Asset Allocation under the Basel Accord Risk Measures

Financial institutions are currently required to meet more stringent capital requirements than they were before the recent financial crisis; in particular, the capital requirement for a large bank's trading book under the Basel 2.5 Accord more than doubles that under the Basel II Accord. The significant increase in capital requirements renders it necessary for banks to take into account the constraint of capital requirement when they make asset allocation decisions. In this paper, we propose a new asset allocation model that incorporates the regulatory capital requirements under both the Basel 2.5 Accord, which is currently in effect, and the Basel III Accord, which was recently proposed and is currently under discussion. We propose an unified algorithm based on the alternating direction augmented Lagrangian method to solve the model; we also establish the first-order optimality of the limit points of the sequence generated by the algorithm under some mild conditions. The algorithm is simple and easy to implement; each step of the algorithm consists of solving convex quadratic programming or one-dimensional subproblems. Numerical experiments on simulated and real market data show that the algorithm compares favorably with other existing methods, especially in cases in which the model is non-convex

Dyson-Schwinger equations towards cold-dense QCD matter with improved truncations

We take the Dyson-Schwinger equation (DSE) approach of QCD to study the phase transition and the equation of state of cold dense matter. Besides the bare vertex and Gauss gluon model, we take into account an improved truncation scheme, the CLRQ vertex and infrared-constant gluon model. For the dynamical chiral symmetry breaking solution of the DSE, we require that the emergence of quark number density to be at the chemical potential for the nuclear liquid-gas phase transition to take place, by incorporating a chemical potential dependent modification factor to the gluon model. The result shows that our modified scheme can not only describe the phase transition of the cold dense matter well but also the deduced equation of state of the matter can describe the recent astronomical observations consistently

Structural difference rule for amorphous alloy formation by ion mixing

We formulate a rule which establishes a sufficient condition that an amorphous binary alloy will be formed by ion mixing of multilayered samples when the two constituent metals are of different crystalline structure, regardless of their atomic sizes and electronegativities. The rule is supported by the experimental results we have obtained on six selected binary metal systems, as well as by the previous data reported in the literature. The amorphization mechanism is discussed in terms of the competition between two different structures resulting in frustration of the crystallization process

Rotation-invariant features for multi-oriented text detection in natural images.

Texts in natural scenes carry rich semantic information, which can be used to assist a wide range of applications, such as object recognition, image/video retrieval, mapping/navigation, and human computer interaction. However, most existing systems are designed to detect and recognize horizontal (or near-horizontal) texts. Due to the increasing popularity of mobile-computing devices and applications, detecting texts of varying orientations from natural images under less controlled conditions has become an important but challenging task. In this paper, we propose a new algorithm to detect texts of varying orientations. Our algorithm is based on a two-level classification scheme and two sets of features specially designed for capturing the intrinsic characteristics of texts. To better evaluate the proposed method and compare it with the competing algorithms, we generate a comprehensive dataset with various types of texts in diverse real-world scenes. We also propose a new evaluation protocol, which is more suitable for benchmarking algorithms for detecting texts in varying orientations. Experiments on benchmark datasets demonstrate that our system compares favorably with the state-of-the-art algorithms when handling horizontal texts and achieves significantly enhanced performance on variant texts in complex natural scenes

A Fast, Efficient Domain Adaptation Technique for Cross-Domain Electroencephalography(EEG)-Based Emotion Recognition

