Privacy-Protection Scheme of a Credit-Investigation System Based on Blockchain

In response to the rapid growth of credit-investigation data, data redundancy among credit-investigation agencies, privacy leakages of credit-investigation data subjects, and data security risks have been reported. This study proposes a privacy-protection scheme for a credit-investigation system based on blockchain technology, which realizes the secure sharing of credit-investigation data among multiple entities such as credit-investigation users, credit-investigation agencies, and cloud service providers. This scheme is based on blockchain technology to solve the problem of islanding of credit-investigation data and is based on zero-knowledge-proof technology, which works by submitting a proof to the smart contract to achieve anonymous identity authentication, ensuring that the identity privacy of credit-investigation users is not disclosed; this scheme is also based on searchable-symmetric-encryption technology to realize the retrieval of the ciphertext of the credit-investigation data. A security analysis showed that this scheme guarantees the confidentiality, the availability, the tamper-proofability, and the ciphertext searchability of credit-investigation data, as well as the fairness and anonymity of identity authentication in the credit-investigation data query. An efficiency analysis showed that, compared with similar identity-authentication schemes, the proof key of this scheme is smaller, and the verification time is shorter. Compared with similar ciphertext-retrieval schemes, the time for this scheme to generate indexes and trapdoors and return search results is significantly shorter.     

A bounded convection scheme for the overlapping control volume approach

This paper introduces a flux-limited scheme FLOCV for the overlapping control volume (OCV) approach to 2D steady and unsteady convection–diffusion problems on structured non-orthogonal grids. FLOCV switches from second- to first-order interpolation in the presence of extrema. Smooth switching between the two is ensured by weighted average second- and first-order upwind differencing, with the weights being dynamically determined. Five convective test problems are solved using this scheme and results are compared with known analytical solutions. It is found that FLOCV approximately retains second-order accuracy of the base discretization scheme on uniform grids and smooth non-uniform orthogonal grids. It is also found effective in removing oscillations for problems with discontinuities on both orthogonal and non-orthogonal grids, with little degradation of accuracy. © 1997 John Wiley & Sons, Ltd.     

Establishing a New Link between Fuzzy Logic,Neuroscience, and Quantum Mechanics through Bayesian Probability: Perspectives in Artificial Intelligence and Unconventional Computing

Human interaction with the world is dominated by uncertainty. Probability theory is a valuable tool to face such uncertainty. According to the Bayesian definition, probabilities are personal beliefs. Experimental evidence supports the notion that human behavior is highly consistent with Bayesian probabilistic inference in both the sensory and motor and cognitive domain. All the higher-level psychophysical functions of our brain are believed to take the activities of interconnected and distributed networks of neurons in the neocortex as their physiological substrate. Neurons in the neocortex are organized in cortical columns that behave as fuzzy sets. Fuzzy sets theory has embraced uncertainty modeling when membership functions have been reinterpreted as possibility distributions. The terms of Bayes’ formula are conceivable as fuzzy sets and Bayes’ inference becomes a fuzzy inference. According to the QBism, quantum probabilities are also Bayesian. They are logical constructs rather than physical realities. It derives that the Born rule is nothing but a kind of Quantum Law of Total Probability. Wavefunctions and measurement operators are viewed epistemically. Both of them are similar to fuzzy sets. The new link that is established between fuzzy logic, neuroscience, and quantum mechanics through Bayesian probability could spark new ideas for the development of artificial intelligence and unconventional computing.     

