The formation of single monolayer of liquid crystalline molecules, 4-n-pentyl-4-cyanobiphenyl (5CB), deposited by the evaporation method in the air, was confirmed with the surface potential measurement. The surface potential increased with the time of evaporation, and the 3- or 4-minute evaporation at a source temperature of 110 gave the saturated potential, indicating the formation of single monolayer. Single monolayer formation was also supported by the comparison of the UV-visible absorption for evaporated film with LB monolayer. Positive potentials were built at the surface, indicating that CN group faces the substrate.

Synchronous Gaussian code-division multiple access (CDMA) systems employing group-orthogonal signature waveforms are proposed and analyzed. All users in the system are divided into groups of users. The signature waveforms are constructed such that all the signature waveforms in one group are orthogonal to all the signature waveforms used in all other groups. This construction of signature waveforms ensures that there is no inter-group interference (i.e., among users in different groups), but at the expense of having intra-group interference (i.e., among users in the same group). However, by choosing a small size for each group, the intra-group interference can be effectively handled by a low-complexity, optimal (or suboptimal) multiuser detector. It is shown that a significant improvement in the system capacity can be achieved by the proposed technique over the conventional one that uses signature waveforms constructed from Welch-bound-equality (WBE) sequences. In particular, it is demonstrated that, while the conventional system's error performance is very sensitive to even small amount of overload, the proposed system with an appropriate design of signature waveforms can achieve a much higher overload (up to 300% as shown in the paper) with an excellent error performance.

In this paper, a fragment-processing solution in 3D graphics rendering algorithms based on fragment lists (i.e. A-buffer) for minimizing loss of image quality is described. While all fragment information should be preserved for exact hidden surface removal, this places additional strain on hardware in terms of silicon gates and clock cycles. Therefore, we propose a fragment processing technique that can effectively merge fragments in order to decrease the depth of fragment lists. It renders scenes quite accurately even in the case when three fragments intersect each other. This algorithm improves hardware acceleration without deteriorating image quality.

In this paper, we describe a technique for optimizing the algebraic method that is applied to higher order differential attack. The higher order differential attack is a well-known attack on block ciphers, in which we derive an attack equation to determine a round key from a property of a higher order differential of a target block cipher. The algebraic method is a linearization of the attack equation and determines the true key by a method such as Gaussian elimination. Our technique is based on linear dependency and can reduce the complexity of that method. We also describe a technique that allows the algebraic method to be used as an attack equation that holds probabilistically. We demonstrate this method by attacking a five-round MISTY1 and show that it needs 221.6 chosen plaintexts and 228.0 encryption times. The computer simulation took about two minutes to complete.

Color histograms have been considered to be effective for color image indexing and retrieval. However, the histogram only represents the global statistical color information. We propose a new method: A Spatial Weighted Color Histogram (SWCH), for image retrieval. The color space of a color image is partitioned into several color subsets according to hue, saturation and value in HSV color space. Then, the spatial center moment of each subset is calculated as the weight of the corresponding subset. Experiments show that our method is more effective in indexing color image and insensitive to intensity variations.

We propose using SQP (Sequential Quadratic Programming) to directly recover 3D quadratic surface parameters from multiple views. A surface equation is used as a constraint. In addition to the sum of squared reprojection errors defined in the traditional bundle adjustment, a Lagrangian term is added to force recovered points to satisfy the constraint. The minimization is realized by SQP. Our algorithm has three advantages. First, given corresponding features in multiple views, the SQP implementation can directly recover the quadratic surface parameters optimally instead of a collection of isolated 3D points coordinates. Second, the specified constraints are strictly satisfied and the camera parameters and 3D coordinates of points can be determined more accurately than that by unconstrained methods. Third, the recovered quadratic surface model can be represented by a much smaller number of parameters instead of point clouds and triangular patches. Experiments with both synthetic and real images show the power of this approach.

Multiple antenna systems are promising architectures for overcoming the effects of multi-path interference and increasing the spectrum efficiency. In order to be able to investigate these systems, in this article, we derive generalized spatial correlation equations of a circular antenna array for two typical angular energy distributions: a Gaussian angle distribution and uniform angular distribution. The generalized spatial correlation equations are investigated carefully by exact and approximate analyses.

The fuzzy set framework can be utilized in several different approaches to modeling the diagnostic process. In this paper, we introduce two main relations between symptoms and diseases where the relations are described by intuitionistic fuzzy set data. Also, we suggest four measures for medical diagnosis. We are dealing with the preliminary diagnosis from the information of interview chart. We quantify the qualitative information based on the interview chart by dual scaling. Prototype of fuzzy diagnostic sets and the linear regression methods are established with these quantified data. These methods can be used to classify new patient's tone of diseases with certain degrees of belief and its concerned symptoms.

