The n-type Ge photodetectors with gold nanoparticles deposited to enhance the responsivity

Gold nanoparticles (AuNPs) have been deposited on n-type Ge photodetectors to improve the responsivity. Two different coverage ratios, including 10.5 and 30.3% of AuNPs have been prepared, and the fabricated photodetectors are compared with the control sample. The 1,310-nm responsivities at -2 V of the control, 10.5% AuNPs, and 30.3% AuNPs samples are 465, 556, and 623 mA/W, respectively. The AuNPs could increase the responsivities due to the plasmon resonance. The reflectance spectra of these samples have been measured to verify that plasmon resonance contributes to the forward scattering of incident light. The reflectance decreases with AuNP deposition, and a denser coverage results in a smaller reflectance. The smaller reflectance indicates more light could penetrate into the Ge active layer, and it results in a larger responsivity.     

Oxygen saturation-dependent effects on blood transverse relaxation at low fields

Objective

Blood oxygenation can be measured using magnetic resonance using the paramagnetic effect of deoxy-haemoglobin, which decreases the \(\textit{T}_{2}\) relaxation time of blood. This \(\textit{T}_{2}\) contrast has been well characterised at the \(\textit{B}_{{0}}\) fields used in MRI (1.5 T and above). However, few studies have characterised this effect at lower magnetic fields. Here, the feasibility of blood oximetry at low field based on \(\textit{T}_{2}\) changes that are within a physiological relevant range is explored. This study could be used for specifying requirements for construction of a monitoring device based on low field permanent magnet systems.

Methods

A continuous flow circuit was used to control parameters such as oxygen saturation and temperature in a sample of blood. It flowed through a variable field magnet, where CPMG experiments were performed to measure its \(\textit{T}_{2}\). In addition, the oxygen saturation was monitored by an optical sensor for comparison with the \(\textit{T}_{2}\) changes.

Results

These results show that at low \(\textit{B}_{{0}}\) fields, the change in blood \(\textit{T}_{2}\) due to oxygenation is small, but still detectable. The data measured at low fields are also in agreement with theoretical models for the oxy-deoxy \(\textit{T}_{2}\) effect.

Conclusion

\(\textit{T}_{2}\) changes in blood due to oxygenation were observed at fields as low as 0.1 T. These results suggest that low field NMR relaxometry devices around 0.3 T could be designed to detect changes in blood oxygenation.

     

Effects of additives on the electrodeposition of tin from an acidic Sn(II) bath

Additive effects of formaldehyde, propionaldehyde and benzaldehyde on the deposition of tin in acidic solution of tin(II) sulfate have been investigated. The effects of these additives on cathodic polarization and a.c. impedance was measured by galvanostatic or potentiostatic methods, respectively. The reduction products of the aldehyde during the deposition and the diffusion coefficient of Sn(II) in various solutions were also determined.     

Efficient algorithms for selection of recovery points in tree taskmodels

Efficient solutions to the problem of optimally selecting recovery points are developed. The solutions are intended for models of computation in which task precedence has a tree structure and a task may fail due to the presence of faults. An algorithm to minimize the expected computation time of the task system under a uniprocessor environment has been developed for the binary tree model. The algorithm has time complexity of O(N₂), where N is the number of tasks, while previously reported procedures have exponential time requirements. The results are generalized for an arbitrary tree model     

The evaluation of cluster policy by fuzzy MCDM: Empirical evidence from HsinChu Science Park

In the recent years, industrial clusters have received considerable attention from economists and industrial analysts, because they are seen as the main reason for economic growth and success of certain economic region. This study systematically reviews past researches of industrial cluster. The purpose of this paper is to contribute to the understanding of this issue regarding the driving forces for the growth of industrial cluster and find out the priority among these cluster policies. Taiwan HsinChu Science Park is a prime example for this paper, and its connection with the innovative participators. We begin with an examination of the literature on cluster about its driving forces and policies upon which we propose a conceptual framework. In doing so, we explore the cluster-based industrial system. Then this research adopts the Fuzzy Analytic Hierarchy Process as the analytical tool. The Fuzzy Analytic Hierarchy Process method is used to determine the weightings for evaluation dimension among decision makers. From our research results, the Factor Conditions is the most important driving force for advancing the industrial cluster performance. Moreover, the promotion of international linkages policy and broader framework policies rank the first two priorities for cluster policy. Overall, this paper concludes with some simulations of cluster policy alternatives confronting the industry and the Taiwanese government.     

