An Approach to Generating Arguments over DL-Lite Ontologies

Argumentation frameworks for ontology reasoning and management have received extensive interests in the field of artificial intelligence in recent years. As one of the most popular argumentation frameworks, Besnard and Hunter's framework is built on arguments in form of where Phi is consistent and minimal for entailing phi. However, the problem about generating arguments over ontologies is still open. This paper presents an approach to generating arguments over DL-Lite ontologies by searching support paths in focal graphs. Moreover, theoretical results and examples are provided to ensure the correctness of this approach. Finally, we show this approach has the same complexity as propositional revision

A Multi-Agent System for E-Business Processes Monitoring in a Web-Based Environment

In this paper, we present a multi-agent system MAGS for the e-business processes monitoring in a web-based environment. We classify the types of agents in MAGS by their monitoring capabilities. An algorithm is given to explain the mechanism of supervising and controlling the execution of business processes. An abstract model of alerts, which can give warnings of infringement on business policies, is proposed. Access control can also be realized by MAGS, which manifests in delivering different view of the business process to different roles participate in it. Being successfully adopted in a customer service management system, MAGS has been proven flexible and practical

The Volatility of the Index of Shanghai Stock Market Research Based on ARCH and Its Extended Forms

The proposed ARCH and its extension model have brought a powerful tool for the study of stock market volatility as well as verify that a “high risk brings high-yield” and the “leverage effect” of stock market. This paper gives modeling analysis by using the ARCH group models; in the last ten years Shanghai's index returns, concluded that there are significant “high-yield associated with high-risk” phenomenon and the “leverage effect” in the domestic securities market. The previous studies in fitting return series of ARMA models, mostly with low accuracy have a very subjective “observation autocorrelation and partial autocorrelation function method,” and even directly use “random walk” model. That will inevitably have some impact on the accuracy of the model. While this paper adopts the Pandit-Wu formulaic modeling method, the ARMA model is built on a strong theoretical foundation

Research of Financial Early-Warning Model on Evolutionary Support Vector Machines Based on Genetic Algorithms

A support vector machine is a new learning machine; it is based on the statistics learning theory and attracts the attention of all researchers. Recently, the support vector machines (SVMs) have been applied to the problem of financial early-warning prediction (Rose, 1999). The SVMs-based method has been compared with other statistical methods and has shown good results. But the parameters of the kernel function which influence the result and performance of support vector machines have not been decided. Based on genetic algorithms, this paper proposes a new scientific method to automatically select the parameters of SVMs for financial early-warning model. The results demonstrate that the method is a powerful and flexible way to solve financial early-warning problem

Whole genome resequencing and phenotyping of MAGIC population for high resolution mapping of drought tolerance in chickpea

Terminal drought is one of the major constraints to crop production in chickpea (Cicer arietinum L.). In order to map drought tolerance related traits at high resolution, we sequenced multi-parent advanced generation intercross (MAGIC) population using whole genome resequencing approach and phenotyped it under drought stress environments for two consecutive years (2013-14 and 2014-15). A total of 52.02 billion clean reads containing 4.67 TB clean data were generated on the 1136 MAGIC lines and eight parental lines. Alignment of clean data on to the reference genome enabled identification of a total, 932,172 of SNPs, 35,973 insertions, and 35,726 deletions among the parental lines. A high-density genetic map was constructed using 57,180 SNPs spanning a map distance of 1606.69 cM. Using compressed mixed linear model, genome-wide association study (GWAS) enabled us to identify 737 markers significantly associated with days to 50% flowering, days to maturity, plant height, 100 seed weight, biomass, and harvest index. In addition to the GWAS approach, an identity-by-descent (IBD)-based mixed model approach was used to map quantitative trait loci (QTLs). The IBD-based mixed model approach detected major QTLs that were comparable to those from the GWAS analysis as well as some exclusive QTLs with smaller effects. The candidate genes like FRIGIDA and CaTIFY4b can be used for enhancing drought tolerance in chickpea. The genomic resources, genetic map, marker-trait associations, and QTLs identified in the study are valuable resources for the chickpea community for developing climate resilient chickpeas

Molecular traces of alternative social organization in a termite genome

Although eusociality evolved independently within several orders of insects, research into the molecular underpinnings of the transition towards social complexity has been confined primarily to Hymenoptera (for example, ants and bees). Here we sequence the genome and stage-specific transcriptomes of the dampwood termite Zootermopsis nevadensis (Blattodea) and compare them with similar data for eusocial Hymenoptera, to better identify commonalities and differences in achieving this significant transition. We show an expansion of genes related to male fertility, with upregulated gene expression in male reproductive individuals reflecting the profound differences in mating biology relative to the Hymenoptera. For several chemoreceptor families, we show divergent numbers of genes, which may correspond to the more claustral lifestyle of these termites. We also show similarities in the number and expression of genes related to caste determination mechanisms. Finally, patterns of DNAmethylation and alternative splicing support

The Application of SVMs Method on Exchange Rates Fluctuation

Technical indicators are very important tools in the analysis of securities investment. In this paper, considering several main technical indicators prevailed in China security market, we predict whether the price of a stock rises or falls with the support vector machines (SVMs). We represent the technical indicators of current four days as input vector. If the price of next day rises, we say that the vector belongs to opposite set, if it falls, we say it belongs to negative set. Studying the samples, the SVMs construct a classification model. Then, based on the data of today and three days before, the SVMs give a prediction of tomorrow price. The experiment shows that the predicting accuracy is all greater than 60%

Medical and Interventional Therapy for Spontaneous Vertebral Artery Dissection in the Craniocervical Segment

Background and Purpose. Spontaneous vertebral artery dissection (SVAD) is an important reason for posterior-circulation-ischemic stroke in the young and middle-aged population. Although some previous reports reveal a favorable outcome with conservative therapy, it is still controversial in the treatment of SVAD in some specific patients. Herein, we present our 10 years of clinical experience for SVAD at this location. Material and Methods. 20 patients with 20 SVADs in V2 and V3 segments were retrospectively studied. Clinical manifestations and imageology materials were collected and analyzed. All the patients underwent anticoagulation except for one patient because of contraindication. 14 patients underwent Wingspan stents implantation with general anesthesia. Results. In our sample, ischemia (infarction or transient ischemic attack, TIA) was found in all the patients. Angiographic stenosis and dissection aneurysm were the most common findings in the segments mentioned above. 19 of the patients (95%) got the excellent imageological and clinical outcomes. Conclusions. According to our experience in this group, although anticoagulation is effective in vertebral artery dissection, interventional therapy for SVADs in V2 and/or V3 segments is preferred in some specific patients. Stent with higher radial supporting and flexibility, such as Wingspan stent, is suggested