• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.2
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• pp.129-152
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• 2024

In the application of deep learning object detection via CCTV in tunnels, a large number of false positive detections occur due to the poor environmental conditions of tunnels, such as low illumination and severe perspective effect. This problem directly impacts the reliability of the tunnel CCTV-based accident detection system reliant on object detection performance. Hence, it is necessary to reduce the number of false positive detections while also enhancing the number of true positive detections. Based on a deep learning object detection model, this paper proposes a false positive data training method that not only reduces false positives but also improves true positive detection performance through retraining of false positive data. This paper's false positive data training method is based on the following steps: initial training of a training dataset - inference of a validation dataset - correction of false positive data and dataset composition - addition to the training dataset and retraining. In this paper, experiments were conducted to verify the performance of this method. First, the optimal hyperparameters of the deep learning object detection model to be applied in this experiment were determined through previous experiments. Then, in this experiment, training image format was determined, and experiments were conducted sequentially to check the long-term performance improvement through retraining of repeated false detection datasets. As a result, in the first experiment, it was found that the inclusion of the background in the inferred image was more advantageous for object detection performance than the removal of the background excluding the object. In the second experiment, it was found that retraining by accumulating false positives from each level of retraining was more advantageous than retraining independently for each level of retraining in terms of continuous improvement of object detection performance. After retraining the false positive data with the method determined in the two experiments, the car object class showed excellent inference performance with an AP value of 0.95 or higher after the first retraining, and by the fifth retraining, the inference performance was improved by about 1.06 times compared to the initial inference. And the person object class continued to improve its inference performance as retraining progressed, and by the 18th retraining, it showed that it could self-improve its inference performance by more than 2.3 times compared to the initial inference.

• Journal of Yeungnam Medical Science
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• v.14 no.2
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• pp.399-414
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• 1997

There are several factors concerning to anemia in chronic renal failure patients. But when rHuEPO is used, most of these factors can be overcome, and the levels of hemoglobin are increased. However, about 10% of the renal failure patients represent rHuEPO-resistant anemia eventhough high dosage of rHuEPO. For these cases, desferrioxamine can be applied to correct rHuEPO resistnacy, and many mechanism of DFO are arguing. So we are going to know whether DFO can be applied to correct anemia of the such patients, how long its effect can be continued. The seven pateients as experimental group(DFO+EPO) who represent refractoriness to rHuEPO and the other seven patients as control group(EPO) were included. Experimental group had lower than 9 g/dL of hemoglobin levels despite high rHuEPO dosage (more than 4000U/Wk) and showed normocytic normochromic anemia. There were no definitve causes of anemia such as hemorrhage or iron deficiency. Control group patients had similar characteristics in age, mean dialysis duration but showed adequate response to rHuEPO. DFO was administered to experimental group for 8 weeks along with rHuEPO(the rHuEPO individual mean dosage had been determined by mean dosage of the previous 6 months. Total mean dosage; 123.5 U/Kg/Wk). After 8 weeks of DFO administration, the hemoglobin and rHuEPO dosage levels were checked for 15 consecutive months. It should be noted that the patients determined their own rHuEPO dosage levels according to hemoglobin levels and economic status. In conrol group, rHuEPO was administered by the same method used in experimental group without DFO through the same period. Fifteen months of observation period after DFO trial were divided as Time I(7 months after DFO trial) and Time II(8 months after Time I). The results are as follows: Before DFO trial, mean hemoglobin level of experimental group was 7.8 g/dL, which is similar level(p>0.05) to control group(mean Hb; 8.2 g/dL). But in experimental group, significantly(p<0.05) higher dosages of rHuEPO(mean; 123.5 U/Kg/Wk) than control group (mean; 41.6 U/Kg/Wk) had been used. It means resistancy to rHuEPO of experimental group. But after DFO trial, the hemoglobin levels of the experimental group were increased significantly(p<0.05), and these effect were continued to Time II.(Time I; mean 8.6g/dL, Time II; mean 8.6g/dL) The effects of DFO to hemoglobin were continued for 15 months after DFO trial with similar degree through Time I, Time II. Also, rHuEPO dosages used in the experimental group were decreased to similar levels of the control group after DFO trial and these effect were also continued for 15 months(Time I; mean 48.1 U/Kg/Wk. Time II; mean 51.8 U/Kg/Wk). In the same period, hemoglobin levels and rHuEPO dosages used in the control group were not changed significantly. Notibly, hemoglobin increment and rHuEPO usage decrement in experimental group were showed maxilly in the 1st month after DFO trial. That is, after the use of DFO, erythopoiesis was enhanced with a reduced rHuEPO dosage. So we think rHuEPO reisistancy can be overcome by DFO therapy. In conclusion, the DFO can improve the anemia caused by chronic renal failure at least over 1 year, and hence, can reduce the dosage of rHuEPO for anemia correction. Additional studies in order to determine the mechanism of DFO on erythropoiesis and careful attention to potential side effects of DFO will be needed.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.111-131
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• 2015

