This letter presents integrating algorithms for affine constraints defined on a manifold. We first explain definition and geometric representation of affine constraints. Next, we derive integrating algorithms to calculate independent first integrals of affine constraints for the two cases where the they are completely integrable and partially nonintegrable. Moreover, we prove the existence of inverse functions in the algorithms. Some examples are also shown to verify our results.

This letter presents an analytical study of the reverse link Erlang capacity of 3G/Ad Hoc Integrated networks. In the considered integrated network, 3G networks and Ad Hoc networks operate over the same frequency band and hence cause interference to each other. The reverse link Erlang capacity is analyzed and discussed in two cases: Ad Hoc networks use and do not use power control.

Context-aware applications are a key aspect of pervasive computing. The core issue of context-aware application development is how to make the application behave suitably according to the changing context without coupling such context dependencies in the program. Several programming paradigms and languages have been proposed to facilitate the development, but they are either lack of sufficient flexibility or somewhat complex for programming and deploying. A reference programming model is proposed in this paper to make up inadequacy of those approaches. In the model, virtual tables constructed by system and maintained by space manager connect knowledge of both developer and space manager while separating dependency between context and application logic from base program. Hierarchy and architecture of the model are presented, and implementation suggestions are also discussed. Validation and evaluation show that the programming model is lightweight and easy to be implemented and deployed. Moreover, the model brings better flexibility for developing context-aware applications.

In this letter, we generalize the binary sequence introduced by Li et al. in [S. Q. Li et al., On the randomness generalized cyclotomic sequences of order two and length pq, IEICE Trans. Fund, vol. E90-A, no.9, pp.2037-2041, 2007] to sequence over arbitrary prime fields. Furthermore, the auto-correlation distribution and linear complexity of the proposed sequence are presented.

In this paper, we propose two authenticated key exchange(AKE) protocols and prove their security in the extended Canetti-Krawczyk model. The first protocol, called NAXOS+, is obtained by slightly modifying the NAXOS protocol proposed by LaMacchia, Lauter and Mityagin [15]. We prove its security under the Computational Diffie-Hellman (CDH) assumption by using the trapdoor test introduced in [6]. To the authors' knowledge, this is the first AKE protocol which is secure under the CDH assumption in the eCK model. The second protocol, called NETS, enjoys a simple and tight security reduction compared to existing schemes including HMQV and CMQV without using the Forking Lemma. Since each session of the NETS protocol requires only three exponentiations per party, its efficiency is also comparable to MQV, HMQV and CMQV.

Wireless Sensor Network(WSN) is widely used in Emergency Management System(EMS) to assure high safety. Real-timely transmitting emergency information in dynamically changing environment should be assured in mission critical district. Conventional methods based on static situations and centralized approaches can not satisfy this requirement. In this paper, to assure real-time property, autonomous community construction technology is proposed to set special area called community which includes a special passage composed of several routers for emergency information's transmission and routers around this passage in one hop range. Emergency information's transmission is protected by routers around this passage from interference of other sensing information's transmission in and outside community. Moreover, autonomous community reconstruction technology is proposed to guarantee real-time property at failure conditions. In this technology, community members autonomously cooperate and coordinate with each other to setup a bypass in community for transmitting emergency information if fault happens. Evaluation results indicate effectiveness of proposed technology.

In this letter, we propose a new observer error linearization approach that is called reduced-order dynamic observer error linearization (RDOEL), which is a modified version of dynamic observer error linearization (DOEL). We introduce the concepts and properties of RDOEL, and provide a complete solution to RDOEL with one integrator. Moreover, we show that it is also a complete solution to a simple case of DOEL.

This paper proposes a low-complexity algorithm to calculate log likelihood ratios (LLRs) of coded bits, which is necessary for channel decoding in coded MIMO mobile communications. An approximate LLR needs to find a pair of transmitted signal candidates that can maximize the log likelihood function under a constraint that a coded bit is equal to either one or zero. The proposed algorithm can find such a pair simultaneously, whereas conventional ones find them individually. Specifically, the proposed method searches for such candidates in directions of the noise enhancement using the MMSE detection as a starting point. First, an inverse matrix which the MMSE weight matrix includes is obtained and then the power method derives eigenvectors of the inverse matrix as the directions of the noise enhancement. With some eigenvectors, one-dimensional search and hard decision are performed. From the resultant signals, the transmitted signal candidates to be required are selected on the basis of the log likelihood function. Computer simulations with 44 MIMO-OFDM, 16QAM, and convolutional codes (rate =1/2, 2/3) demonstrate that the proposed algorithm requires only 1.0 dB more Eb/N0 than that of the maximum likelihood detection (MLD) in order to achieve packet error rate of 10-3, while reducing the complexity to about 0.2% of that of MLD.

