Image matching is an important area of research in the field of artificial intelligence, machine vision and visual navigation. This paper presents a new image matching scheme suitable for visual navigation. In this scheme, gray scale images are sliced and quantized to form sub-band binary images. The information in the binary images is then signaturized to form a vector space and the signatures are sorted as per significance. These sorted signatures are then normalized to transform the represented image pictorial features in a rotation and scale invariant form. For the image matching these two vector spaces from both the images are compared in the transformed domain. This comparison yields efficient results directly in the image spatial domain avoiding the need of image inverse transformation. As compared to the conventional correlation, this comparison avoids the wide range of square error calculations all over the image. In fact, it directly guides the solution to converge towards the estimate given by the adaptive prediction for a high speed performance in an aerial video sequence. A four dimensional solution population scheme has also been presented with a matching confidence factor. This factor helps in terminating the iterations when the essential matching conditions have been achieved. The proposed scheme gives robust and fast results for normal, scaled and rotated templates. Speed comparison with older techniques shows the computational viability of this new technique and its much lesser dependence on image size. The method also shows noise immunity at 30 dB AWGN and impulsive noise.

The authors present R2Power, an effective approach to the realizable reduction of RC networks with independent current sources. The proposed approach is based on the entrywise perturbation theory for diagonally dominant M-matrices. The accuracy of the node voltages of the reduced network, as compared to those of the original network, is maintained on the order of the entrywise perturbation performed during reduction. R2Power can be used to reduce the size of RC networks used to model the power networks of SoCs, for efficient IR-drop analysis. Experiments showed that R2Power reduced the size of industrial examples by more than 95%, with maximum relative node voltage errors of less than 0.012%.

In this paper, a Kalman filter-based method for restoration of video images acquired by an in-vehicle camera in foggy conditions is proposed. In order to realize Kalman filter-based restoration, the proposed method clips local blocks from the target frame by using a sliding window and regards the intensities in each block as elements of the state variable of the Kalman filter. Furthermore, the proposed method designs the following two models for restoration of foggy images. The first one is an observation model, which represents a fog deterioration model. The proposed method automatically determines all parameters of the fog deterioration model from only the foggy images to design the observation model. The second one is a non-linear state transition model, which represents the target frame in the original video image from its previous frame based on motion vectors. By utilizing the observation and state transition models, the correlation between successive frames can be effectively utilized for restoration, and accurate restoration of images obtained in foggy conditions can be achieved. Experimental results show that the proposed method has better performance than that of the traditional method based on the fog deterioration model.

We present a very simple probabilistic, passive attack against the protocols HB and HB+. Our attack presents some interesting features: it requires less captured transcripts of protocol executions when compared to previous results; It makes possible to trade the amount of required transcripts for computational complexity; the value of noise used in the protocols HB and HB+ need not be known.

An elementary formal system, EFS for short, is a kind of logic program over strings, and regarded as a set of rules to generate a language. For an EFS Γ, the language L(Γ) denotes the set of all strings generated by Γ. We consider a new form of EFS, called a restricted two-clause EFS, and denote by rEFS the set of all restricted two-clause EFSs. Then we study the learnability of rEFS in the exact learning model. The class rEFS contains the class of regular patterns, which is extensively studied in Learning Theory. Let Γ* be a target EFS in rEFS of learning. In the exact learning model, an oracle for superset queries answers "yes" for an input EFS Γ in rEFS if L(Γ) is a superset of L(Γ*), and outputs a string in L(Γ*)-L(Γ), otherwise. An oracle for membership queries answers "yes" for an input string w if w is included in L(Γ*), and answers "no", otherwise. We show that any EFS in rEFS is exactly identifiable in polynomial time using membership and superset queries. Moreover, for other types of queries, we show that there exists no polynomial time learning algorithm for rEFS by using the queries. This result indicates the hardness of learning the class rEFS in the exact learning model, in general.

Durability describes the ability of a device to operate properly in imperfect conditions. We have recently proposed a novel neural network structure called an "Affordable Neural Network" (AfNN), in which affordable neurons of the hidden layer are considered as the elements responsible for the robustness property as is observed in human brain function. Whereas earlier we have shown that AfNNs can still generalize and learn, here we show that these networks are robust against damages occurring after the learning process has terminated. The results support the view that AfNNs embody the important feature of durability. In our contribution, we investigate the durability of the AfNN when some of the neurons in the hidden layer are damaged after the learning process.

A new acceleration scheme that decreases the number of required iterations in relaxation methodology is proposed. The proposed scheme uses dynamic error prediction of an improved approximation to the solution during an iterative computation. The proposed scheme's application to circuit simulations required an average of 67.3% fewer iterations compared to un-accelerated relaxation methods.

