Financial Computational Intelligence

Artificial intelligence decision support system is always a popular topic in providing the human with an optimized decision recommendation when operating under uncertainty in complex environments. The particular focus of our discussion is to compare different methods of artificial intelligence decision support systems in the investment domain – the goal of investment decision-making is to select an optimal portfolio that satisfies the investor’s objective, or, in other words, to maximize the investment returns under the constraints given by investors. In this study we apply several artificial intelligence systems like Influence Diagram (a special type of Bayesian network), Decision Tree and Neural Network to get experimental comparison analysis to help users to intelligently select the best portfoliArtificial intelligence, neural network, decision tree, bayesian network

Novel CMOS RFIC Layout Generation with Concurrent Device Placement and Fixed-Length Microstrip Routing

With advancing process technologies and booming IoT markets, millimeter-wave CMOS RFICs have been widely developed in re- cent years. Since the performance of CMOS RFICs is very sensi- tive to the precision of the layout, precise placement of devices and precisely matched microstrip lengths to given values have been a labor-intensive and time-consuming task, and thus become a major bottleneck for time to market. This paper introduces a progressive integer-linear-programming-based method to gener- ate high-quality RFIC layouts satisfying very stringent routing requirements of microstrip lines, including spacing/non-crossing rules, precise length, and bend number minimization, within a given layout area. The resulting RFIC layouts excel in both per- formance and area with much fewer bends compared with the simulation-tuning based manual layout, while the layout gener- ation time is significantly reduced from weeks to half an hour.Comment: ACM/IEEE Design Automation Conference (DAC), 201

A preliminary study on the dynamic friction behavior of a one-third scale-down vertical cylindrical cask

In Taiwan, the capacities of spent fuel pools for temporary storage in nuclear power plant will reach depletion soon, and the site of final disposal facility is still to be decided. Therefore, the installation of dry-type interim storage facilities is urgent. The dry storage systems in Taiwan utilize a freestanding cask and design to non-anchored to the foundation pad. It is necessary to establish the simulation techniques for the non-anchored structure, such as the dry storage cask, for the reasonable assessment of its seismic behavior when the earthquake hit. This study is cast a 1/3 scale-down pedestal specimen of the INER-dry storage cask system, which were conducted to acquire the actual friction coefficient at the cask/pad interface as well as the effect of normal stress and sliding rate on it. Based on the results of cyclic loading testing, the cyclic frequency almost had no influence on the friction coefficient but the friction coefficient increased with the normal stress increased. Apparent rocking of the cask was induced at a higher friction coefficient, while sliding dominated the cask motion at a lower one. In addition, the cast motions were almost purely sliding and the range of the friction coefficient was between 0.60 and 0.73 under various compositions of dry storage cask system

Percutaneous Transhepatic Cholangiography and Drainage is an Effective Rescue Therapy for Biliary Complications in Liver Transplant Recipients Who Fail Endoscopic Retrograde Cholangiopancreatography

BackgroundWe attempted to evaluate both the factors that predispose a patient to biliary complications after liver transplantation and the results of percutaneous transhepatic cholangiography and drainage (PTCD) for the management of those complications.MethodsThis study retrospectively reviewed the cases of 81 patients who received liver transplants at Taipei Veterans General Hospital between February 2003 and June 2008. Biliary complications were diagnosed on the basis of clinical findings, laboratory data, and the results of imaging studies.ResultsA total of 18 patients (22.2%) developed biliary complications, and living donor liver transplantation (LDLT) was a significant risk factor (p = 0.035), compared to cadaveric liver transplantation. Eight patients with biliary complications received PTCD as the first treatment modality and 6 had successful results. An additional 10 patients received endoscopic retrograde cholangiopancreatography (ERCP) initially, but only 2 patients were effectively managed. One patient received conservative treatment after ERCP failure. One patient died from sepsis after ERCP. The remaining 6 patients with failed ERCP were successfully managed with PTCD. The overall mortality rate in these patients with biliary complications was 16.7%. No significant prognostic predictors were identified, including age, sex, biochemical data, and model for end-stage liver disease scores.ConclusionBiochemical markers cannot predict biliary complications preoperatively. LDLT increases the risk of biliary complications. PTCD is an effective rescue therapy when ERCP fails

