We consider an improved control method based on the Stability Transformation Method. Stability Transformation Method detects unknown and unstable periodic orbits of chaotic dynamical systems. Based on the approach to realize the Stability Transformation Method in real systems, we have proposed a control method which can stabilize unknown and unstable periodic orbits embedded in chaotic attractors. However, setting of the control parameters of the control system has remained as unsolved issue. When the dynamics of a target system are unknown, the control parameters have to be set by trial and error. In this paper, we improve the control method with the automatic adjustment function of the control parameters. We show an example of stabilizing unstable periodic orbits of the 3-dimensional hysteresis chaos generator by using the proposed control method. Some results are confirmed by laboratory measurements. The results imply that any unknown and unstable periodic orbits can be stabilized by using the proposed method, if the target chaos system is reduced to 1-dimensional return map.

Aircraft Landing Scheduling (ALS) attempts to determine the landing time for each aircraft. The objective of ALS is to minimise the deviations of the landing time of each aircraft from its target landing time. In this paper, we propose a dynamic hyper-heuristic algorithm for the ALS problem. In our approach, the Scatter Search algorithm is chosen as the high level heuristic to build a chain of intensification and diversification priority rules, which are applied to generate the landing sequence by different priority rules, which are low level heuristics in the hyper-heuristic framework. The landing time for each aircraft can be calculated efficiently based on the landing sequence. Simulation studies demonstrate that the proposed algorithm can obtain high quality solutions for ALS.

This note presents a new approach for the robustness of Hurwitz polynomials under coefficient perturbation. The s-domain Hurwitz polynomial is transformed to the z-domain polynomial by the bilinear transformation. Then an approach based on the Rouché theorem introduced in the literature is applied to compute a crude bound for the allowable coefficient variation such that the perturbed polynomial maintains the Hurwitz stability property. Three methods to obtain improved bounds are also suggested. The results of this note are computationally more efficient than the existing direct s-domain approaches especially for polynomials of higher degree. Furthermore examples indicate that the exact bound for the coefficient variation can be obtained in some cases.

We design a full-order observer for discrete-time linear time-invariant systems with constant output delays. The observer design is based on the output delay model expressed by a two-dimensional state variable, with discrete-time and space independent variables. Employing a discrete-time state transformation, we construct an explicit strict Lyapunov function that enables us to prove the global exponential stability of the full-order observer error system with an explicit estimate of the exponential decay rate. The numerical example demonstrates the design of the full-order observer and illustrates the validity of the exponential stability.

With the distributed data mining technique having been widely used in a variety of fields, the privacy preserving issue of sensitive data has attracted more and more attention in recent years. Our major concern over privacy preserving in distributed data mining is the accuracy of the data mining results while privacy preserving is ensured. Corresponding to the horizontally partitioned data, this paper presents a new hybrid algorithm for privacy preserving distributed data mining. The main idea of the algorithm is to combine the method of random orthogonal matrix transformation with the proposed secure multi-party protocol of matrix product to achieve zero loss of accuracy in most data mining implementations.

This paper describes a novel method for the bi-directional transformation between the power consumption patterns of appliances and human living activities. We have been proposing a demand-side energy management system that aims to cut down the peak power consumption and save the electric energy in a household while keeping user's quality of life based on the plan of electricity use and the dynamic priorities of the appliances. The plan of electricity use could be established in advance by predicting appliance power consumption. Regarding the priority of each appliance, it changes according to user's daily living activities, such as cooking, bathing, or entertainment. To evaluate real-time appliance priorities, real-time living activity estimation is needed. In this paper, we address the problem of the bi-directional transformation between personal living activities and power consumption patterns of appliances. We assume that personal living activities and appliance power consumption patterns are related via the following two elements: personal appliance usage patterns, and the location of people. We first propose a Living Activity - Power Consumption Model as a generative model to represent the relationship between living activities and appliance power consumption patterns, via the two elements. We then propose a method for the bidirectional transformation between living activities and appliance power consumption patterns on the model, including the estimation of personal living activities from measured appliance power consumption patterns, and the generation of appliance power consumption patterns from given living activities. Experiments conducted on real daily life demonstrate that our method can estimate living activities that are almost consistent with the real ones. We also confirm through case study that our method is applicable for simulating appliance power consumption patterns. Our contributions in this paper would be effective in saving electric energy, and may be applied to remotely monitor the daily living of older people.

In this paper, we propose a novel content-aware image resizing method based on grid transformation. Our method focuses on not only keeping important regions unchanged but also keeping the aspect ratio of the main object in an image unchanged. The dual conditions can avoid distortion which often occurs when only using the former condition. Our method first calculates image importance. Next, we extract the main objects on an image by using image importance. Finally, we calculate the optimal grid transformation which suppresses changes in size of important regions and in the aspect ratios of the main objects. Our method uses lower and upper thresholds for transformation to suppress distortion due to extreme shrinking and enlargement. To achieve better resizing results, we introduce a boundary discarding process. This process can assign wider regions to important regions, reducing distortions on important regions. Experimental results demonstrate that our proposed method resizes images with less distortion than other resizing methods.

