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

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

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

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 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 adde

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

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 $\Lambda_{eff}$ which is the sum of the quantum zero point energy $\Lambda_{dark energy}$ and the geometric cosmological constant $\Lambda$. The OPERA experiment can be applied to determine the geometric cosmological constant $\Lambda$. It is the first time to distinguish the contributions of $\Lambda$ and $\Lambda_{dark energy}$ 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

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

Pengaruh Penambahan Beberapa Esens Buah pada Perangkap Metil Eugenol terhadap Ketertarikan Lalat Buah Bactrocera Dorsalis Kompleks pada Pertanaman Mangga di Desa Pasirmuncang, Majalengka

Fruit fly (Bactrocera dorsalis Complex) is one of the major pests in horticultural commodities in Indonesia. In this present study, a control method of formulating methyl eugenol and the addition of fruit essences was tested to attract B. dorsalis Complex. The objective was to find out the effect of fruit essences addition in the performance of methyl eugenol in attracting fruit flies and to obtain the most effective fruit essences for attracting male and female fruit flies. The experiment was conducted on mango plantation in Pasirmuncang village, Majalengka, West Java from March 2016 until December 2016. Several synthetic fruit essences which were separately added to methyl eugenol in this experiment were mango, citrus, guava, and starfruit essences. The results showed that the addition of fruit essences on methyl eugenol traps had the same effectiveness or as good as any single methyl eugenol trap. Moreover, the additions of mango and orange essences were not effective enough in attracting female fruit flies, although the number of female fruit flies that were caught were more than the other treatments. IntisariLalat buah Bactrocera dorsalis Kompleks merupakan salah satu hama utama pada komoditas hortikultura. Pada penelitian ini, metode pengendalian dengan memformulasikan metil eugenol dan tambahan esens buah diuji untuk menarik B. dorsalis Kompleks. Tujuannya adalah untuk mengetahui efek penambahan esens buah pada kinerja perangkap metil eugenol dalam menarik lalat buah serta untuk mendapatkan esens buah yang efektif untuk menarik lalat buah betina. Penelitian ini dilakukan di perkebunan mangga di desa Pasirmuncang, Majalengka, Jawa Barat dari bulan Maret 2016 hingga bulan Desember 2016. Beberapa jenis esens buah sintetik yang secara terpisah ditambahkan pada metil eugenol pada percobaan ini adalah mangga, jeruk, jambu biji, dan belimbing. Hasil penelitian menunjukkan bahwa penambahan esens buah pada perangkap metil eugenol memiliki keefektifan yang sama baiknya dengan perangkap metil eugenol secara tunggal. Selain itu, penambahan esens mangga dan esens jeruk belum cukup efektif dalam menarik lalat buah betina meskipun jumlah lalat buah betina yang tertangkap lebih banyak dibandingkan dengan perlakuan lainnya