On classifying digital accounting documents

Advances in computing and multimedia technologies allow many accounting documents to be digitized within little cost for effective storage and access. Moreover, the amount of accounting documents is increasing rapidly, this leads to the need of developing some mechanisms to effectively manage those (semi-structured) digital accounting documents for future accounting information systems (AIS). In general, accounting documents contains such as invoices, purchase orders, checks, photographs, charts, diagrams, etc. As a result, the major functionality of future AIS is to automatically classify digital accounting documents into different categories in an effective manner. The aim of this paper is to examine flat nonhierarchical and hierarchical classification schemes for automatic classification of different types of digital accounting documents. The experimental results show that non-hierarchical classification of digital accounting documents performs better than hierarchically classifying digital accounting documents.Los avances en informática y en las tecnologías multimedia permiten, que muchos documentos de contabilidad sean digitalizados por poco dinero para un almacenamiento y acceso efectivos. Además, la cantidad de documentos de contabilidad está incrementando de forma rápida, lo que lleva a la necesidad por desarrollar algunos mecanismos para dirigir efectivamente aquellos (semi-estructurados) documentos de contabilidad digitales para los futuros sistemas de información de contabilidad (AIS en inglés). En general, dichos documentos contienen por ejemplo, facturas, órdenes de compra, comprobaciones, fotografías, gráficos, diagramas, etc. Como resultado, la mayor funcionalidad de los futuros AIS es para clasificar automáticamente los documentos digitales de contabilidad en diferentes categorías de una forma efectiva. El objetivo de este artículo es el de examinar los esquemas de clasificación jerárquica y no jerárquica sin cambios para la clasificación automática de los diferentes tipos de dichos documentos. Los resultados experimentales demuestran que la clasificación no jerárquica de estos documentos tiene más éxito que la jerárquica

Discovering important factors of intangible firm value by association rules

It is very important for investors to understand the critical factors affecting the value of firms before making investments. In knowledge-based economy, the method for creating firm value transfers from traditional physical assets to intangible knowledge. As intangible assets value is an important part of firm value, valuation of intangible assets becomes a widespread topic of interest in the future of economy. This paper applies association rules, one data mining technique, to discover critical factors affecting firm value in Taiwan and to provide a more flexible model than the traditional regression method. Based on collecting related factors found in literature, the results indicate that R&D intensity, family, participation in management, pyramids, profitability, and dividend are the six important factors, in which some are consistent with significant important variables in prior literature, but most of them are unique for Taiwan, one emerging economy

The Development of Audit Detection Risk Assessment System: Using the Fuzzy Theory and Audit Risk Model

The result of audit designation is significantly influenced by the audit evidence collected when planning the audit and the degree of detection risk is further depends on the amount of audit evidence. Therefore, when the assessment factors of detection risk are more objective and correct, audit costs and the risk of audit failure can be reduced. Thus, the aim of this paper is to design an audit detection risk assessment system that could more precisely assess detection risk, comparing with the traditional determination method of detection risk in order to increase the audit quality and reduce the possibility of audit failure. First, the grounded theory is used to reorganize 53 factors affecting detection risk mentioned in literatures and then employed the Delphi method to screen the 43 critical risk factors agreed upon by empirical audit experts. In addition, using the fuzzy theory and audit risk model to calculate the degree of detection risk allow the audit staff to further determine the amount of audit evidence collected and set up initial audit strategies and construct the audit detection risk assessment system. Finally, we considered a case study to evaluate the system in terms of its feasibility and validity

Project dispute prediction by hybrid machine learning techniques

This study compares several well-known machine learning techniques for public-private partnership (PPP) project dispute problems. Single and hybrid classification techniques are applied to construct models for PPP project dispute prediction. The single classification techniques utilized are multilayer perceptron (MLP) neural networks, decision trees (DTs), support vector machines, the naïve Bayes classifier, and k-nearest neighbor. Two types of hybrid learning models are developed. One combines clustering and classification techniques and the other combines multiple classification techniques. Experimental results indicate that hybrid models outperform single models in prediction accuracy, Type I and II errors, and the receiver operating characteristic curve. Additionally, the hybrid model combining multiple classification techniques perform better than that combining clustering and classification techniques. Particularly, the MLP+MLP and DT+DT models perform best and second best, achieving prediction accuracies of 97.08% and 95.77%, respectively. This study demonstrates the efficiency and effectiveness of hybrid machine learning techniques for early prediction of dispute occurrence using conceptual project information as model input. The models provide a proactive warning and decision-support information needed to select the appropriate resolution strategy before a dispute occurs

Inflammatory Marker but Not Adipokine Predicts Mortality among Long-Term Hemodialysis Patients

Aims: chronic inflammation contributes significantly to the morbidity and mortality of chronic hemodialysis patients. A recent research has shown that adipokines were associated with inflammation in these patients. We aim to investigate whether biomarkers of inflammation, adipokines, and clinical features can predict the outcome of hemodialysis patients. Materials and methods: we enrolled 181 hemodialysis patients (men: 97, mean age: 56.3±13.6) and analyzed predictors of long-term outcomes. Results: during the 3-year followup period, 41 patients died; the main causes of death were infection and cardiovascular disease. Elevated serum levels of hsCRP and albumin and advanced age were highly associated with death (all P<.001). Leptin and adiponectin levels were not significantly different between deceased patients and survivors. Cox-regression analysis indicated that age, diabetes, albumin level, and hsCRP were independent factors predicting mortality. Conclusion: the presence of underlying disease, advanced age, and markers of chronic inflammation is strongly related to survival rate in long-term hemodialysis patients