We present a novel model, named Category Constraint-Latent Dirichlet Allocation (CC-LDA), to learn and recognize natural scene category. Previous work had to resort to additional classifier after obtaining image topic representation. Our model puts the category information in topic inference, so every category is represented in a different topics simplex and topic size, which is consistent with human cognitive habit. The significant feature in our model is that it can do discrimination without combined additional classifier, during the same time of getting topic representation. We investigate the classification performance with variable scene category tasks. The experiments have demonstrated that our learning model can get better performance with less training data.

The heterodyne laser interferometer acts as an ultra-precise measurement apparatus in semiconductor manufacture. However the periodical nonlinearity property caused from frequency cross-talk is an obstacle to improve the high measurement accuracy in nanometer scale. In order to minimize the nonlinearity error of the heterodyne interferometer, we propose a frequency cross-talk compensation algorithm using an artificial intelligence method. The feedforward neural network trained by back-propagation compensates the nonlinearity error and regulates to minimize the difference with the reference signal. With some experimental results, the improved accuracy is proved through comparison with the position value from a capacitive displacement sensor.

This work elucidates the evolution of three generations of the laboratory information system in the National Taiwan University Hospital, which were respectively implemented in an IBM Series/1 minicomputer, a client/server and a plug-and-play HL7 interface engine environment respectively. The experience of using the HL7 healthcare information exchange in the hospital information system, laboratory information system, and automatic medical instruments over the past two decades are illustrated and discussed. The latest design challenge in developing intelligent laboratory information services is to organize effectively distributed and heterogeneous medical instruments through the message gateways. Such experiences had spread to some governmental information systems for different purposes in Taiwan; besides, the healthcare information exchange standard, software reuse mechanism, and application service provider adopted in developing the plug-and-play laboratory information system are also illustrated.

The performance of an analog winner-take-all (WTA) circuit is affected by the corner error and the offset error. Despite the fact that the corner error can be reduced with large transconductance of the transistor, the offset error caused by device mismatch has not been completely studied. This paper presents the complete offset error analysis, and proposes low offset design guidelines and an offset cancellation scheme. The experimental results show good agreement with the theoretical analysis and the drastic improvement of the offset error.

An adaptive zero forcing maximum likelihood soft input soft output (AZFML-SISO) detector for multiple input multiple output (MIMO) wireless systems is presented. Its performance in an iterative MIMO receiver is analyzed. The AZFML-SISO detector calculates the soft outputs, applying the ML approach to the list that contains only those signal vectors limited by a hypersphere around the zero forcing (ZF) solution. The performance of the algorithm is evaluated on a communication system based on the standard for single carrier broadband wireless communication IEEE 802.16, with three transmit and three receive antennas. It is shown by computer simulation that the computational complexity in an average sense of the receiver running the AZFML-SISO algorithm is reduced by 90% at the SNR values of 30 dB and by 50% for SNR values of 15 dB in comparison to the receiver with an ML detector, while the system performance degrades by less than 1 dB.

The body area network (BAN) has attracted attention because of its potential for high-grade wireless communication technology and its safety and high durability. Also, human area transmission of a BAN propagating at an ultra-wide band (UWB) has been demonstrated recently. When considering the efficiency of electromagnetic (EM) propagation inside the human body for BAN and hyperthermia treatment using RF, it is important to determine the mechanism of EM dissipation in the human body. A body heating system for hyperthermia must deposit EM energy deep inside the body. Also, it is important that the EM field generated by the implant system is sufficiently strong. In this study, the specific absorption rate (SAR) distribution is simulated using an EM simulator to consider the biological transmission mechanism and its effects. To utilize the EM field distribution using an implant system for hyperthermia treatment, the SAR distribution inside the human body is simulated. As a result, the SAR distribution is concentrated on the surface of human tissue, the muscle-bolus interface, the pancreas, the stomach, the spleen and the regions around bones. It can also be concentrated in bone marrow and cartilage. From these results, the appropriate location for the implant system is revealed on the basis of the current distribution and differences in the wave impedance of interfacing tissues. The possibility of accurate data transmission and suitable treatment planning is confirmed.