There are only a handful number of research conducted on pattern analysis of corporate distress as compared with research for bankruptcy prediction. The few that exists mainly focus on audited firms because financial data collection is easier for these firms. But in reality, corporate financial distress is a far more common and critical phenomenon for non-audited firms which are mainly comprised of small and medium sized firms. The purpose of this paper is to classify non-audited firms under distress according to their financial ratio using data mining; Self-Organizing Map (SOM). SOM is a type of artificial neural network that is trained using unsupervised learning to produce a lower dimensional discretized representation of the input space of the training samples, called a map. SOM is different from other artificial neural networks as it applies competitive learning as opposed to error-correction learning such as backpropagation with gradient descent, and in the sense that it uses a neighborhood function to preserve the topological properties of the input space. It is one of the popular and successful clustering algorithm. In this study, we classify types of financial distress firms, specially, non-audited firms. In the empirical test, we collect 10 financial ratios of 100 non-audited firms under distress in 2004 for the previous two years (2002 and 2003). Using these financial ratios and the SOM algorithm, five distinct patterns were distinguished. In pattern 1, financial distress was very serious in almost all financial ratios. 12% of the firms are included in these patterns. In pattern 2, financial distress was weak in almost financial ratios. 14% of the firms are included in pattern 2. In pattern 3, growth ratio was the worst among all patterns. It is speculated that the firms of this pattern may be under distress due to severe competition in their industries. Approximately 30% of the firms fell into this group. In pattern 4, the growth ratio was higher than any other pattern but the cash ratio and profitability ratio were not at the level of the growth ratio. It is concluded that the firms of this pattern were under distress in pursuit of expanding their business. About 25% of the firms were in this pattern. Last, pattern 5 encompassed very solvent firms. Perhaps firms of this pattern were distressed due to a bad short-term strategic decision or due to problems with the enterpriser of the firms. Approximately 18% of the firms were under this pattern. This study has the academic and empirical contribution. In the perspectives of the academic contribution, non-audited companies that tend to be easily bankrupt and have the unstructured or easily manipulated financial data are classified by the data mining technology (Self-Organizing Map) rather than big sized audited firms that have the well prepared and reliable financial data. In the perspectives of the empirical one, even though the financial data of the non-audited firms are conducted to analyze, it is useful for find out the first order symptom of financial distress, which makes us to forecast the prediction of bankruptcy of the firms and to manage the early warning and alert signal. These are the academic and empirical contribution of this study. The limitation of this research is to analyze only 100 corporates due to the difficulty of collecting the financial data of the non-audited firms, which make us to be hard to proceed to the analysis by the category or size difference. Also, non-financial qualitative data is crucial for the analysis of bankruptcy. Thus, the non-financial qualitative factor is taken into account for the next study. This study sheds some light on the non-audited small and medium sized firms' distress prediction in the future.

• The Korean Journal of Vision Science
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• v.20 no.4
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• pp.579-588
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• 2018

Purpose : To analyze the eyeglasses supply system for ametropic soldiers in ROK military. Methods : We investigated and analyzed the supply system of eyeglasses for the ametropic soldiers provided by the Korean military. The refractive powers and corrected visual acuity were measured for 37 ametropic soldiers who wear insert glasses for ballistic protective and gas-masks supplied by the military based on their habitual prescriptions. Full correction of refractive error was prescribed for subjects having less than 1.0 of distance visual acuity, and comparison was held for inspecting the changes in corrected visual acuity. Suggestions were provided for solving the issues regarding current supplying system, and this study investigated the applicabilities for utilizing professional optometric manpower. Results : The new glasses supplied by army for ametropic soldiers were duplicated from the glasses they worn when entering the army. The spherical equivalent refractive powers of the conventional, ballistic protective and gas-mask insert glasses supplied for 37 ametropic soldiers were $-3.47{\pm}1.69D$, $-3.52{\pm}1.66D$ and $-3.55{\pm}1.63D$, respectively, and the spherical equivalent refractive power of full corrected glasses was $-3.79{\pm}1.66D$, which showed a significant difference(p<0.05). The distant corrected visual acuity measured at high and low contrast(logMAR) of conventional, ballistic protective and gas-mask insert glasses were $0.06{\pm}0.80$, $0.21{\pm}0.82$, $0.15{\pm}0.74$, $0.34{\pm}0.89$, $0.10{\pm}0.70$ and $0.22{\pm}0.27$, respectively, while the corrected visual acuity by full corrected glasses were increased to $0.02{\pm}1.05$, $0.10{\pm}0.07$, $0.09{\pm}0.92$, $0.26{\pm}0.10$, $0.04{\pm}1.00$ and $0.19{\pm}1.00$, respectively. There was a significant difference(p<0.05) except for the case of the low contrast corrected visual acuity of the conventional and gas-mask insert glasses. The procedure for ordering, dispensing, and supplying military glasses consists of 5 steps, and it was found that approximately two weeks or more are required to supply from the initial examination. Conclusion : The procedure of supplying the military glasses showed three issues: 1) a lack of refraction for prescription system, 2) relatively long length of time required for supplying the glasses, 3) an inaccurate power of supplied glasses. In order to solve those issues, in the short term, education is necessarily required for soldiers on the measurement of the refractive powers, and in the near future, further standard procedures for prescription of glasses as well as the securement of optometric manpower are expected.