This paper presents an unsupervised learning-based method for selection of feature points and object category classification without previous setting of the number of categories. Our method consists of the following procedures: 1)detection of feature points and description of features using a Scale-Invariant Feature Transform (SIFT), 2)selection of target feature points using One Class-Support Vector Machines (OC-SVMs), 3)generation of visual words of all SIFT descriptors and histograms in each image of selected feature points using Self-Organizing Maps (SOMs), 4)formation of labels using Adaptive Resonance Theory-2 (ART-2), and 5)creation and classification of categories on a category map of Counter Propagation Networks (CPNs) for visualizing spatial relations between categories. Classification results of static images using a Caltech-256 object category dataset and dynamic images using time-series images obtained using a robot according to movements respectively demonstrate that our method can visualize spatial relations of categories while maintaining time-series characteristics. Moreover, we emphasize the effectiveness of our method for category classification of appearance changes of objects.

In terrain visualization, the quadtree is the most frequently used data structure for progressive mesh generation. The quadtree provides an efficient level of detail selection and view frustum culling. However, most applications using quadtrees are performed on the CPU, because the pointer and recursive operation in hierarchical data structure cannot be manipulated in a programmable rendering pipeline. We present a quadtree-based terrain rendering method for GPU (Graphics Processing Unit) execution that uses vertex splitting and triangle splitting. Vertex splitting supports a level of detail selection, and triangle splitting is used for crack removal. This method offers higher performance than previous CPU-based quadtree methods, without loss of image quality. We can then use the CPU for other computations while rendering the terrain using only the GPU.

In this paper, we study the decentralized coverage control problem for an environment using a group of autonomous mobile robots with nonholonomic kinematic and dynamic constraints. In comparison with standard coverage control procedures, we develop a combined controller for Voronoi-based coverage approach in which kinematic and dynamic constraints of the actual mobile sensing robots are incorporated into the controller design. Furthermore, a collision avoidance component is added in the kinematic controller in order to guarantee a collision free coverage of the area. The convergence of the network to the optimal sensing configuration is proven with a Lyapunov-type analysis. Numerical simulations are provided approving the effectiveness of the proposed method through several experimental scenarios.

The turn of the century is witnessing radical changes in the way information services are spreading due to the progress of IT and the constantly increase in the number of users of the WWW. Therefore, the business market is changing its strategy for a modern online business environment. Autonomous Decentralized Database System (ADDS), based on autonomous coordinating subsystems, has been proposed as a system architecture in order to meet the innovative e-business requirements for consistency and high response among distributed database systems. Autonomy and decentralization of subsystems help achieving high response time in highly competitive situation and autonomous Mobile Agent based coordination has been proposed to achieve flexibility in a highly dynamic environment. In this paper, it is analyzed the case in which the system size increases; and a multi agent coordination, the same number of mobile agents and sites coexist in the system, is proposed for achieving the timeliness property. The response time in the system is conformed by those transactions that require coordination and those that can be satisfied immediately. In accordance, the distribution of the data in the system for coordination is a medullar issue for the improvement of the response time. A trade-off exits between these two kind of transactions depending on the coordination of the Mobile Agents, the capacity of allocating data among the sites, and as well as the distribution of the data and user requests in the system. In this sense, since the system requires high response time, a data allocation technology in which each mobile agent autonomously determine its own capacity for adjusting data among the sites is proposed. Thus, the system will adapt itself to the dynamic environment. The effectiveness of the proposed architecture and technologies are evaluated by simulation.

Method of moments (MoM) is an efficient design and analysis method for waveguide slot arrays. A rectangular entire-domain basis function is one of the most popular approximations for the slot aperture fields. MoM with only one basis function does not provide sufficient accuracy and the use of higher order mode of basis functions is inevitable to guarantee accuracy. However, including the higher order modes in MoM results in a rapid increase in the computational time as well as the analysis complexity; this is a serious drawback especially in the slot parameter optimization. The authors propose the slot correction length that compensates for the omission of higher order mode of basis functions. This length is constant for a wide range of couplings and frequency bands for various types of slots. The validity and universality of the concept of slot correction length are demonstrated for various slots and slot parameters. Practical slot array design can be drastically simplified by the use of MoM with only one basis function together with the slot correction length. As an example, a linear waveguide array of reflection-cancelling slot pairs is successfully designed.

