Application of virtual reality for peritoneal dialysis exchange learning in patients with end-stage renal disease and cognitive impairment

Virtual Reality - Cognitive impairment is not uncommon in patients with end-stage renal disease and can make it more difficult for these patients to carry out peritoneal dialysis (PD) on their own....     

A two-asset stochastic model for long-term portfolio selection

In mean–variance (M–V) analysis, an investor with a holding period [0,T] operates in a two-dimensional space—one is the mean and the other is the variance. At time 0, he/she evaluates alternative portfolios based on their means and variances, and holds a combination of the market portfolio (e.g., an index fund) and the risk-free asset to maximize his/her expected utility at time T. In our continuous-time model, we operate in a three-dimensional space—the first is the spot rate, the second is the expected return on the risky asset (e.g., an index fund), and the third is time. At various times over [0,T], we determine, for each combination of the spot rate and expected return, the optimum fractions invested in the risky and risk-free assets to maximize our expected utility at time T. Hence, unlike those static M–V models, our dynamic model allows investors to trade at any time in response to changes in the market conditions and the length of their holding period. Our results show that (1) the optimum fraction y*(t) in the risky asset increases as the expected return increases but decreases as the spot rate increases; (2) y*(t) decreases as the holding period shortens; and (3) y*(t) decreases as the risk aversion parameter-γ is larger.     

A kernel‐based core growing clustering method

In this paper, a novel clustering method in the kernel space is proposed. It effectively integrates several existing algorithms to become an iterative clustering scheme, which can handle clusters with arbitrary shapes. In our proposed approach, a reasonable initial core for each of the cluster is estimated. This allows us to adopt a cluster growing technique, and the growing cores offer partial hints on the cluster association. Consequently, the methods used for classification, such as support vector machines (SVMs), can be useful in our approach. To obtain initial clusters effectively, the notion of the incomplete Cholesky decomposition is adopted so that the fuzzy c‐means (FCM) can be used to partition the data in a kernel defined‐like space. Then a one‐class and a multiclass soft margin SVMs are adopted to detect the data within the main distributions (the cores) of the clusters and to repartition the data into new clusters iteratively. The structure of the data set is explored by pruning the data in the low‐density region of the clusters. Then data are gradually added back to the main distributions to assure exact cluster boundaries. Unlike the ordinary SVM algorithm, whose performance relies heavily on the kernel parameters given by the user, the parameters are estimated from the data set naturally in our approach. The experimental evaluations on two synthetic data sets and four University of California Irvine real data benchmarks indicate that the proposed algorithms outperform several popular clustering algorithms, such as FCM, support vector clustering (SVC), hierarchical clustering (HC), self‐organizing maps (SOM), and non‐Euclidean norm fuzzy c‐means (NEFCM). © 2009 Wiley Periodicals, Inc.4     

Extraction of Speaker Features from Different Stages of DSR Front-Ends for Distributed Speaker Verification

The ETSI has recently published a front-end processing standard for distributed speech recognition systems. The key idea of the standard is to extract the spectral features of speech signals at the front-end terminals so that acoustic distortion caused by communication channels can be avoided. This paper investigates the effect of extracting spectral features from different stages of the front-end processing on the performance of distributed speaker verification systems. A technique that combines handset selectors with stochastic feature transformation is also employed in a back-end speaker verification system to reduce the acoustic mismatch between different handsets. Because the feature vectors obtained from the back-end server are vector quantized, the paper proposes two approaches to adding Gaussian noise to the quantized feature vectors for training the Gaussian mixture speaker models. In one approach, the variances of the Gaussian noise are made dependent on the codeword distance. In another approach, the variances are a function of the distance between some unquantized training vectors and their closest code vector. The HTIMIT corpus was used in the experiments and results based on 150 speakers show that stochastic feature transformation can be added to the back-end server for compensating transducer distortion. It is also found that better verification performance can be achieved when the LMS-based blind equalization in the standard is replaced by stochastic feature transformation.     