We present a differential fixpoint computation method for program analyses based on abstract interpretation. An analysis of a program based on abstract interpretation can be expressed using a monotonic increasing function and a fixpoint of the function becomes an analysis result. To compute a fixpoint, the function is applied repeatedly until the results become stable. This brings redundant computation because new results always include the former results. Differential methods try to avoid such redundancy by computing only the increment of each function application. Compared with other differential fixpoint evaluation methods, our method can deal with non-distributive functions which often occur in practical program analyses. To compute increments for non-distributive functions, we adapt an indirect way of using a differential evaluation rule for expressions which form function bodies. We have designed a differential worklist algorithm and applied the algorithm to implement an alias and constant propagation analysis. Experiments show that our method can avoid much redundant computation.

This paper proposes a fast multi-cycle path detection method for large sequential circuits. The proposed method is based on ATPG techniques, especially on implication techniques, to use circuit structures and multi-cycle path conditions directly. The method also checks whether or not a multi-cycle path may be invalidated by static hazards at the inputs of flip-flops. Then we explain how to apply the proposed algorithm to real industrial designs. Experimental results show that our method is much faster than conventional ones and that it is efficient enough to handle large industrial designs.

In this paper, the absorbing property of the discrete Green's function ABC, which was based on a powerful concept of the TLM method, has been improved by relocating loss process from the time domain to the space domain. The proposed scheme simply adds a loss matrix to the connection matrix in the basic TLM algorithm to make the formulation of the ABC more efficient. Various lengths of absorbing layers discretized for a WR-90 empty waveguide have been tested in terms of reflection property. An expression for an optimum absorbing property has been also derived with respect to the length of the layer. Comparison of the layer with the discrete Green's function ABC shows that the layer in this study has improved reflection property better than approximately 3 and 6 dB, respectively, when 50Δ and 60Δ absorbing layers have been adopted for the WR-90 waveguide. Finally, the layer has been applied to a WR-75 metal insert filter as an example.

Hyperthermia is one of the modalities for cancer treatment, utilizing the difference of thermal sensitivity between tumor and normal tissue. In this treatment, the tumor or target cancer cell is heated up to the therapeutic temperature between 42 and 45 without overheating the surrounding normal tissues. Particularly, the authors have been studying the coaxial-slot antenna for interstitial microwave hyperthermia. At that time, we analyzed the heating characteristics of the coaxial-slot antenna under the assumption that the human body is a homogeneous medium. In this paper, we analyzed the heating characteristics of the coaxial-slot antenna inside an actual neck tumor by using numerical calculations. The models of calculations consist of MRI tomograms of an actual patient. As a result of the calculations, we observed almost uniform temperature distributions inside the human body including the actual neck tumor, which are similar to the results obtained for a homogeneous medium.

A test generation method with time-expansion model can achieve high fault efficiency for acyclic sequential circuits, which can be obtained by partial scan design. This method, however, requires combinational test pattern generation algorithm that can deal with multiple stuck-at faults, even if the target faults are single stuck-at faults. In this paper, we propose a test generation method for acyclic sequential circuits with a circuit model, called MS-model, which can express multiple stuck-at faults in time-expansion model as single stuck-at faults. Our procedure can generate test sequences for acyclic sequential circuits with just combinational test pattern generation algorithm for single stuck-at faults. Experimental results show that test sequences for acyclic sequential circuits with high fault efficiency are generated in small computational effort.

Aging is progressing in our country. Cerebral disease poses a serious problem. Viewing this problem objectively, we can say that support of aging and cerebral disease patients is a useful research theme. To the present, we have done rank evaluation of cerebral disease using synthetic face picture images. This study assesses cognitive ability and expression control ability for intoxication, which is known to impair thinking, cognition, and memory ability. We also examine correspondence of intoxication to cerebral disease. Measurement of cognitive ability corresponds to observation of an internal condition; the measurement of expression control ability corresponds to observation of an external condition. In measurement of cognitive ability, we simulated early stage symptoms of vascular dementia in the second stage of BAC. Also, decreased cognitive ability occurs from the first stage of BAC on face recognition to figure and language. Moreover, face test results show significant difference between decrease in the first stage of BAC and one in the second stage of BAC. These results indicate the possibility of rank evaluation and early stage detection of vascular dementia using a face picture image. From measurement of expression control ability, we obtained the result that we can judge whether a subject has reached second stage of BAC by observing an expression's strength of smile. The second stage of BAC shows symptoms similar to those of vascular dementia. We found the possibility that smile is valid as one externally-observable index for detection of cerebral disease.

