An analytical solution of the London equation for the weakly coupled grain model of high Tc superconducting thin films has been obtained in the case of finite thickness by taking full account of anisotropic conductivities. Using the solution, we provide general expressions for the transmission-line parameters of high Tc superconducting transmission lines. Dependences of the inductance and resistance on the grain size, coupling strength and film thickness have been numerically evaluated and discussed.

Inductive Logic Programming (ILP) is a study of machine learning systems that use clausal theories in first-order logic as a representation language. In this paper, we survey theoretical foundations of ILP from the viewpoints of Logic of Discovery and Machine Learning, and try to unify these two views with the support of the modern theory of Logic Programming. Firstly, we define several hypothesis construction methods in ILP and give their proof-theoretic foundations by treating them as a procedure which complets incomplete proofs. Next, we discuss the design of individual learning algorithms using these hypothesis construction methods. We review known results on learning logic programs in computational learning theory, and show that these algorithms are instances of a generic learning strategy with proof completion methods.

We report on the fabrication and operation of all-NbN single flux quantum (SFQ) circuits with resistively shunted NbN/AlN/NbN tunnel junctions fabricated on silicon substrates. The critical current varied by about 5% in 400 NbN/AlN/NbN junction arrays, where the junction area was 88 µm2. Critical current densities of the NbN/AlN/NbN tunnel junctions showed exponential dependence on the deposition time of the AlN barrier. By using the 12-nm-thick Cu film as shunted resistors, non-hysteretic current-voltage characteristics were achieved. From dc-SQUID measurements, the sheet inductance of our NbN stripline was estimated to be around 1.2 pH at 4.2 K. We designed and fabricated circuits consisting of dc/SFQ converters, Josephson transmission lines, and T flip-flop-based SFQ/dc converters. The circuits demonstrated correct operation with a bias margin of more than 15% at 4.2 K.

A novel electrical gating circuit is proposed for ultrafast applications in electronics. The circuit employs a two-conductor coupled line, and does not have any active devices such as transistors or diodes. Hence, the ultimate speed of the circuit is limited only by the cutoff frequency of the lines employed. The authors describe the circuit theory and discuss the results of experiments that involved ultrafast measurement using electro-optic sampling techniques. The latter suggests the potential of the circuit to achieve the gatings of at least 80-Gbit/s.

In this paper, we describe our superconducting digital technology that uses Nb/AlOx/Nb Josephson junctions. Superconducting devices have intrinsically superior characteristics than those of semiconductor devices, and Nb/AlOx/Nb junctions have ideal current-voltage characteristics for digital applications. Superconducting devices that use Nb/AlOx/Nb junctions have being actively developed because of their high speed and low power characteristics. Presently, we can fabricate more than twenty thousand junctions on one chip. Using niobium technology, a superconducting 4-kbit RAM has been already successfully developed. We have demonstrated the operation of a network system with a superconducting network chip. Some problems, such as difficulty in high-speed testing, disturbance from trapped magnetic flux and so on, have been overcome by techniques such as a clock-driven testing method, moat structures and so on. The developed technologies, such as the fabrication technology, the design technology for moat structures and so on, must become the basic keys for the development of digital applications based on a single flux quantum device, which will be a promising component for ultra-high speed systems in the twenty-first century.

A hierarchical structure of the statistical models involving the parametric, state space, generalized state space, and self-organizing state space models is explained. It is shown that by considering higher level modeling, it is possible to develop models quite freely and then to extract essential information from data which has been difficult to obtain due to the use of restricted models. It is also shown that by rising the level of the model, the model selection procedure which has been realized with human expertise can be performed automatically and thus the automatic processing of huge time series data becomes realistic. In other words, the hierarchical statistical modeling facilitates both automatic processing of massive time series data and a new method for knowledge discovery.

This paper describes the design principles, the specification, and evaluations of a new 128-bit block cipher E2, which was proposed to the AES (Advanced Encryption Standard) candidates. This algorithm supports 128-bit, 192-bit, and 256-bit secret keys. The design philosophy of E2 is highly conservative; the structure uses 12-round Feistel as its main function whose round function is constructed with 2-round SPN structure, and initial/final transformational functions. E2 has practical security against differential attack, linear attack, cryptanalysis with impossible differential, truncated differential attack, and so on. Furthermore, E2 can be implemented efficiently and flexibly on various platforms because the primitive operations involve byte length processing.