A provably secure and efficient two‐party password‐based explicit authenticated key exchange protocol resistance to password guessing attacks

Password‐based two‐party authenticated key exchange (2PAKE) protocol enables two or more entities, who only share a low‐entropy password between them, to authenticate each other and establish a high‐entropy secret session key. Recently, Zheng et al. proposed a password‐based 2PAKE protocol based on bilinear pairings and claimed that their protocol is secure against the known security attacks. However, in this paper, we indicate that the protocol of Zheng et al. is insecure against the off‐line password guessing attack, which is a serious threat to such protocols. Consequently, we show that an attacker who obtained the users' password by applying the off‐line password guessing attack can easily obtain the secret session key. In addition, the protocol of Zheng et al. does not provide the forward secrecy of the session key. As a remedy, we also improve the protocol of Zheng et al. and prove the security of our enhanced protocol in the random oracle model. The simulation result shows that the execution time of our 2PAKE protocol is less compared with other existing protocols. Copyright © 2015 John Wiley & Sons, Ltd.     

Evidence for inhibition of monoamine oxidase in vivo in rat brain by 7,8-dichloro-1,2,3,4-tetrahydroisoquinoline

7,8-Dichloro-1,2,3,4-tetrahydroisoquinoline (DCTQ) (50 mg/kg i.p.) antagonized the inactivation of MAO by pargyline as measured by direct enzyme assays in brain homogenates and by accumulation of hypothalamic catecholamines. These findings lend credence to the earlier interpretation that changes in brain concentrations of biogenic amines and their metabolites in DCTQ-treated rats were due at least in part to MAO inhibition.     

A more efficient and secure ID-based remote mutual authentication with key agreement scheme for mobile devices on elliptic curve cryptosystem

Recently, Yang and Chang proposed an identity-based remote login scheme using elliptic curve cryptography for the users of mobile devices. We have analyzed the security aspects of the Yang and Chang's scheme and identified some security flaws. Also two improvements of the Yang and Chang's scheme have been proposed recently, however, it has been found that the schemes have similar security flaws as in the Yang and Chang's scheme. In order to remove the security pitfalls of the Yang and Chang and the subsequent schemes, we proposed an enhanced remote user mutual authentication scheme that uses elliptic curve cryptography and identity-based cryptosystem with three-way challenge-response handshake technique. It supports flawless mutual authentication of participants, agreement of session key and the leaked key revocation capability. In addition, the proposed scheme possesses low power consumption, low computation cost and better security attributes. As a result, the proposed scheme seems to be more practical and suitable for mobile users for secure Internet banking, online shopping, online voting, etc.     

The effect of carbon on oxygen precipitation in high carbon CZ silicon crystals

To clarify the role of carbon impurities in the formation of oxygen precipitates, the behavior of CZ silicon wafers with varying carbon concentrations from 0.2 ppm to 2 ppm were studied under different heat treatment conditions. It is found that the rate of reduction in interstitial oxygen is not a function of carbon concentration as reported previously for both the cases of medium and low temperature annealing. Under medium temperature (1050°C) annealing no carbon reduction was detected, even though the reduction in interstitial oxygen can be very large, while with low temperature (750°C) annealing, oxygen reduction is always associated with the carbon reduction, but is not dependent on carbon concentration alone. A heterogenous precipitation model is presented to explain the observed phenomena.     

Control and simulation for a closed-chain dual redundant ' manipulator system

The two-level hierarchical control scheme is adopted to solve a dual-chain robotic system formed by two redundant manipulators grasping a common object with hard point contacts. The upper-level coordinator gathers all the necessary information to resolve the force distribution problem so as to generate all the desired contact forces With all the desired contact forces being specified, the dynamics of each chain are decoupled. Therefore, the lower-level local control problem can be treated as a general open-chain redundant manipulator problem. Furthermore, the Compact-Dual LP method is applied to resolve the upper-level coordination problem; while the Compact QP method associated with the computed torque control method is adopted to solve the redundant manipulator problem. To obtain proper simulation results, the simulated actual contact forces are formulated and the corresponding simulation problem of the closed-chain robotic system is also completely solved in the article. Simulation results show that the two-level hierarchical control scheme is an effective and efficient algorithm for resolving the large-scale control problem of multiple-chain robotic systems. © 1995 John Wiley & Sons, Inc.