669 research outputs found
Acculturation of Chinese and Islamic Culture at the Interior of the Ronghe Mosque
The architectural form of the Ronghe mosque is an architectural work with cultural tolerance related to building function change and cultural fusion. The combination of culture is manifested in the form of the mosque’s interior with various elements and ornaments. The visual form of the mosque’s interior represents the function of the building inside. In addition to its practical functions, the visuals mosque buildings provide visual meaning from the result of new formations because they get the influence of Chinese culture the characterizes the mosque so that it becomes a building of places of worship that have own character without reducing the values of Islamic law. Acculturation or cultural fusion in its applica-tion to the interior of mosque has a new form and some are only a combined form. In the discussion of this paper apply the case study approach as part of a qualitative framework, which will be discussed descriptively analytically. This method focuses on periodic observations of the object under study by looking for traces as suggested by Gehl (2013, p.24).
Keywords Acculturation, Chinese Culture, Islamic Culture and Ronghe Mosque
A False Acceptance Error Controlling Method for Hyperspherical Classifiers
Controlling false acceptance errors is of critical importance in many pattern recognition applications, including signature and speaker verification problems. Toward this goal, this paper presents two post-processing methods to improve the performance of hyperspherical classifiers in rejecting patterns from unknown classes. The first method uses a self-organizational approach to design minimum radius hyperspheres, reducing the redundancy of the class region defined by the hyperspherical classifiers. The second method removes additional redundant class regions from the hyperspheres by using a clustering technique to generate a number of smaller hyperspheres. Simulation and experimental results demonstrate that by removing redundant regions these two post-processing methods can reduce the false acceptance error without significantly increasing the false rejection error
One-Class-at-a-Time Removal Sequence Planning Method for Multiclass Classification Problems
Using dynamic programming, this work develops a one-class-at-a-time removal sequence planning method to decompose a multiclass classification problem into a series of two-class problems. Compared with previous decomposition methods, the approach has the following distinct features. First, under the one-class-at-a-time framework, the approach guarantees the optimality of the decomposition. Second, for a K-class problem, the number of binary classifiers required by the method is only K-1. Third, to achieve higher classification accuracy, the approach can easily be adapted to form a committee machine. A drawback of the approach is that its computational burden increases rapidly with the number of classes. To resolve this difficulty, a partial decomposition technique is introduced that reduces the computational cost by generating a suboptimal solution. Experimental results demonstrate that the proposed approach consistently outperforms two conventional decomposition methods
A Training Sample Sequence Planning Method for Pattern Recognition Problems
In solving pattern recognition problems, many classification methods, such as the nearest-neighbor (NN) rule, need to determine prototypes from a training set. To improve the performance of these classifiers in finding an efficient set of prototypes, this paper introduces a training sample sequence planning method. In particular, by estimating the relative nearness of the training samples to the decision boundary, the approach proposed here incrementally increases the number of prototypes until the desired classification accuracy has been reached. This approach has been tested with a NN classification method and a neural network training approach. Studies based on both artificial and real data demonstrate that higher classification accuracy can be achieved with fewer prototypes
Multimodal estimation of distribution algorithms
Taking the advantage of estimation of distribution algorithms (EDAs) in preserving high diversity, this paper proposes a multimodal EDA. Integrated with clustering strategies for crowding and speciation, two versions of this algorithm are developed, which operate at the niche level. Then these two algorithms are equipped with three distinctive techniques: 1) a dynamic cluster sizing strategy; 2) an alternative utilization of Gaussian and Cauchy distributions to generate offspring; and 3) an adaptive local search. The dynamic cluster sizing affords a potential balance between exploration and exploitation and reduces the sensitivity to the cluster size in the niching methods. Taking advantages of Gaussian and Cauchy distributions, we generate the offspring at the niche level through alternatively using these two distributions. Such utilization can also potentially offer a balance between exploration and exploitation. Further, solution accuracy is enhanced through a new local search scheme probabilistically conducted around seeds of niches with probabilities determined self-adaptively according to fitness values of these seeds. Extensive experiments conducted on 20 benchmark multimodal problems confirm that both algorithms can achieve competitive performance compared with several state-of-the-art multimodal algorithms, which is supported by nonparametric tests. Especially, the proposed algorithms are very promising for complex problems with many local optima
The separability of tripartite Gaussian state with amplification and amplitude damping
Tripartite three mode Gaussian state undergoes parametric amplification and
amplitude damping as well as thermal noise is studied. In the case of a state
totally symmetrically interacting with the environment, the time dependent
correlation matrix of the state in evolution is given. The conditions for fully
separability and fully entanglement of the final tripartite three mode Gaussian
state are worked out.Comment: 9 pages, 3 figure
Health and nutrition of Orang Asli (Che Wong) at Krau Wildlife Reserve, Pahang – a descriptive study
This study was conducted to determine the nutritional status of Orang Asli (Che Wong) men,
women and children. Through purposive sampling, 29 households consisting of 29 men, 28 women,
and 20 children (10 female and 10 male) were chosen. Demographic and socioeconomic information
were collected using structured questionnaire. Men and women were measured for height, weight,
blood pressure and waist circumference while weight and height was measured for children.
