A Comparative Study of Data Mining Techniques for Credit Scoring in Banking

Shih-Chen Huang and Min-Yuh Day (2013), "A Comparative Study of Data Mining Techniques for Credit Scoring in Banking", in Proceedings of the IEEE International Conference on Information Reuse and Integration (IEEE IRI 2013), San Francisco, California, USA, August 14-16, 2013, pp. 684-691.[[abstract]]Credit is becoming one of the most important incomes of banking. Past studies indicate that the credit risk scoring model has been better for Logistic Regression and Neural Network. The purpose of this paper is to conduct a comparative study on the accuracy of classification models and reduce the credit risk. In this paper, we use data mining of enterprise software to construct four classification models, namely, decision tree, logistic regression, neural network and support vector machine, for credit scoring in banking. We conduct a systematic comparison and analysis on the accuracy of 17 classification models for credit scoring in banking. The contribution of this paper is that we use different classification methods to construct classification models and compare classification models accuracy, and the evidence demonstrates that the support vector machine models have higher accuracy rates and therefore outperform past classification methods in the context of credit scoring in banking.[[sponsorship]]IEEE[[incitationindex]]EI[[conferencetype]]國際[[conferencedate]]20130814~20130816[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]San Francisco, California, US

Assessing the Effects of Acupuncture by Comparing Needling the Hegu Acupoint and Needling Nearby Nonacupoints by Spectral Analysis of Microcirculatory Laser Doppler Signals

We aimed to assess the effects of acupuncture by analyzing the frequency content of skin blood-flow signals simultaneously recorded at the Hegu acupoint and two nearby nonacupoints following acupuncture stimulation (AS). Laser Doppler flowmetry (LDF) signals were measured in male healthy volunteers in two groups of experiments: needling the Hegu acupoint (n = 13) and needling a nearby nonacupoint (control experiment; n = 10). Each experiment involved recording a 20 min baseline-data sequence and two sets of effects data recorded 0–20 and 50–70 min after stopping AS. Wavelet transform with Morlet mother wavelet was applied to the measured LDF signals. Needling the Hegu acupoint significantly increased the blood flow, significantly decreased the relative energy contribution at 0.02–0.06 Hz and significantly increased the relative energy contribution at 0.4–1.6 Hz at Hegu, but induced no significant changes at the nonacupoints. Also, needling a nearby nonacupoint had no effect in any band at any site. This is the first time that spectral analysis has been used to investigate the microcirculatory blood-flow responses induced by AS, and has revealed possible differences in sympathetic nerve activities between needling the Hegu acupoint and its nearby nonacupoint. One possible weakness of the present design is that different De-Qi feelings following AS could lead to nonblind experimental setup, which may bias the comparison between needling Hegu and its nearby nonacupoint. Our results suggest that the described noninvasive method can be used to evaluate sympathetic control of peripheral vascular activity, which might be useful for studying the therapeutic effects of AS

Anti-Fatigue Effect of Aqueous Extract of Anisomeles indica (L) Kuntze in Mice

Purpose: To determine the anti-fatigue effect of Anisomeles indica (L.) Kuntze, an herb traditionally used for health improvement in Taiwan.Methods: Three groups (n = 10 per group) of Balb/c female mice were administered A. indica aqueous extract orally for 28 days at 125 (low dose A. indica, LA), 250 (medium dose A. indica, MA), and 500 (high dose A. indica, HA) mg/kg/day, respectively, while a control group received distilled water. After 28 days, a forced swimming test was performed, and biochemical parameters including plasma triglyceride (TG), glucose, lactate and ammonia levels related to fatigue were examined.Results: No mice died during the study period. Physical examinations did not reveal any treatmentrelated adverse effects after dosing, in terms of food and water consumption. Moreover, no obvious peptic ulcers, haemorrhage, or pathological changes in the liver or kidney were observed in A. indica treated mice, and there were no significant differences in body weight between the control and treatment groups (p > 0.05). Mice treated with A. indica extract in the MA and HA groups showed significantly prolonged exhaustive swimming time (p < 0.05), increased hepatic glycogen and muscle glycogen levels (p < 0.05), and decreased triglyceride and plasma ammonia levels (p < 0.05) in a dosedependent manner, compared with the controls. However, plasma glucose and lactic acid levels were not significantly changed (p > 0.05).Conclusion: These results provide the first in vivo evidence supporting the anti-fatigue claims associated with A. indica treatment, indicating that this traditional herb may be of therapeutic use as an ergogenic and anti-fatigue agent.Keywords: Anisomeles indica, Exhaustive swimming test, Fatigue, Glycogen, Plasma ammonia, Lactic aci