Histogram sequences represent high-dimensional time-series converted from images by space filling curves (SFCs). To overcome the high-dimensionality nature of histogram sequences (e.g., 106 dimensions for a 1024×1024 image), we often use lower-dimensional transformations, but the tightness of their lower-bounds is highly affected by the types of SFCs. In this paper we attack a challenging problem of evaluating which SFC shows the better performance when we apply the lower-dimensional transformation to histogram sequences. For this, we first present a concept of spatial locality and propose spatial locality preservation metric (SLPM in short). We then evaluate five well-known SFCs from the perspective of SLPM and verify that the evaluation result concurs with the actual transformation performance. Finally, we empirically validate the accuracy of SLPM by providing that the Hilbert-order with the highest SLPM also shows the best performance in k-NN (k-nearest neighbors) search.

A coarse-grained reconfigurable architecture (CGRA) is typically hybrid architecture, which is composed of a reconfigurable processing unit (RPU) and a host microprocessor. Many computation-intensive kernels (e.g., loop nests) are often mapped onto RPUs to speed up the execution of programs. Thus, mapping optimization of loop nests is very important to improve the performance of CGRA. Processing element (PE) utilization rate, communication volume and reconfiguration cost are three crucial factors for the performance of RPUs. Loop transformations can affect these three performance influencing factors greatly, and would be of much significance when mapping loops onto RPUs. In this paper, a joint loop transformation approach for RPUs is proposed, where the PE utilization rate, communication cost and reconfiguration cost are under a joint consideration. Our approach could be integrated into compilers for CGRAs to improve the operating performance. Compared with the communication-minimal approach, experimental results show that our scheme can improve 5.8% and 13.6% of execution time on motion estimation (ME) and partial differential equation (PDE) solvers kernels, respectively. Also, run-time complexity is acceptable for the practical cases.

This paper presents an alternative approach for the analysis of EM field by a rotating body with FDTD method and Overset Grid Generation method, considering Lorentz transformation for the higher velocity cases. This approach has been previously proposed for the case of linear and uniformly moving body against/to the incident wave. Here, the approach is expanded to a rotating body which includes the interpolation technique in the space and time increment along the cylindrical rotation at the fixed axis. First, the grid size ratios between the main mesh and the sub-mesh are studied. The appropriate choice of the grid size ratio is obtained. Then, the modulations of the EM field when the incident wave hits the rotating body in high velocity cases are analyzed. The relationship of the phase shift and the velocity is further observed. The observed EM fields are compared with the theoretical results and achieved good agreements in high relative velocities. The assessment of the numerical errors in a rotating environment is also highlighted. This numerical approach may have numerous situations to which it can be applied. This may be involved with the design of rotating devices such as microactuator, commutator and others.

The globalization of commerce has increased the importance of retrieving and updating complex and distributed information efficiently. Web services currently show that the most promise for building distributed application systems and model-driven architecture is a new approach to developing such applications. The expanding scale and complexity of enterprise information systems (EISs) under distributed computing environments has made sharing and exchanging data particularly challenging. Data services are applications tailored specifically for information oriented tasks to deal with business service requirements, and are heavily dependent on the distributed architecture of consumer data processing. The implementation of a data service can eliminate inconsistency among various application systems in the exchange of data. This paper proposes a data-oriented model-driven developmental framework to deal with these issues, in which a platform independent model (PIM) is divided into a service model, a logic data model, and a service composition model. We also divide a platform specific model (PSM) into a physical data model and a data service model. In this development method, we define five meta-models and outline a set of rules governing the transformation from PIMs into PSMs. A code generator is also included to transform each PSM into the application code. We include a case study to demonstrate the feasibility and merits of the proposed development framework with a case study.

Image warping is usually used to perform real-time geometric transformation of the images captured by the CMOS image sensor of video camera. Several existing look-up table (LUT)-based algorithms achieve real-time performance; however, the size of the LUT is still large, and it has to be stored in off-chip memory. To reduce latency and bandwidth due to the use of off-chip memory, this paper proposes an improved LUT (ILUT) scheme that compresses the LUT to the point that it can be stored in on-chip memory. First, a one-step transformation is adopted instead of using several on-line calculation stages. The memory size of the LUT is then reduced by utilizing the similarity of neighbor coordinates, as well as the symmetric characteristic of video camera images. Moreover, an elaborate pipeline hardware structure, cooperating with a novel 25-point interpolation algorithm, is proposed to accelerate the system and reduce further memory usage. The proposed system is implemented by a field-programmable gate array (FPGA)-based platform. Two different examples show that the proposed ILUT achieves real-time performance with small memory usage and low system requirements.

Recently a simple algorithm was presented by the first author which enables one to successively compute the transformation matrix of various order for the general 1-D to 1-D polynomial transformation. This letter extends the result to the general 1-D to 2-D polynomial transformation. It is also shown that the matrix obtained can be used for the 2-D to 2-D polynomial transformation as well.