Mean age for men, women and children were 39.89±17.09 years, 33.7±16.08 years, and 3.25±1.33
years respectively. Only 6.9% of men and 14.3% of women completed 3 years of primary school
education. The average household income was RM 261.56±254.40. Mean Body Mass Index (BMI) for
men was 21.83±3.40 (underweight: 13.8%, normal: 72.4%, overweight: 10.3%, and obese: 3.3%).
Mean Body Mass Index (BMI) for women was 28.6±4.05 (underweight: 23.3%, normal weight:
46.3%, and overweight: 26.7%). The mean circumference for men was 74.43±6.09cm and for women,
it was 73.92±6.80 cm. However, caution should be exercised when interpreting the BMI results
when none of them had waist circumference more than 102 cm (men) and 88 cm (women). About
10.3% of the men and 10.7% of women had blood pressure of more than 130/85 mmHg. The
prevalence of underweight, stunting and wasting of children was 45%, 35% and 30% respectively.
Food frequency questionnaire (FFQ) consisting of seven food groups (cereals, meats, fish, fruits,
vegetables, dairy products and drinks) was used to determine the dietary diversity score. The
minimum score was 0 and the maximum score was 37. Mean total score for men was 9.46±3.70
(maximum score of 18) and for women, it was 9.48 ± 4.63 (maximum score of 21). Food patterns for
both male and female were similar whereby fruits and milk groups were the least consumed. In
conclusion, further research should be conducted in the Che Wong community to determine the
association between food intake and nutritional status of Orang Asli
The CP-violating asymmetry in \eta\to\pi^+ \pi^- e^+e^-
We study the CP-violating asymmetry {\cal A}_{\rm CP}, which arises, in
\eta\to\pi^+\pi^- e^+e^-, from the angular correlation of the e^+ e^- and
\pi^+\pi^- planes due to the interference between the magnetic and electric
decay amplitudes. With the phenomenologically determined magnetic amplitude and
branching ratio as input, the asymmetry, induced by the electric bremsstrahlung
amplitude through the CP-violating decay \eta\to\pi^+\pi^-, and by an
unconventional tensor type operator, has been estimated respectively. The upper
bound of {\cal A}_{\rm CP} from the former is about 10^{-3}, and the asymmetry
from the latter might be up to O(10^{-2}). One can therefore expect that this
CP asymmetry would be an interesting CP-violating observable for the future
precise measurements in the \eta factories.Comment: LaTeX, 6 pages. One reference corrected, and some new references
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On determination of the geometric cosmological constant from the OPERA experiment of superluminal neutrinos
The recent OPERA experiment of superluminal neutrinos has deep consequences
in cosmology. In cosmology a fundamental constant is the cosmological constant.
From observations one can estimate the effective cosmological constant
which is the sum of the quantum zero point energy
and the geometric cosmological constant . The
OPERA experiment can be applied to determine the geometric cosmological
constant . It is the first time to distinguish the contributions of
and from each other by experiment. The
determination is based on an explanation of the OPERA experiment in the
framework of Special Relativity with de Sitter space-time symmetry.Comment: 7 pages, no figure
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