Electroencephalography (EEG)-based emotion recognition is an important element in psychiatric health diagnosis for patients. However, the underlying EEG sensor signals are always non-stationary if they are sampled from different experimental sessions or subjects. This results in the deterioration of the classification performance. Domain adaptation methods offer an effective way to reduce the discrepancy of marginal distribution. However, for EEG sensor signals, both marginal and conditional distributions may be mismatched. In addition, the existing domain adaptation strategies always require a high level of additional computation. To address this problem, a novel strategy named adaptive subspace feature matching (ASFM) is proposed in this paper in order to integrate both the marginal and conditional distributions within a unified framework (without any labeled samples from target subjects). Specifically, we develop a linear transformation function which matches the marginal distributions of the source and target subspaces without a regularization term. This significantly decreases the time complexity of our domain adaptation procedure. As a result, both marginal and conditional distribution discrepancies between the source domain and unlabeled target domain can be reduced, and logistic regression (LR) can be applied to the new source domain in order to train a classifier for use in the target domain, since the aligned source domain follows a distribution which is similar to that of the target domain. We compare our ASFM method with six typical approaches using a public EEG dataset with three affective states: positive, neutral, and negative. Both offline and online evaluations were performed. The subject-to-subject offline experimental results demonstrate that our component achieves a mean accuracy and standard deviation of 80.46% and 6.84%, respectively, as compared with a state-of-the-art method, the subspace alignment auto-encoder (SAAE), which achieves values of 77.88% and 7.33% on average, respectively. For the online analysis, the average classification accuracy and standard deviation of ASFM in the subject-to-subject evaluation for all the 15 subjects in a dataset was 75.11% and 7.65%, respectively, gaining a significant performance improvement compared to the best baseline LR which achieves 56.38% and 7.48%, respectively. The experimental results confirm the effectiveness of the proposed method relative to state-of-the-art methods. Moreover, computational efficiency of the proposed ASFM method is much better than standard domain adaptation; if the numbers of training samples and test samples are controlled within certain range, it is suitable for real-time classification. It can be concluded that ASFM is a useful and effective tool for decreasing domain discrepancy and reducing performance degradation across subjects and sessions in the field of EEG-based emotion recognition

Production of biscuits by substitution with different ratios of yellow pea flour

To promote the commercialization of yellow pea flour (YPF) due to its nutritional benefits. Four biscuits with different YPF ratio (10%–50%) were conducted to explore the optimal addition percentage. The effects of YPF on the rheological and baking performance of biscuits were performed. The results showed that the substitution ratio of YPF and milling methods had a critical impact on the rheological properties of dough. The dough stability decreased gradually while a softening degree increased with YPF ratio increased. In a term of biscuits, the dimensions of length (L), width (W), thickness (T) and color (L*) of biscuits reduced as YPF addition ratio increased, while colors (a* and b*) and hardness apparently increased. In addition, milling methods had a great influence on the texture and sensory evaluation of four biscuits. The dimensions and color parameters of biscuits from fine flours were larger than that from coarse flours, whereas hardness from fine flours was relatively softer, indicating flour with fine particle size could accelerate the extension and expansion of dough network, and improve Maillard reaction during baking. The highest sensory score for short and tough biscuits was obtained given at YPF ratio of 30% without compromising the qualities of biscuits

Relationship between adiponectin and testosterone in patients with type 2 diabetes

Introduction: This study was designed to investigate the relationship between serum adiponectin and testosterone in patients with type 2 diabetes. Materials and methods: Serum level of adiponectin and testosterone were prospectively measured in 65 patients with type 2 diabetes and in 20 healthy subjects. Testosterone was determined by the radio-immunoassay, whereas adiponectin levels were determined by enzyme-linked immunosorbent assay (ELISA). Results: The average serum testosterone did not differ between the diabetes and the control group, but the average adiponectin in the diabetes group was lower (14.6 (14.2-15.0) vs. 24.3 (24.05-24.55) ng/mL, P = 0.001). In the diabetes group, the serum adiponectin level in patients with renal dysfunction (22.3 (21.5-23.1) ng/mL) was higher than in patients with no complications (12.1 (11.45-12.75) ng/mL) and than in patients with coronary artery disease (11.2 (10.25-12.15) ng/mL) (P = 0.009). Univariate correlation analysis showed an inverse weak correlation between adiponectin and testosterone concentrations in male diabetic patients (r = -0.27, P = 0.009). There was no significant correlation between adiponectin and testosterone in female patients (r = -0.05, P = 0.167). Conclusions: We conclude that patients with type 2 diabetes have lower serum adiponectin concen-tration than healthy individuals, and that there is a weak inverse correlation between adiponectin and testosterone serum concentrations in male diabetics