Report generation is one of the most important tasks for database and e-commerce applications. Current report tools typically provide a set of predefined components that are used to specify report layout and format. However, available layout options are limited, and WYSIWYG formatting is not allowed. This paper proposes a four-phase report generation process to overcome these problems. The first phase retrieves source tables from the database. The second phase reorganizes the layout of the source tables by transferring the source tables into a set of new flat tables (in the first normal form). The third phase restructures the flat tables into a nested table (report) by specifying the report structure. The last phase formats the report with a WYSIWYG format editor supporting a number of formatting rules designed specifically for nested reports. Each phase of the proposed process supports visual programming, giving an easy-to-use user interface and allowing very flexible report layouts and formats. A visual end-user-programming tool, called TPS, is developed to demonstrate the proposed process and show that reports with sophisticated layouts can be created without writing low-level report generation programs.

In this paper, we present an automatic vision-based traffic sign recognition system, which can detect and classify traffic signs at long distance under different lighting conditions. To realize this purpose, the traffic sign recognition is developed in an originally proposed dual-focal active camera system. In this system, a telephoto camera is equipped as an assistant of a wide angle camera. The telephoto camera can capture a high accuracy image for an object of interest in the view field of the wide angle camera. The image from the telephoto camera provides enough information for recognition when the accuracy of traffic sign is low from the wide angle camera. In the proposed system, the traffic sign detection and classification are processed separately for different images from the wide angle camera and telephoto camera. Besides, in order to detect traffic sign from complex background in different lighting conditions, we propose a type of color transformation which is invariant to light changing. This color transformation is conducted to highlight the pattern of traffic signs by reducing the complexity of background. Based on the color transformation, a multi-resolution detector with cascade mode is trained and used to locate traffic signs at low resolution in the image from the wide angle camera. After detection, the system actively captures a high accuracy image of each detected traffic sign by controlling the direction and exposure time of the telephoto camera based on the information from the wide angle camera. Moreover, in classification, a hierarchical classifier is constructed and used to recognize the detected traffic signs in the high accuracy image from the telephoto camera. Finally, based on the proposed system, a set of experiments in the domain of traffic sign recognition is presented. The experimental results demonstrate that the proposed system can effectively recognize traffic signs at low resolution in different lighting conditions.

In this paper, we consider a stabilization problem for the cart-pendulum system based on discrete mechanics, which is known as a good discretizing method for mechanical systems and has not been really applied to control theory. First, the continuous and discrete cart-pendulum systems are explained. We next propose a transformation method that converts a discrete-time input derived from the discrete-time optimal regulator theory into a continuous-time zero-order hold input, and carry out some simulations on stabilization of the cart-pendulum system by the transformation method. Then, we apply not only our proposed method but also existing methods to an experimental laboratory of the cart-pendulum system and perform some experiments in order to verify the availability of the proposed method.

In this letter, we propose an effective method to retrieve images from a 2D shape image database using discrete shock graphs combined with an adaptive selection algorithm. Experimental results show that our method is more accurate and fast than conventional approaches and reduces computational complexity.

This paper presents an adaptive magnification transformation based particle swarm optimizer (AMT-PSO) that provides an adaptive search strategy for each particle along the search process. Magnification transformation is a simple but very powerful mechanism, which is inspired by using a convex lens to see things much clearer. The essence of this transformation is to set a magnifier around an area we are interested in, so that we could inspect the area of interest more carefully and precisely. An evolutionary factor, which utilizes the information of population distribution in particle swarm, is used as an index to adaptively tune the magnification scale factor for each particle in each dimension. Furthermore, a perturbation-based elitist learning strategy is utilized to help the swarm's best particle to escape the local optimum and explore the potential better space. The AMT-PSO is evaluated on 15 unimodal and multimodal benchmark functions. The effects of the adaptive magnification transformation mechanism and the elitist learning strategy in AMT-PSO are studied. Results show that the adaptive magnification transformation mechanism provides the main contribution to the proposed AMT-PSO in terms of convergence speed and solution accuracy on four categories of benchmark test functions.

We demonstrate a single-channel 1.28 Tbit/s-525 km transmission using OTDM of subpicosecond DQPSK signals. In order to cope with transmission impairments due to time-varying higher-order PMD, which is one of the major limiting factors in such a long-haul ultrahigh-speed transmission, we newly developed an ultrafast time-domain optical Fourier transformation technique in a round-trip configuration. By applying this technique to subpicosecond pulses, transmission impairments were greatly reduced, and BER performance below FEC limit was obtained with increased system margin.

Aperiodic quadriphase Z-complementary sequences, which include the conventional complementary sequences as special cases, are introduced. It is shown that, the aperiodic quadriphase Z-complementary pairs are normally better than binary ones of the same length, in terms of the number of Z-complementary pairs, and the maximum zero correlation zone. New notions of elementary transformations on quadriphase sequences and elementary operations on sets of quadriphase Z-complementary sequences are presented. In particular, new methods for analyzing the relations among the formulas relative to sets of quadriphase Z-complementary sequences and for describing the sets are proposed. The existence problem of Z-complementary pairs of quadriphase sequences with zero correlation zone equal to 2, 3, and 4 is investigated. Constructions of sets of quadriphase Z-complementary sequences and their mates are given.