Transflective IPS‐LCD with improved reflective contrast ratio

Abstract— In order to improve the reflective contrast ratio of transflective IPS‐LCDs, a novel pixel design for a normally white reflective IPS has been proposed. In this design, the large‐inter‐electrode‐spacing layout using a novel driving method and a double‐layered electrode have effectively reduced the light leakage. By applying these two technologies, a transflective IPS‐LCD has been successfully demonstrated with a high contrast ratio (15:1) in the reflective mode and a wide‐viewing‐angle characteristic in the transmissive mode.     

A low wall-loading DEMO reactor design with high priority for early and reliable realization of a tokamak fusion reactor over the cost performance

Based on scientific databases adopted for designing ITER plasmas and on the advancement of fusion nuclear technology from the recent R&D program, a low wall-loading DEMO fusion reactor has been designed, where high priority has been given to the early and reliable realization of a tokamak fusion plasma over the cost performance. Since the major radius of this DEMO reactor is chosen to be 10 m, plasma ignition is achievable with a low fusion power of 0.8 GW and an operation period of 4–5 hours is available only with inductive current drive. The low ignition power makes it possible to adopt a first wall with an austenitic stainless steel, for which significant databases and operating experience exists, due to its use in the presence of neutron irradiation in fission reactors. In step with development of advanced materials, a step-wise increase of the fusion power seems to be feasible and realistic, because this DEMO reactor has the potential to produce a fusion power of 5 GW.     

Self-identification algorithm for zeolite-based thermal capacity gas sensor

Microsystem Technologies - We demonstrate a new operation mode of thermal gas sensor based on thermal capacity extraction with identification algorithm. The system is a silicon microstructure...     

Production of IL-6 by T cells from the femoral head of patients with rapidly destructive coxopathy (RDC)

We developed a method to improve the quantitative precision of FDG-PET scans in cancer patients. The total-lesion evaluation method generates a correlation coefficient (r) constrained Patlak parametric image of the lesion together with three calculated glucose metabolic indices: (a) the total-lesion metabolic index ("KT-tle", ml/min/lesion); (b) the total-lesion voxel index ("VT-tle", voxels/lesion); and (c) the global average metabolic index ("KV-tle", ml/min/voxel). METHODS: The glucose metabolic indices obtained from conventional region of interest (ROI) and multiplane evaluation were used as standards to evaluate the accuracy of the total-lesion evaluation method. Computer simulations and four patients with metastatic melanoma before and after chemotherapy were studied. RESULTS: Computer simulations showed that the total-lesion evaluation method has improved precision (% s.d. < 0.6%) and accuracy (approximately 10% error) compared with the conventional ROI method (% s.d. approximately 5%; approximately 25% error). The KT-tle and VT-tle indices from human FDG-PET studies using the total-lesion evaluation method showed excellent correlations with the corresponding values obtained from the conventional ROI methods and multiplane evaluation (r approximately 1.0) and CT lesion volume measurements. CONCLUSION: This method is a simple but reliable way to quantitatively monitor tumor FDG uptake. The method has several advantages over the conventional ROI method: (a) less sensitive to the ROI definition, (b) no need for image registration of serial scan data and (c) includes tumor volume changes in the global tumor metabolism.     

Identification of a golf swing robot using soft computing approach

Golf swing robots have been recently developed in an attempt to simulate the ultra high-speed swing motions of golfers. Accurate identification of a golf swing robot is an important and challenging research topic, which has been regarded as a fundamental basis in the motion analysis and control of the robots. But there have been few studies conducted on the golf swing robot identification, and comparative analyses using different kinds of soft computing methodologies have not been found in the literature. This paper investigates the identification of a golf swing robot based on four kinds of soft computing methods, including feedforward neural networks (FFNN), dynamic recurrent neural networks (DRNN), fuzzy neural networks (FNN) and dynamic recurrent fuzzy neural networks (DRFNN). The performance comparison is evaluated based on three sets of swing trajectory data with different boundary conditions. The sensitivity of the results to the changes in system structure and learning rate is also investigated. The results suggest that both FNN and DRFNN can be used as a soft computing method to identify a golf robot more accurately than FFNN and DRNN, which can be used in the motion control of the robot.     

Brave induction: a logical framework for learning from incomplete information

This paper introduces a novel logical framework for concept-learning called brave induction. Brave induction uses brave inference for induction and is useful for learning from incomplete information. Brave induction is weaker than explanatory induction which is normally used in inductive logic programming, and is stronger than learning from satisfiability, a general setting of concept-learning in clausal logic. We first investigate formal properties of brave induction, then develop an algorithm for computing hypotheses in full clausal theories. Next we extend the framework to induction in nonmonotonic logic programs. We analyze computational complexity of decision problems for induction on propositional theories. Further, we provide examples of problem solving by brave induction in systems biology, requirement engineering, and multiagent negotiation.     