Behavioral compatibility between subtypes and supertypes in object-oriented systems is a very important issue to enable the substitution between object types since it supports the extension and evolution of an object oriented system. In other words, the subtype must be guaranteed that it can provide all behaviors (operations) of the supertype for replacing the supertype with the subtype. Invocation consistency checking is one of techniques to verify behavioral compatibility between two object types. The technique confirms weather an object type can accept all sequence of operations of the other object type or not. The classical methods rule checks behavioral compatibility by verifying invocation consistency of two object types. The rule argues that subtypes meet behavioral compatibility with supertypes if the subtypes' preconditions of inherited operations are weakened and postconditions are strengthened. Noting that the classical methods rule is not sufficient for checking behavioral compatibility between objects, we propose an extended methods rule on the basis of the classical methods rule. Based on the proposed extended methods rule, we have implemented a tool, BCCT, to automatically check behavioral compatibility between two objects.

One of the most important duties of government is to maintain safety. In 2007, the Ministry of Internal Affairs and Communications of Japan tested 16 different models of a safety support system for children on school routes. One of the models was constructed and tested at a school in an area of the city of Hiroshima from September to December of 2007. A consortium was established by the city of Hiroshima; Hiroshima City University; Chugoku Electric Power Co., Inc.; and KDDI Corporation to conduct this project. For the model project, we developed a new safety support system for children on school routes by using a mobile ad hoc network constructed from mobile phones with the Bluetooth function. About 500 students and 50 volunteers used this system for four months. The support system provided good performance and accuracy in maintaining the safety of students on the way to school [7]. The basic idea of the safety support system is the grouping of children and volunteers using a mobile ad hoc network. In this paper, we present an outline of this system and evaluate the performance of grouping and the effectiveness of our approach.

This letter studies application of the growing PSO to the design of DC-AC inverters. In this application, each particle corresponds to a set of circuit parameters and moves to solve a multi-objective problem of the total harmonic distortion and desired average power. The problem is described by the hybrid fitness consisting of analog objective function, criterion and digital logic. The PSO has growing structure and dynamic acceleration parameters. Performing basic numerical experiments, we have confirmed the algorithm efficiency.

Subspace learning based face recognition methods have attracted considerable interest in recent years, including Principal Component Analysis (PCA), Independent Component Analysis (ICA), Linear Discriminant Analysis (LDA), and some extensions for 2D analysis. However, a disadvantage of all these approaches is that they perform subspace analysis directly on the reshaped vector or matrix of pixel-level intensity, which is usually unstable under illumination or pose variance. In this paper, we propose to represent a face image as a local descriptor tensor, which is a combination of the descriptor of local regions (K*K-pixel patch) in the image, and is more efficient than the popular Bag-Of-Feature (BOF) model for local descriptor combination. Furthermore, we propose to use a multilinear subspace learning algorithm (Supervised Neighborhood Embedding-SNE) for discriminant feature extraction from the local descriptor tensor of face images, which can preserve local sample structure in feature space. We validate our proposed algorithm on Benchmark database Yale and PIE, and experimental results show recognition rate with our method can be greatly improved compared conventional subspace analysis methods especially for small training sample number.

SQUARE is an 8-round SPN structure block cipher and its round function and key schedule have been slightly modified to design building blocks of Rijndael. Key schedule of SQUARE is simple and efficient but fully affine, so we apply a related-key attack on it. We find a 3-round related-key differential trail with probability 2-28, which has zero differences both on its input and output states, which is called local collision in [6]. By extending of this related-key differential, we construct a successful attack on full rounds of SQUARE. In this paper, we present a key recovery attack on full rounds of SQUARE using a related-key boomerang distinguisher. We construct a 7-round related-key boomerang distinguisher with probability 2-119 by finding local collision, and calculate its probability using ladder switch and multiple path estimation techniques. As a result, one round on top of the distinguisher is added to construct an attack on full rounds of SQUARE which recovers 16-bit key information with 2123 encryptions and 2121 data.

Inter-vehicle communication (IVC) system using 700 MHz band to prevent car crashes has been proposed recently. In this paper, we first apply the FDTD method to the analyses of propagation characteristics at an intersection for IVC. We investigate the propagation characteristics considering the electrical conductivities, thickness and windows of building wall and pedestrians. As a result, it is shown that the electrical conductivities and thickness of building wall have a slight influence. In contrast, windows and pedestrians have a great influence on the propagation characteristics. Furthermore, the azimuth delay profiles are obtained by using the MUSIC algorithm.

This letter mainly deals with the multi-rank signal detecting problem against Spherically Invariant Random Vector (SIRV) background with Invariance theory. It is proved that generalized likelihood ratio test (GLRT), Rao test and Wald test are all the Uniformly Most Powerful Invariant (UMPI) detectors in SIRV distributions under a mild technical condition.