Surface Waves on Superfluid <Superscript>4</Superscript>He Under Reduced Gravity

Superfluid ⁴He was produced on a small jet plane for the first time using a small GM-refrigerator to condense the liquid and a scroll pump to get the superfluid by evaporation. The surface wave on superfluid under 0.5g _E, 0.1g _E and 0.05g _E, together with 2g _E and 1g _E, was successfully examined by an optical method utilizing parabolic flight. Here, g _E is the gravitational constant on the ground. Assuming that only the fundamental mode was excited as determined by the sample cell width, the resonance peak in the frequency domain was well reproduced by the gravity wave with corresponding gravity constant.     

Wireless Body Area Network Combined with Satellite Communication for Remote Medical and Healthcare Applications

Wireless Body Area Network (WBAN) is expected to play an important role in supporting medical and healthcare services with increased convenience and comfort. One main advantage of WBAN is that it enables automatic biosignal collection in real time which is essential in medical treatment and healthcare vigilance. To harmonize with the strong demands from both medical and healthcare societies, and information and communications technology industries, IEEE 802 Standard Committee set up a task group of TG15.6 to develop an IEEE wireless standard on WBAN. In this paper, we first review the main activities of TG15.6 with the updated status. Then, we present a prototype WBAN system that is implemented by using ultra-wideband technology. Multi-hop mechanism is adopted to guarantee reliable connection. Finally, we describe an experimental system that uses the developed WBAN system by combining with satellite communication in supporting remote medical treatment and healthcare. In case of less of medical resources such as in emergency, in rural or isolated areas, such a system is important in sending the corresponding biosignal to a remote hospital in real time to help patient management. The relative delay of WBAN data delivery via satellite is measured which is dependent on the satellite link capacity.     

Tunable Spectrum Selectivity for Multiphoton Absorption with Enhanced Visible Light Trapping in ZnO Nanorods

Observation of visible light trapping in zinc oxide (ZnO) nanorods (NRs) correlated to the optical and photoelectrochemical properties is reported. In this study, ZnO NR diameter and c‐axis length respond primarily at two different regions, UV and visible light, respectively. ZnO NR diameter exhibits UV absorption where large ZnO NR diameter area increases light absorption ability leading to high efficient electron–hole pair separation. On the other hand, ZnO NR c‐axis length has a dominant effect in visible light resulting from a multiphoton absorption mechanism due to light reflection and trapping behavior in the free space between adjacent ZnO NRs. Furthermore, oxygen vacancies and defects in ZnO NRs are associated with the broad visible emission band of different energy levels also highlighting the possibility of the multiphoton absorption mechanism. It is demonstrated that the minimum average of ZnO NR c‐axis length must satisfy the linear regression model of Z _p,min = 6.31d to initiate the multiphoton absorption mechanism under visible light. This work indicates the broadening of absorption spectrum from UV to visible light region by incorporating a controllable diameter and c‐axis length on vertically aligned ZnO NRs, which is important in optimizing the design and functionality of electronic devices based on light absorption mechanism.     

Training a reciprocal-sigmoid classifier by feature scaling-space

This paper presents a reciprocal-sigmoid model for pattern classification. This proposed classifier can be considered as a Φ-machine since it preserves the theoretical advantage of linear machines where the weight parameters can be estimated in a single step. The model can also be considered as an approximation to logistic regression under the framework of Generalized Linear Models. While inheriting the necessary classification capability from logistic regression, the problems of local minima and tedious recursive search no longer exist in the proposed formulation. To handle possible over-fitting when using high order models, the classifier is trained using multiple samples of uniformly scaled pattern features. Empirically, the classifier is evaluated using a benchmark synthetic data from random sampling runs for initial statistical evidence regarding its classification accuracy and computational efficiency. Additional experiments based on ten runs of 10-fold cross validations on 40 data sets further support the effectiveness of the reciprocal-sigmoid model, where its classification accuracy is seen to be comparable to several top classifiers in the literature. Main reasons for the good performance are attributed to effective use of reciprocal sigmoid for embedding nonlinearities and effective use of bundled feature sets for smoothing the training error hyper-surface. Editor: Risto Miikkulainen     