RssAB Signaling Coordinates Early Development of Surface Multicellularity in Serratia marcescens

Bacteria can coordinate several multicellular behaviors in response to environmental changes. Among these, swarming and biofilm formation have attracted significant attention for their correlation with bacterial pathogenicity. However, little is known about when and where the signaling occurs to trigger either swarming or biofilm formation. We have previously identified an RssAB two-component system involved in the regulation of swarming motility and biofilm formation in Serratia marcescens. Here we monitored the RssAB signaling status within single cells by tracing the location of the translational fusion protein EGFP-RssB following development of swarming or biofilm formation. RssAB signaling is specifically activated before surface migration in swarming development and during the early stage of biofilm formation. The activation results in the release of RssB from its cognate inner membrane sensor kinase, RssA, to the cytoplasm where the downstream gene promoters are located. Such dynamic localization of RssB requires phosphorylation of this regulator. By revealing the temporal activation of RssAB signaling following development of surface multicellular behavior, our findings contribute to an improved understanding of how bacteria coordinate their lifestyle on a surface

YamSat: the First Picosatellite being Developed in Taiwan

This paper describes the current planning and design of the YamSat, the first picosatellite being developed in Taiwan. The design, analysis, manufacture, integration, test and operation of the YamSat will be performed by the National Space Program Office (NSPO), Taiwan, R.O.C, in cooperation with other domestic organizations and companies. It is a member of the CubeSat [1], 10cm x 10cm x 10cm size and within 1kg mass. The major objective of the YamSat is to qualify in space the components and technology developed in Taiwan, including a micro-spectrometer payload using Micro Electro Mechanical Systems (MEMS) technology. The YamSat will be ready for flight in the middle of 2002

ENU Mutagenesis Identifies Mice with Morbid Obesity and Severe Hyperinsulinemia Caused by a Novel Mutation in Leptin

BACKGROUND: Obesity is a multifactorial disease that arises from complex interactions between genetic predisposition and environmental factors. Leptin is central to the regulation of energy metabolism and control of body weight in mammals. METHODOLOGY/PRINCIPAL FINDINGS: To better recapitulate the complexity of human obesity syndrome, we applied N-ethyl-N-nitrosourea (ENU) mutagenesis in combination with a set of metabolic assays in screening mice for obesity. Mapping revealed linkage to the chromosome 6 within a region containing mouse Leptin gene. Sequencing on the candidate genes identified a novel T-to-A mutation in the third exon of Leptin gene, which translates to a V145E amino acid exchange in the leptin propeptide. Homozygous Leptin(145E/145E) mutant mice exhibited morbid obesity, accompanied by adipose hypertrophy, energy imbalance, and liver steatosis. This was further associated with severe insulin resistance, hyperinsulinemia, dyslipidemia, and hyperleptinemia, characteristics of human obesity syndrome. Hypothalamic leptin actions in inhibition of orexigenic peptides NPY and AgRP and induction of SOCS1 and SOCS3 were attenuated in Leptin(145E/145E) mice. Administration of exogenous wild-type leptin attenuated hyperphagia and body weight increase in Leptin(145E/145E) mice. However, mutant V145E leptin coimmunoprecipitated with leptin receptor, suggesting that the V145E mutation does not affect the binding of leptin to its receptor. Molecular modeling predicted that the mutated residue would form hydrogen bond with the adjacent residues, potentially affecting the structure and formation of an active complex with leptin receptor within that region. CONCLUSIONS/SIGNIFICANCE: Thus, our evolutionary, structural, and in vivo metabolic information suggests the residue 145 as of special function significance. The mouse model harboring leptin V145E mutation will provide new information on the current understanding of leptin biology and novel mouse model for the study of human obesity syndrome

Women with endometriosis have higher comorbidities: Analysis of domestic data in Taiwan

AbstractEndometriosis, defined by the presence of viable extrauterine endometrial glands and stroma, can grow or bleed cyclically, and possesses characteristics including a destructive, invasive, and metastatic nature. Since endometriosis may result in pelvic inflammation, adhesion, chronic pain, and infertility, and can progress to biologically malignant tumors, it is a long-term major health issue in women of reproductive age. In this review, we analyze the Taiwan domestic research addressing associations between endometriosis and other diseases. Concerning malignant tumors, we identified four studies on the links between endometriosis and ovarian cancer, one on breast cancer, two on endometrial cancer, one on colorectal cancer, and one on other malignancies, as well as one on associations between endometriosis and irritable bowel syndrome, one on links with migraine headache, three on links with pelvic inflammatory diseases, four on links with infertility, four on links with obesity, four on links with chronic liver disease, four on links with rheumatoid arthritis, four on links with chronic renal disease, five on links with diabetes mellitus, and five on links with cardiovascular diseases (hypertension, hyperlipidemia, etc.). The data available to date support that women with endometriosis might be at risk of some chronic illnesses and certain malignancies, although we consider the evidence for some comorbidities to be of low quality, for example, the association between colon cancer and adenomyosis/endometriosis. We still believe that the risk of comorbidity might be higher in women with endometriosis than that we supposed before. More research is needed to determine whether women with endometriosis are really at risk of these comorbidities