Controlled Drug Delivery Systems: Current Status and Future Directions

The drug delivery system enables the release of the active pharmaceutical ingredient to achieve a desired therapeutic response. Conventional drug delivery systems (tablets, capsules, syrups, ointments, etc.) suffer from poor bioavailability and fluctuations in plasma drug level and are unable to achieve sustained release. Without an efficient delivery mechanism, the whole therapeutic process can be rendered useless. Moreover, the drug has to be delivered at a specified controlled rate and at the target site as precisely as possible to achieve maximum efficacy and safety. Controlled drug delivery systems are developed to combat the problems associated with conventional drug delivery. There has been a tremendous evolution in controlled drug delivery systems from the past two decades ranging from macro scale and nano scale to intelligent targeted delivery. The initial part of this review provides a basic understanding of drug delivery systems with an emphasis on the pharmacokinetics of the drug. It also discusses the conventional drug delivery systems and their limitations. Further, controlled drug delivery systems are discussed in detail with the design considerations, classifications and drawings. In addition, nano-drug delivery, targeted and smart drug delivery using stimuli-responsive and intelligent biomaterials is discussed with recent key findings. The paper concludes with the challenges faced and future directions in controlled drug delivery.     

Finite differences on triangular grids

We define a finite differences method for triangular grids and we show how to link it to a finite element method. From this new point of view we then analyze properties of the solution and convergence. © 1998 John Wiley & Sons, Inc. Numer Methods Partial Differential Eq 14: 567–579, 1998     

A simple grid generation method

This paper presents a simple grid generation method which adopts the uni-directional interpolation idea but only interpolates one co-ordinate between two opposite boundaries. The use of this new scheme showed that (a) it is convenient to use; and (b) compared with the built-in grid generator of certain commercial computational fluid dynamics (CFD) code, it saves time significantly. © 1998 John Wiley & Sons, Ltd.     

A boundary conforming structured grid for global ocean circulation studies

A boundary conforming two-dimensional structured grid for the irregular domain of the world's ocean is generated numerically using differential equation techniques. It is calculated using block structured methods which allow the inclusion of all major bodies of water including seas and basins, and which preserve slope continuity of the co-ordinate lines across the global domain. The block structure is coupled with an innovative blown-up cube model of the Earth which permits all areas of the global ocean to be modeled with the same resolution, eliminating problems associated with polar singularities. The grid is generated on the curved surface of the Earth (rather than the longitude–latitude plane) by employing the Beltrami operator instead of the standard Laplacian operator. Application of the grid to a steady state heat conduction problem shows the relative computational accuracy and the potential to resolve the complex, smaller scale oceanographic phenomena of great importance to global circulation studies. © 1998 John Wiley & Sons, Ltd.     

Investigation of a CPG‐array CdZnTe γ‐ray imaging detector with single collecting electrodes readout

The single‐electrode readout method has been applied to a coplanar grid (CPG) array CdZnTe detector in order to halve the number of preamplifiers previously needed and to facilitate imaging applications of CPG detectors. A method of predetermining the width of the optimum collecting electrodes has also been proposed, using the calculated optimum relative gain factor G. Meanwhile, a detailed process for calculating the charge induction efficiency (CIE) is presented. To simplify the calculation process, the computational formula of the CIE was deduced through the integration of the weighting potential. For performance evaluation, a 2 × 2 CPG‐array CdZnTe detector was elaborately designed and tested with ¹³⁷Cs at 662 keV. Experimental results showed the capability of using the CPG‐array CdZnTe detector with single collecting electrode readout for γ‐ray imaging applications, with the same complexity of associated readout electronics as that of the pixelated CdZnTe detectors.     

The Finite Difference Based Fast Adaptive Composite Grid Method

The fast adaptive composite grid (FAC) method is an iterative method for solving discrete boundary value problems on composite grids. McCormick introduced the method in [8] and considered the convergence behaviour for discrete problems resulting from finite volume element discretization on composite grids. In this paper we consider discrete problems resulting from finite difference discretization on composite grids. We distinguish between two obvious discretization approaches at the grid points on the interfaces between fine and coarse subgrids. The FAC method for solving such discrete problems is described. In the FAC method several intergrid transfer operators appear. We study how the convergence behaviour depends on these intergrid transfer operators. Based on theoretical insights, (quasi-)optimal intergrid transfer operators are derived. Numerical results illustrate the fast convergence of the FAC method using these intergrid transfer operators.