surfaces bounded by the edge points. We show that combinations of occlusion types contain information that can confirm surface existence. The method was tested successfully on real images by reconstructing flat and curved surfaces. Videos can be hierarchically structured with the method. The method makes various applications possible, such as object selective image communication and object selective video editing.