Combined MCDM techniques for exploring stock selection based on Gordon model

Basing on the Gordon model perspective and applying multiple criteria decision making (MCDM), this research explores the influential factors and relative weight of dividend, discount rate, and dividend growth rate. The purpose is to establish an investment decision model and provides investors with a reference/selection of stocks most suitable for investing effects to achieve the greatest returns. Taking full consideration of the interrelation effect among variables of the decision model, this paper introduced analytical network process (ANP) and examined leading electronics companies spanning the hottest sectors of lens, solar, and handset by experts. Empirical findings indicated that dividend was affected by industry outlook, earnings, operating cash flow, and dividend payout rate; discount rate was affected by market β and risk-free rate; and dividend growth rate was affected by earnings growth rate and dividend payout growth rate. Also, according to literatures, discount rate possessed a self-effect relationship. Among the eight evaluation criteria, market β was the most important factor influencing investment decisions, followed by dividend growth rate and risk-free rate. In stock evaluations, leadership companies in the solar industry outperformed those in handset and lens, becoming investors’ favorite stock group at the time that this research was conducted.     

Effective Utilization of Hypercubes in the Presence of Faults

To effectively utilize a faulty hypercube, it is often necessary to reconfigure the hypercube in such a way as to retain as many fault-free nodes as possible. This inspires us to identify maximalincomplete subcubesin a faulty hypercube, as the subcube so reconfigured is often much larger than any complete subcube obtainable and is likely to retain performance better. An efficient algorithm is first presented to find incomplete subcubes in a faulty hypercube. Three applications are then implemented on both an incomplete system and a complete one to measure their actual performance differences. Each application is mapped onto incomplete hypercubes, following the techniques developed for complete hypercubes (possibly with some modifications). Among the three applications,Gaussian eliminationtakes exactly the same mapping scheme on an incomplete system as on a complete one, whileFFTrequires some efforts to adapt it to the incomplete topology. The measured results of the three applications indicate that reconfiguring a faulty hypercube into an incomplete subcube is beneficial in practice.     

A revised discrete particle swarm optimization algorithm for permutation flow-shop scheduling problem

This research proposes a revised discrete particle swarm optimization (RDPSO) to solve the permutation flow-shop scheduling problem with the objective of minimizing makespan (PFSP-makespan). The candidate problem is one of the most studied NP-complete scheduling problems. RDPSO proposes new particle swarm learning strategies to thoroughly study how to properly apply the global best solution and the personal best solution to guide the search of RDPSO. A new filtered local search is developed to filter the solution regions that have been reviewed and guide the search to new solution regions in order to keep the search from premature convergence. Computational experiments on Taillard’s benchmark problem sets demonstrate that RDPSO significantly outperforms all the existing PSO algorithms.     

Optimal resilient threshold GQ signatures

GQ signature scheme is widely used in many cryptographic protocols, such as forward-secure signature scheme, identity-based signature scheme, etc. However, there is no threshold version of this important signature scheme in the open literature. We proposed the first threshold GQ signature scheme. The scheme is proved unforgeable and robust against any adaptive adversary by assuming hardness of computing discrete logarithm modulo a safe prime and existence of fully synchronous broadcast channel. Furthermore, with some modifications, our scheme achieves optimal resilience such that the adversary can corrupt up to a half of the players. As an extension of our work, we provided a threshold identity-based signature scheme and a threshold forward-secure signature scheme, which is the threshold version of the most efficient forward-secure signature scheme up to now.     

A mathematical formulation of uncertain information

This paper introduces a mathematical model of uncertain information. Each body of uncertain information is an information quadruplet, consisting of a code space, a message space, an interpretation function, and an evidence space. Each information quadruplet contains prior information as well as possible new evidence which may appear later. The definitions of basic probability and belief function are based on the prior information. Given new evidence, Bayes' rule is used to update the prior information. This paper also introduces an idea of independent information and its combination. A combination formula is derived for combining independent information. Both the conventional Bayesian approach and Dempster-Shafer's approach belong to this mathematical model. A Bayesian prior probability measure is the prior information of a special information quadruplet; Bayesian conditioning is the combination of special independent information. A Dempster's belief function is the belief function of a different information quadruplet; the Dempster combination rule is the combination rule of independent quadruplets. This paper is a mathematical study of handling uncertainty and shows that both the conventional Bayesian approach and Dempster-Shafer's approach originate from the same mathematical theory.This work was supported in part by the National Science Foundation under grant number IRI-8505735 and a summer research grant of Ball State University.