An XML-based continuous auditing web services model -An Implementation Study

The concepts of continuous auditing are now more than two decades old, many researchers have issued differ continuous audit system model for applying over internet technology. A continuous audit is an assurance service where the time between the occurrence of events underlying a particular subject matter and the issuance of an auditor‘s opinion on the fairness of a client‘s representation of the subject matter is eliminated. The auditor offer restricted views provided by the continuous audit web services (CAWS) routines on a fee basis to analysts, investors, financial institutions, and other parties interested in obtaining continuous audit (CA) of business performance or other audit objects of interest. In our study proposed not only discuss with how to ensure the integrity and effectiveness of the entire data collection system but also implement the XML web services to enterprise applied for correctness and usefulness well-known the CAWS model. The CAWS design and demonstrate an implementation of continuous audit with the internal auditor data verify for compliance CA domain. The demonstrated CAWS model uses data retrieval layer, data analysis layer and data presentation layer over the internet to continuously monitor by the audit department. The article concludes with suggestion for future research and our implemented experiences

Colour morphology and its approaches

Mathematical morphology was first applied to binary images and readily extended to grey-level images. In extending mathematical morphology to colour it is difficult to define a suitable unambiguous ordering. We present two complete ordering schemes based on colour difference and similarity ordering for colour morphology. A novel colour difference formula is first introduced. This colour difference formula is based on colour extrema derived from a simple physical model of image formation and avoids the more arbitrary mathematical and perceptual definitions previously reported. Moreover, we define similarity criteria as the basis for mathematical morphology that can be used with flat and non-flat structuring elements. The proposed orderings meet the properties of mathematical morphology, and provide a harmonised approach for binary, grey-level and colour morphology. A comparison of ordering schemes for dilation, erosion, opening, closing and filtering operator shows the colour difference-based ordering presented here to be at least as good as other ordering schemes and better than some of the well principled, previously reported methods in not generating artefacts and reducing image noise. Additionally, the development of a similarity-based ordering to perform morphological gradient and Hit-or-Miss transforms for colour images is presented

An Ensemble Classifier for Stock Trend Prediction Using Sentence-Level Chinese News Sentiment and Technical Indicators

In the financial market, predicting stock trends based on stock market news is a challenging task, and researchers are devoted to developing forecasting models. From the existing literature, the performance of the forecasting model is better when news sentiment and technical analysis are considered than when only one of them is used. However, analyzing news sentiment for trend forecasting is a difficult task, especially for Chinese news, because it is unstructured data and extracting the most important features is difficult. Moreover, positive or negative news does not always affect stock prices in a certain way. Therefore, in this paper, we propose an approach to build an ensemble classifier using sentiment in Chinese news at sentence level and technical indicators to predict stock trends. In the training stages, we first divide each news item into a set of sentences. TextRank and word2vec are then used to generate a predefined number of key sentences. The sentiment scores of these key sentences are computed using the given financial lexicon. The sentiment values of the key phrases, the three values of the technical indicators and the stock trend label are merged as a training instance. Based on the sentiment values of the key sets, the corpora are divided into positive and negative news datasets. The two datasets formed are then used to build positive and negative stock trend prediction models using the support vector machine. To increase the reliability of the prediction model, a third classifier is created using the Bollinger Bands. These three classifiers are combined to form an ensemble classifier. In the testing phase, a voting mechanism is used with the trained ensemble classifier to make the final decision based on the trading signals generated by the three classifiers. Finally, experiments were conducted on five years of news and stock prices of one company to show the effectiveness of the proposed approach, and results show that the accuracy and P / L ratio of the proposed approach are 61% and 4.0821 are better than the existing approach

N 1,N 2-Bis(6-methyl-2-pyrid­yl)formamidine

In the crystal structure of the title mol­ecule, C13H14N4, the two pyridyl rings are not coplanar but twisted about the C—N bond with an inter­planar angle of 71.1 (1)°. In the crystal, the mol­ecules form dimers, situated on crystallographic centres of inversion, which are connected via a pair of N—H⋯N hydrogen bonds. C—H⋯π-electron ring inter­actions are also present in the crystal structure. The title mol­ecule adopts an s–cis–anti–s–cis conformation in the solid state

Methyl 4-[(5-chloro­pyrimidin-2-yl)carbamo­yl]benzoate

Mol­ecules of the title compound, C13H10ClN3O3, form centrosymmetric dimers via inter­molecular N—H⋯N hydrogen bonds generating an R 2 2(8) motif. The dimers are further connected through an O⋯Cl—C halogen bond [O⋯Cl = 3.233 (1) Å and O⋯Cl—C = 167.33 (1)°] into a chain along [110]. The secondary amide group adopts a cis conformation. Weak C—H⋯N hydrogen bonds among the methyl benzoate and pyrimidyl rings are also observed in the crystal structure

4-Methyl-N-[(Z)-3-(4-methyl­phen­ylsulfon­yl)-1,3-thia­zolidin-2-yl­idene]benzene­sulfonamide

In the crystal structure of the title compound, C17H18N2O4S3, mol­ecules are connected into centrosymmetric dimers via weak inter­molecular C—H⋯π inter­actions. These dimers are further connected through a series of weak C—H⋯O hydrogen bonds, while futher C—H⋯π inter­actions involving the phenyl and thia­zoline rings are also observed. The thia­zolidine ring is twisted from the benzene rings rings by dihedral angles of 79.1 (1) and 85.0 (1)°, while the dihedral angle between two benzene rings is 76.0 (1)°

Integrating the BWM and TOPSIS algorithm to evaluate the optimal token exchanges platform in Taiwan

This research presents procedures for determining the optimal solution of token exchanges platform for investors in Taiwan via integrating the best-worst method (BWM) and the technique for ordering preference by similarity to the ideal solution (TOPSIS). Firstly, this research applies the modified Delphi method to develop the perspectives and factors via literature review and experts opinion. Secondly, the BWM is implemented to obtain weights of perspectives and factors on the linear programming concept. Thirdly, the TOPSIS model is used to rank the optimal solution of the token exchange for investors or corporations. Finally, the proposed model BWMTOPSIS-based procedures will list the optimal token exchanges platform on the three token exchange platforms to investors or corporations in Taiwan on the basis of their rankings in the architecture. The proposed combination framework is able to provide academic and commerce support to investors or corporations in implementing the token into their portfolio as a valuable objective guide to determine the optimal token exchange platform. First published online 09 December 202