A LOOP-BASED APPROACH IN CLUSTERING AND ROUTING IN MOBILE AD HOC NETWORKS

Although clustering is a convenient framework to enable traffic control and service support in Mobile Ad hoc NETworks （MANETs）, it is seldom adopted in practice due to the additional traffic overhead it leads to for the resource limited ad hoc network. In order to address this problem, we proposed a loop-based approach to combine clustering and routing. By employing loop topologies, topology information is disseminated with a loop instead of a single node, which provides better robustness, and the nature of a loop that there are two paths between each pair of nodes within a loop composed of setup procedure, regular procedure and emergent route recovering. suggests smart route recovery strategy. Our approach is recovery procedure to achieve clustering, routing and     

Face recognition with radial basis function (RBF) neural networks

A general and efficient design approach using a radial basis function (RBF) neural classifier to cope with small training sets of high dimension, which is a problem frequently encountered in face recognition, is presented. In order to avoid overfitting and reduce the computational burden, face features are first extracted by the principal component analysis (PCA) method. Then, the resulting features are further processed by the Fisher's linear discriminant (FLD) technique to acquire lower-dimensional discriminant patterns. A novel paradigm is proposed whereby data information is encapsulated in determining the structure and initial parameters of the RBF neural classifier before learning takes place. A hybrid learning algorithm is used to train the RBF neural networks so that the dimension of the search space is drastically reduced in the gradient paradigm. Simulation results conducted on the ORL database show that the system achieves excellent performance both in terms of error rates of classification and learning efficiency.     

The design and optimization of high-performance, double-polyself-aligned p-n-p technology

The device design and performance of double-poly self-aligned p-n-p technology, featuring a low-resistivity p⁺ subcollector, thin p-epi, and boron-doped poly-emitter are described. Device isolation is provided by deep and shallow trenches which reduce the collector-to-substrate capacitance while maintaining a high breakdown voltage (⩾40 V). By utilizing a shallow emitter process in conjunction with an optimized arsenic-base implant, devices with emitter-base junction depths as shallow as 20 nm and base widths of less than 100 nm were obtained. Cutoff frequencies of up to 27 GHz were obtained, and the AC performance was demonstrated by an NTL-gate delay of 36 ps and an active-pull-down (APD) ECL-gate delay of 20 ps. This high-performance p-n-p technology was developed to be compatible with existing double-poly n-p-n technologies. The matching speed of p-n-p devices opens up new opportunities for high-performance complementary bipolar circuits     

Molecular dynamics simulations of HLA-DR4 (DRB1*0405) complexed with analogue peptide: conformational changes in the putative T-cell receptor binding regions

The specific recognition of foreign peptide bound to the major histocompatibility complex (MHC) molecule by T-cell receptor (TCR) leads to T-cell activation. We found that analogue peptides containing single amino acid substitutions at the third amino acid position (p3), p5, p7 and p8 of the index peptide (YWALEAAAD) induced different response patterns of T cell clones specific for the index peptide in the context of the human MHC class II molecule HLA-DR4. Analogue peptides were classified into three types, agonists, antagonists or null peptides (non-agonistic and non-antagonistic peptides). A molecular basis for how these slight changes lead to such different consequences for T cells has not been described. To explore the mechanistic basis of these observations, molecular dynamics simulations at 300 K of 300 ps duration were carried out for the DR4-index peptide, DR4-agonist, and DR4-antagonist complexes. The simulations showed that the DR4-antagonist complexes were distinguished from the DR4-index peptide and DR4-agonist complexes by relatively higher deviations of C(alpha) atoms in proposed TCR-binding regions, suggesting that subtle changes of the exposed framework of the peptide binding groove by the antagonist peptides could induce the TCR antagonistic activities.     

Constant and high switching frequency torque controller for DTC drives

The letter presents a new method of increasing the switching frequency of a direct torque control (DTC) of induction machines. The method simply replaces the hysteresis comparator of the conventional DTC drives with a triangular waveform-based constant switching frequency controller. By synchronizing the digital signal processor (DSP) sampling with a triangular waveform and with an appropriate systematic controller design, a high switching frequency DTC drive is possible without requiring a high-frequency space-vector modulator. The implementation of the controller is simple and operates based on waveform comparisons; in this letter it is implemented using a combination of a DSP and a field programmable gate array device. Simulation and experimental results indicate that the controller both reduces the torque ripple and maintains a constant switching frequency.