Reinforcement Learning (RL) is an efficient learning method for solving problems that learning agents have no knowledge about the environment a priori. Ant Colony System (ACS) provides an indirect communication method among cooperating agents, which is an efficient method for solving combinatorial optimization problems. Based on the cooperating method of the indirect communication in ACS and the update policy of reinforcement values in RL, this paper proposes the Q-ACS multiagent cooperating learning method that can be applied to both Markov Decision Processes (MDPs) and combinatorial optimization problems. The advantage of the Q-ACS method is for the learning agents to share episodes beneficial to the exploitation of the accumulated knowledge and utilize the learned reinforcement values efficiently. Further, taking the visited times into account, this paper proposes the T-ACS multiagent learning method. The merit of the T-ACS method is that the learning agents share better policies beneficial to the exploration during agent's learning processes. Meanwhile, considering the Q-ACS and the T-ACS as homogeneous multiagent learning methods, in the light of indirect media communication among heterogeneous multiagent, this paper presents a heterogeneous multiagent RL method, the D-ACS that composites the learning policy of the Q-ACS and the T-ACS, and takes different updating policies of reinforcement values. The agents in our methods are given a simply cooperating way exchanging information in the form of reinforcement values updated in the common model of all agents. Owning the advantages of exploring the unknown environment actively and exploiting learned knowledge effectively, the proposed methods are able to solve both problems with MDPs and combinatorial optimization problems effectively. The results of experiments on hunter game and traveling salesman problem demonstrate that our methods perform competitively with representative methods on each domain respectively.

A two stage non-scan design for testability method is proposed. The first stage selects test points based on an earlier testability measure conflict. A new design for testability algorithm is proposed to select test points by a fault-oriented testability measure conflict+ in the second stage. Test points are selected in the second stage based on the hard faults after the initial ATPG run of the design for testability circuit in the preliminary stage. The new testability measure conflict+ based on conflict analysis of hard-faults in the process of test generation is introduced, which emulates most general features of sequential ATPG. The new testability measure reduces testability of a fault to the minimum D or controllability of the primary outputs, and therefore, does not need observability measure any more. Effective approximate schemes are adopted to get reasonable estimation of the testability measure. A couple of effective techniques are also adopted to accelerate the process of the proposed design for testability algorithm. Experimental results show that the proposed method gets even better results than two of the recent non-scan design for testability methods nscan and lcdft.

Some new differential input ideal differentiator and integrator function circuits using the current feedback amplifier (CFA) device are presented. The time constant (τo) is tunable by the control voltage (Vc) of a multiplier element connected appropriately around the feedback loop. The CFA device port errors () have insignificant effects on (τo). Test results based on hardware implementation and macromodel simulation are included; the proposed circuits exhibited good high frequency response with low phase errors (θe 2) upto about 450 kHz.

The adaptive cross-spectral (ACS) technique recently introduced by Okuno et al. provides an attractive solution to acoustic echo cancellation (AEC) as it does not require double-talk (DT) detection. In this paper, we first introduce a generalized ACS (GACS) technique where a step-size parameter is used to control the magnitude of the incremental correction applied to the coefficient vector of the adaptive filter. Based on the study of the effects of the step-size on the GACS convergence behaviour, a new variable step-size ACS (VSS-ACS) algorithm is proposed, where the value of the step-size is commanded dynamically by a special finite state machine. Furthermore, the proposed algorithm has a new adaptation scheme to improve the initial convergence rate when the network connection is created. Experimental results show that the new VSS-ACS algorithm outperforms the original ACS in terms of a higher acoustic echo attenuation during DT periods and faster convergence rate.

In this paper, we consider the problem of bearing estimation for spatially distributed sources in unknown spatially-correlated noise. Assumed that the noise covariance matrix is centro-Hermitian, a differential denoising scheme is developed. Combined it with the classic DSPE algorithm, a differential denoising estimator is formulated. Its modified version is also derived. Exactly, the differential processing is first imposed on the covariance matrix of array outputs. The resulting differential signal subspace (DSS) is then utilized to weight array outputs. The noise components orthogonal to DSS are eliminated. Based on eigenvalue decomposition of the covariance matrix of weighted array outputs, the DSPE null spectrum is constructed. The asymptotic performance of the proposed bearing estimator is evaluated in a closed form. Moreover, in order to improve the performance of bearing estimation in case of low signal-to-noise ratio, a modified differential denoising estimator is proposed. Simulation results show the effectiveness of the proposed estimators under the low SNR case. The impacts of angular spread and number of sensors are also investigated.

The objective of this study was to explore suitable spatial filters for inverse estimation of cortical potentials from the scalp electroencephalogram. The effect of incorporating noise covariance into inverse procedures was examined by computer simulations. The parametric projection filter, which allows inverse estimation with the presence of information on the noise covariance, was applied to an inhomogeneous three-concentric-sphere model under various noise conditions in order to estimate the cortical potentials from the scalp potentials. The present simulation results suggest that incorporation of information on the noise covariance allows better estimation of cortical potentials, than inverse solutions without knowledge about the noise covariance, when the correlation between the signal and noise is low. The method for determining the optimum regularization parameter, which can be applied for parametric inverse techniques, is also discussed.