Effect of cold rolling on the superconducting and electronic properties of two amorphous alloys; Nb50Zr35Si15 and Nb70Zr15Si15

The effect of cold rolling on the superconducting properties was examined for amorphous Nb₅₀Zr₃₅Si₁₅ and Nb₇₀Zr₁₅Si₁₅ superconductors. Cold rolling to 10 to 20% reduction in thickness results in a rise of superconducting transition temperature (T _c) and a decrease in transition width (T _c), upper critical field gradient near , critical current density [J _c(H)] and normal electrical resistivity (_n). Changes of about 7% forT _c 33% for T _c, 12% for and 70% forJ _c(H) are found. The rise ofT _c upon cold rolling was considered to originate from the increase in the electron-phonon coupling constant () due to an increase in the electronic density of states at the Fermi level [N(E _f)] and a decrease in the phonon frequency (), while the decreases in T_c,J _c(H) and _n were attributed to the decrease in fluxoid pinning force due to an increase in homogeneity in the amorphous structure. From the results described above, the following two conclusions were derived: (a) cold rolling causes changes in electronic and phonon-states in the quenched amorphous phase, and (b) deformation upon cold rolling occurs not only in the coarse deformation bands observable by optical microscopy, but also on a much finer scale comparable to the coherence length (7.7 nm).     

Superconductivity of Zr-Nb-Si amorphous alloys

Superconducting amorphous alloys with high strength and good ductility have been found in rapidly quenched alloys of the Zr-Nb-Si system. These alloys were produced in a continuous ribbon form of 1 to 2 mm width and 0.02 to 0.03 mm thickness using a modified single roller quenching apparatus. The amorphous alloys were formed over the whole composition range between zirconium and niobium, but the silicon content was limited to the relatively narrow range between about 12 and 24 at%. All the amorphous alloys showed a superconducting transition whose temperature, T _c, increased from 2.31 to 4.20 K with increasing niobium content or with decreasing silicon content. The upper critical magnetic field, H _c2, and the critical current density, J _c, for Zr₁₅Nb₇₀Si₁₅ alloy were of the order of 4.5 Tesla(T) and 5.5×10⁶ A m^–2 at 1.5 K in the absence of applied field. The upper critical field gradient at T _c, , and the electrical resistivity at 4.2 K, _n, decreased from 2.89 to 2.10 T K^–1 and from 2.70 to 1.80m, respectively, with the amount of niobium. The Debye temperature, _D, the electron-phonon coupling constant, , and the bare density of electronic states at the Fermi level, N(E _f ) were calculated from the experimentally measured values of _n, , Young's modulus and density by using the strong-coupling theories. From the comparison of T _c with their calculated parameters, it was found that is the most dominant parameter for T _c. The GL parameter, , and the GL coherence length, _GL(0), were estimated to be 70 to 100 and about 7.6 nm, respectively, from the experimental values of and _n by using the GLAG theory and hence it is concluded that the present amorphous alloys are an extremely dirty type-II superconductor having a very weak flux pinning force.     

A high‐performance sorting algorithm for multicore single‐instruction multiple‐data processors

Many sorting algorithms have been studied in the past, but there are only a few algorithms that can effectively exploit both single‐instruction multiple‐data (SIMD) instructions and thread‐level parallelism. In this paper, we propose a new high‐performance sorting algorithm, called aligned‐access sort (AA‐sort), that exploits both the SIMD instructions and thread‐level parallelism available on today's multicore processors. Our algorithm consists of two phases, an in‐core sorting phase and an out‐of‐core merging phase. The in‐core sorting phase uses our new sorting algorithm that extends combsort to exploit SIMD instructions. The out‐of‐core algorithm is based on mergesort with our novel vectorized merging algorithm. Both phases can take advantage of SIMD instructions. The key to high performance is eliminating unaligned memory accesses that would reduce the effectiveness of SIMD instructions in both phases. We implemented and evaluated the AA‐sort on PowerPC 970MP and Cell Broadband Engine platforms. In summary, a sequential version of the AA‐sort using SIMD instructions outperformed IBM's optimized sequential sorting library by 1.8 times and bitonic mergesort using SIMD instructions by 3.3 times on PowerPC 970MP when sorting 32 million random 32‐bit integers. Also, a parallel version of AA‐sort demonstrated better scalability with increasing numbers of cores than a parallel version of bitonic mergesort on both platforms. Copyright © 2011 John Wiley & Sons, Ltd.     

Thermomechanical behavior of Ti-Ni shape memory alloy films deposited by DC magnetron sputtering

In this study, thermomechanical properties of titanium-nickel (Ti-Ni) shape memory alloy (SMA) films are investigated in order to derive constitutive relations. Ti-Ni SMA films, deposited by DC magnetron sputtering under controlled film composition, are characterized by uniaxial tensile tests. At room temperature (R.T.), Ti-Ni films having Ti contents less than 50 at% exhibit superelastic behavior, and those having Ti contents greater than 50 at% exhibit shape memory behavior. However, the Ni—53.2 at% Ti film fractured at a tensile strain of 0.8% because of an increase in brittleness with increasing Ti content. At elevated temperatures, Ti-Ni films having Ti contents of 50.2 to 52.6 at% undergo phase change from martensite to austenite. The Young's modulus of the Ti-Ni films depends on temperature at each phase, regardless of film composition. Film composition does, however, affect the measured material constants b_A, b_M, c_A, and c_M. Stress-strain curves calculated from the constructed constitutive equation closely agree with those obtained from tensile tests, for both the martensite and austenite phases. The constitutive equations are expected to find great utility in the design of Ti-Ni film-actuated microelectromechanical systems (MEMS).