We demonstrated all-optical demultiplexing of 160-Gb/s signal to 40- and 80-Gb/s by a Mach-Zehnder Interferometric all-optical switch, where the picosecond cross-phase modulation (XPM) induced by intersubband excitation in InGaAs/AlAsSb coupled double quantum wells is utilized. A bi-directional pump configuration, i.e., two control pulses are injected from both sides of a waveguide chip simultaneously, increases a nonlinear phase shift twice in comparison with injection of single pump beam with forward- and backward direction. The bi-directional pump configuration is the effective way to avoid damaging waveguide facets in the case where high optical power of control pulse is necessary to be injected for optical gating at repetition rate of 40/80 GHz. Bit error rate (BER) measurements on 40-Gb/s demultiplexed signal show that the power penalty is decreased slightly for the bi-directional pump case in the BER range less than 10-6. The power penalty is 1.3 dB at BER of 10 - 9 for the bi-directional pump case, while it increases by 0.3-0.6 dB for single pump cases. A power penalty is influenced mainly by signal attenuation at "off" state due to the insufficient nonlinear phase shift, upper limit of which is constrained by the current low XPM efficiency of 0.1 rad/pJ and the damage threshold power of 100 mW in a waveguide facet.

This paper presents a scan design for delay fault testability of 2-rail logic circuits. The flip flops used in the scan design are based on master-slave ones. The proposed scan design provides complete fault coverage in delay fault testing of 2-rail logic circuits. In two-pattern testing with the proposed scan design, initial vectors are set using the set-reset operation, and the scan-in operation for initial vectors is not required. Hence, the test application time is reduced to about half that of the enhanced scan design. Because the additional function is only the set-reset operation of the slave latch, the area overhead is small. The evaluation shows that the differences in the area overhead of the proposed scan design from those of the standard scan design and the enhanced scan design are 2.1 and -14.5 percent on average, respectively.

In equational theorem proving, convergent term rewriting systems play a crucial role. In order to compute convergent term rewriting systems, the standard completion procedure (KB) was proposed by Knuth and Bendix and has been improved in various ways. The multi-completion system MKB developed by Kurihara and Kondo accepts as input a set of reduction orders in addition to equations and efficiently simulates parallel processes each of which executes the KB procedure with one of the given orderings. Wehrman and Stump also developed a new variant of completion procedure, constraint-based completion, in which reduction orders need not be given by using automated modern termination checkers. As a result, the constraint-based procedures simulate the execution of parallel KB processes in a sequential way, but naive search algorithms sometimes cause serious inefficiency when the number of the potential reduction orders is large. In this paper, we present a new procedure, called a constraint-based multi-completion procedure MKBcs, by augmenting the constraint-based completion with the framework of the multi-completion for suppressing the combinatorial explosion by sharing inferences among the processes. The existing constraint-based system SLOTHROP, which basically employs the best-first search, is more efficient when its built-in heuristics for process selection are appropriate, but when they are not, our system is more efficient. Therefore, both systems have their role to play.

We consider the problem of secret key agreement in Gaussian Maurer's Model. In Gaussian Maurer's model, legitimate receivers, Alice and Bob, and a wire-tapper, Eve, receive signals randomly generated by a satellite through three independent memoryless Gaussian channels respectively. Then Alice and Bob generate a common secret key from their received signals. In this model, we propose a protocol for generating a common secret key by using the result of soft-decision of Alice and Bob's received signals. Then, we calculate a lower bound on the secret key rate in our proposed protocol. As a result of comparison with the protocol that only uses hard-decision, we found that the higher rate is obtained by using our protocol.

In this paper, the impacts of using multiple transmit antennas under doubly correlated MIMO channels on CDMA uplink code acquisition is studied. The performance of a MIMO code acquisition system is analyzed by considering spatial fading correlations, which depend on antenna spacing and azimuth spread at both MS and BS. The detection performance and mean acquisition time in the presence of spatially correlated MIMO channel are presented on a frequency selective fading channel and compared with the cases of spatial fading decorrelation via numerical evaluation. It is observed that the acquisition performance relies on the degree of spatial fading correlations. In addition, it is surprisingly seen that a MIMO code acquisition system provides worse performance than SIMO.

Software model checking is typically applied to components of large systems. The assumption generation is the problem of finding the least restrictive environment in which the components satisfy a given safety property. There is an algorithm to compute the environment for properties given as a regular language. In this paper, we propose a general scheme for computing the assumption even for non-regular properties, and show the uniqueness of the least restrictive assumption for any class of languages. In general, dealing with non-regular languages may fall into undecidability of problems. We also show a method to compute assumptions based on visibly pushdown automata and their finite-state abstractions.

In this letter, we present an exact analytic expression for the maximum signal-to-interference ratio (SIR) for receivers communicating with multiple transmitting nodes over a general time-varying channel, where one of the nodes is chosen as a desired signal source based on the instantaneous channel condition and the other nodes act as interference sources. As an illustrative example, the maximum SIR distribution of a mobile receiver surrounded by three base stations (BS) is determined in a closed-form formula for Rayleigh fading channels, and its accuracy is confirmed using simulation results.