In this paper, we present an access scheme for packet-typed wireless networks, called DQRUMA/PAR (Distributed-Queueing Request Update Multiple Access with Periodically Automatic Reservation), which can transmit multimedia traffic efficiently. Here, we deal with three kinds of traffic i. e. voice, data and still picture. DQRUMA/PAR introduces the transmission scheme that mobile stations for voice communications reserve the transmission capacity periodically during their talkspurts. The transmission control process of DQRUMA/PAR will become easier than the one of DQRUMA, and the delay characteristic of voice is improved. Furthermore, we study two enforced protocols on DQRUMA/PAR. One is the more enforced protocol for voice communications. We call this as Voice Enforced mode (VE mode) on DQRUMA/PAR. The other is the more enforced protocol for data communications. We call this as Data Enforced mode (DE mode) on DQRUMA/PAR. The transmission delay of voice will become reduced significantly by introducing VE mode. On the other hand, the transmission delay characteristic of data will be improved by introducing DE mode. We carry out the performance comparisons of pure DQRUMA/PAR with PRMA and DQRUMA and show the considerable improvement of the protocol numerically. Next we make the performance comparisons between pure DQRUMA/PAR and two enforced modes on DQRUMA/PAR and show the considerable improvements of these enforced protocols, respectively.

This paper presents a simple and generic conversion from a public-key encryption scheme that is indistinguishable against chosen-plaintext attacks into a public-key encryption scheme that is indistinguishable against adaptive chosen-ciphertext attacks in the random oracle model. The scheme obtained by the conversion is as efficient as the original encryption scheme and the security reduction is very tight in the exact security manner.

In this study, we propose a branch-point scheme for multicast ABR service in ATM networks. The performance of the proposed scheme is obtained to show that the consolidation noise and delay can be reduced more effectively than those of the existing schemes.

The arrangement graph An,k is not only a generalization of star graph (n-k=1), but also more flexible. Designing efficient broadcasting algorithm on a regular interconnection network is a fundamental issue for the parallel processing techniques. Two contributions are proposed in this paper. Initially, we elucidate a first result to construct n-k edge-disjoint spanning trees in an An,k. Second, we present efficient (one/all)-to-all broadcasting algorithms by using constructed n-k spanning trees, where height of each spanning tree is 2k-1. The arrangement graph is assumed to use one-port and all-port communication models and packet-switching (or store-and-forward) technique. Using n-k spanning trees allows us to present efficient broadcasting algorithm in the arrangement graphs and outperforms previous results. This is justified by our performance analysis.

A method for locating underground pipes from a pulse radar image is presented. The method employs the Laplacian of Gaussian filter to extract edges and employs the Hough transform to determine the depth of the pipes. A preliminary experiment showed its ability to detect deeply buried pipes with weak signal echoes.

This paper addresses output regulation for nonlinear systems driven by a time varying parameter. The derivative information of the time varying parameter is necessary for the improved regulation performance but it is not readily available in general. In this paper, we propose a velocity estimation of the time varying parameter for use in the control law without amplifying noise signals.

Interpolation attack was presented by Jakobsen and Knudsen at FSE'97. Interpolation attack is effective against ciphers that have a certain algebraic structure like the PURE cipher which is a prototype cipher, but it is difficult to apply the attack to real-world ciphers. This difficulty is due to the difficulty of deriving a low degree polynomial relation between ciphertexts and plaintexts. In other words, it is difficult to evaluate the security against interpolation attack. This paper generalizes the interpolation attack. The generalization makes easier to evaluate the security against interpolation attack. We call the generalized interpolation attack linear sum attack. We present an algorithm that evaluates the security of byte-oriented ciphers against linear sum attack. Moreover, we show the relationship between linear sum attack and higher order differential attack. In addition, we show the security of CRYPTON, E2, and RIJNDAEL against linear sum attack using the algorithm.