Lambda Set Selection in Roth-Karp Decomposition for LUT-Based FPGA Technology Mapping," in

Abstract partition tends to produce better results. However, to the best of our knowledge, finding a good input partition in Roth-Karp decomposition has not been formally addressed in previous research. In this paper, we propose a new heuristics to solve this problem. Roth-Karp decomposition is a classical decomposition method. Because it can reduce the number of input variables of a function, it becomes one of the most popular techniques used in LUT-based FPGA technology mapping. However, the lambda set selection problem, which can dramatically affect the decomposition quality in Roth-Karp decomposition, has not been formally addressed before. In this paper, we propose a new heuristic-based algorithm to solve this problem. The experimental results show that our algorithm can efficiently produce outputs with better decomposition quality than that produced by other algorithms without using lambda set selection strategy

Characterizing clinical isolates of Acanthamoeba castellanii with high resistance to polyhexamethylene biguanide in Taiwan

AbstractBackground/PurposeAcanthamoeba keratitis (AK), a painful infectious corneal disease, is caused by the free-living pathogenic species Acanthamoeba. The symptoms include corneal infiltrate, epithelial, and stromal destruction, and loss of vision. Current treatment generally involves an hourly application of polyhexamethylene biguanide (PHMB) over a period of several days; however, even this is not entirely effective against all strains/isolates. The aims of this study were to confirm the existence of pathogenic strains in Taiwan which are highly resistant to drugs and to characterize the behavior of these strains.MethodsAn in vitro Acanthamoeba species culture platform was established to observe the effectiveness of treatment and chart the morphological changes that occur under the effects of drugs using a light microscope and time-lapse recording. Changes in gene expression were examined using reverse transcription polymerase chain reaction (RT-PCR) and real-time PCR.ResultsOver 90% of the standard strain cells (ATCC 30010) were lysed after being treated with PHMB for 1 hour; however, clinical isolates of Acanthamoeba castellanii that differed in their susceptibility to the treatment drug were only partly lysed. Following treatment with PHMB, National Cheng Kung University Hospital isolation B (NCKH_B) transformed into a pseudocyst under the effects of drug stress; however, National Cheng Kung University Hospital isolation D (NCKH_D), an isolate with higher tolerance for PHMB, did not transform.ConclusionOur results confirm the existence of clinical isolates of A. castellanii with high resistance to PHMB in Taiwan and present the alternative drug tolerance of A. castellanii in addition to the transformation of pseudocyst/cyst

Understanding the Impact of Service Failure and Recovery Justice on Consumers’ Satisfaction and Repurchase Intention

This research attempts to explore the impacts of different types of justice and their interactions on the satisfaction toward service failure recovery. We attempt to classify justices into hygiene, motivator, or asymmetric variable, based on the concept of asymmetric effect and two factors theory proposed by Herzberg. Specifically, we predict that procedural and distributive justices are hygiene or performance factor and interpersonal justice is motivator. In addition, based on expectancy-disconfirmation theory (EDT), we also attempt to understand the interaction between paired justices by arguing that motivator can generate more effect when hygiene factor or performance factors meet initial expectation. An experiment, with 3x2x2 between-subjects factorial design consisting of three factors to represent different levels of justice provided by online retailer, will be conducted to test the proposed hypotheses. A two-step approach will be used to (1) confirmation the types (hygiene, performance, or motivator) that each justice dimension belongs to, (2) understand the impact of each justice on satisfaction, and (3) test whether motivator will generate more effect when hygiene and performance factor are satisfied