The MOV and FR algorithms, which are representative attacks on elliptic curve cryptosystems, reduce the elliptic curve discrete logarithm problem (ECDLP) to the discrete logarithm problem in a finite field. This paper studies these algorithms and introduces the following three results. First, we show an explicit condition under which the MOV algorithm can be applied to non-supersingular elliptic curves. Next, by comparing the effectiveness of the MOV algorithm to that of the FR algorithm, it is explicitly shown that the condition needed for the MOV algorithm to be subexponential is the same as that for the FR algorithm except for elliptic curves of trace two. Finally, a new explicit reduction algorithm is proposed for the ECDLP over elliptic curves of trace two. This algorithm differs from a simple realization of the FR algorithm. Furthermore, we show, by experimental results, that the running time of the proposed algorithm is shorter than that of the original FR algorithm.

Super-anomalous elliptic curves over a ring Z/nZ ;(n=Πi=1k piei) are defined by extending anomalous elliptic curves over a prime filed Fp. They have n points over a ring Z/nZ and pi points over Fpi for all pi. We generalize Satoh-Araki-Smart algorithm and Ruck algorithm, which solve a discrete logarithm problem over anomalous elliptic curves. We prove that a "discrete logarithm problem over super-anomalous elliptic curves" can be solved in deterministic polynomial time without knowing prime factors of n.

A data-parallel processing approach is promising for real-time volume rendering because of the massive parallelism in volume rendering. In data-parallel volume rendering, local results processing elements(PEs) generate from allocated subvolumes are integrated to form a final image. Generally, the integration causes an overhead unavoidable in data-parallel volume rendering due to communications among PEs. This paper proposes a data-parallel shear-warp volume rendering algorithm combined with an adaptive volume subdivision method to reduce the communication overhead and improve processing efficiency. We implement the parallel algorithm on a message-passing multiprocessor system for performance evaluation. The experimental results show that the adaptive volume subdivision method can reduce the overhead and achieve higher efficiency compared with a conventional slab subdivision method.

This paper describes the application of an unsupervised parallel approach called the Annealed Hopfield Neural Network (AHNN) using a modified cost function with moment and entropy preservation for magnetic resonance image (MRI) classification. In the AHNN, the neural network architecture is same as the original 2-D Hopfield net. And a new cooling schedule is embedded in order to make the modified energy function to converge to an equilibrium state. The idea is to formulate a clustering problem where the criterion for the optimum classification is chosen as the minimization of the Euclidean distance between training vectors and cluster-center vectors. In this article, the intensity of a pixel in an original image, the first moment combined with its neighbors, and their gray-level entropy are used to construct a 3-component training vector to map a neuron into a two-dimensional annealed Hopfield net. Although the simulated annealing method can yield the global minimum, it is very time-consuming with asymptotic iterations. In addition, to resolve the optimal problem using Hopfield or simulated annealing neural networks, the weighting factors to combine the penalty terms must be determined. The quality of final result is very sensitive to these weighting factors, and feasible values for them are difficult to find. Using the AHNN for magnetic resonance image classification, the need of finding weighting factors in the energy function can be eliminated and the rate of convergence is much faster than that of simulated annealing. The experimental results show that better and more valid solutions can be obtained using the AHNN than the previous approach in classification of the computer generated images. Promising solutions of MRI segmentation can be obtained using the proposed method. In addition, the convergence rates with different cooling schedules in the test phantom will be discussed.

We propose a coherent automatic gain control (AGC) scheme with low complexity for high-speed satellite communications. A mathematical model for the gain detector and a stochastic difference equation are established to investigate the characteristics of the scheme. Based on the random process theory with the equation, we analyze the acquisition and tracking performance of the AGC loop. It has been verified that the results by the analytical method agree with the simulation results obtained in the presence of small amount of phase offsets in the carrier recovery circuits for the QPSK system. Though the analytical results deviate from the simulation results slightly in the presence of maximum phase offset, they give us the insight in analyzing the characteristics of the proposed scheme.

Optical time- and wavelength-domain paths in future very-high-speed optical communications networks are discussed taking into account trends in current optical transmission and optical signal processing technologies. It is important to investigate optical STM cross-connect systems for time-domain paths in the earlier research phase to ensure the deployment of optical cross-connect technology. The configuration of an optical cross-connect system and the issues that need to be investigated are presented. We also report, for the first time, a preliminary experiment of an optical STM cross-connect system, using 20 Gbit/s optical signals.