Study of the River Bed Variation after the Baling Check-Dam Failure

The study provides longitudinal and cross-sectional analysis of 8 pieces topography data collected from 1980 to 2011 and bed material particle size based on three investigations conducted between 2008 and 2012. The mainstream topography data in December 2007 shows that the head-cutting distance was about 3 kilometers after the dam broke. The topography data since 2008 displays that river the channel is stable as well. The topography data shows that the longitudinal section in the tributary had a head-cutting distance of about 3 kilometers after the dam broke, and the river channel still is showing adjustment behavior. The scour-and-fill analysis result of the mainstream cross-section shows that the transverse adjust changed significantly upstream from the dam location from 2006-2008. The particle size of the bed material has shown a trend from coarsening to fining according to different sampling points. Therefore, the river bed is still adjusting continuously. Finally, this study is based on a debris flow and sediment laden flow numerical model. The simulation result is fit for river-bed changes after dam-break.2007年石門水庫上游的巴陵防砂壩潰壩事件，導致上游河床沖刷約20公尺，下游最大淤積約10公尺。本文蒐集巴陵防砂壩1980至2011年潰壩前後8次地形測量資料與2008-2012年共進行三次河床質粒徑調查以分析潰壩對於河床變動及河床質粒徑變化的影響。結果顯示，巴陵壩潰壩3個月後河床已逐漸趨於動態平衡，河床質粒徑整體有粗化再細化的趨勢。最後，本文以適用於土石流及高含砂水流的數值模式進行潰壩事件模擬，並利用河床測量成果進行比較

Joint relationship between renal function and proteinuria on mortality of patients with type 2 diabetes: The Taichung Diabetes Study

Abstract Background Estimated glomerular filtration rate (eGFR) is a powerful predictor of mortality in diabetic patients with limited proteinuria data. In this study, we tested whether concomitant proteinuria increases the risk of mortality among patients with type 2 diabetes. Methods Participants included 6523 patients > 30 years with type 2 diabetes who were enrolled in a management program of a medical center before 2007. Renal function was assessed by eGFR according to the Modification of Diet in Renal Disease Study equation for Chinese. Proteinuria was assessed by urine dipstick. Results A total of 573 patients (8.8%) died over a median follow-up time of 4.91 years (ranging from 0.01 year to 6.42 years). The adjusted expanded cardiovascular disease (CVD)-related mortality rates among patients with proteinuria were more than three folds higher for those with an eGFR of 60 mL/min/1.73 m2 or less compared with those with an eGFR of 90 mL/min/1.73 m2 or greater [hazard ratio, HR, 3.15 (95% confidence interval, CI, 2.0–5.1)]. The magnitude of adjusted HR was smaller in patients without proteinuria [1.98 (95% CI, 1.1–3.7)]. An eGFR of 60 mL/min/1.73 m2 to 89 mL/min/1.73 m2 significantly affected all-cause mortality and mortality from expanded CVD-related causes only in patients with proteinuria. Similarly, proteinuria affected all outcomes only in patients with an eGFR of <60 mL/min/1.73 m2. Conclusion The risks of all-cause mortality, as well as expanded and non-expanded mortality from CVD-related causes associated with proteinuria or an eGFR of 90 mL/min/1.73 m2 or greater are independently increased. Therefore, the use of proteinuria measurements with eGFR increases the precision of risk stratification for mortality.http://deepblue.lib.umich.edu/bitstream/2027.42/112804/1/12933_2012_Article_558.pd

Deploying Image Deblurring across Mobile Devices: A Perspective of Quality and Latency

Recently, image enhancement and restoration have become important applications on mobile devices, such as super-resolution and image deblurring. However, most state-of-the-art networks present extremely high computational complexity. This makes them difficult to be deployed on mobile devices with acceptable latency. Moreover, when deploying to different mobile devices, there is a large latency variation due to the difference and limitation of deep learning accelerators on mobile devices. In this paper, we conduct a search of portable network architectures for better quality-latency trade-off across mobile devices. We further present the effectiveness of widely used network optimizations for image deblurring task. This paper provides comprehensive experiments and comparisons to uncover the in-depth analysis for both latency and image quality. Through all the above works, we demonstrate the successful deployment of image deblurring application on mobile devices with the acceleration of deep learning accelerators. To the best of our knowledge, this is the first paper that addresses all the deployment issues of image deblurring task across mobile devices. This paper provides practical deployment-guidelines, and is adopted by the championship-winning team in NTIRE 2020 Image Deblurring Challenge on Smartphone Track.Comment: CVPR 2020 Workshop on New Trends in Image Restoration and Enhancement (NTIRE

Benchmarking of eight recurrent neural network variants for breath phase and adventitious sound detection on a self-developed open-access lung sound database-HF_Lung_V1

A reliable, remote, and continuous real-time respiratory sound monitor with automated respiratory sound analysis ability is urgently required in many clinical scenarios-such as in monitoring disease progression of coronavirus disease 2019-to replace conventional auscultation with a handheld stethoscope. However, a robust computerized respiratory sound analysis algorithm has not yet been validated in practical applications. In this study, we developed a lung sound database (HF_Lung_V1) comprising 9,765 audio files of lung sounds (duration of 15 s each), 34,095 inhalation labels, 18,349 exhalation labels, 13,883 continuous adventitious sound (CAS) labels (comprising 8,457 wheeze labels, 686 stridor labels, and 4,740 rhonchi labels), and 15,606 discontinuous adventitious sound labels (all crackles). We conducted benchmark tests for long short-term memory (LSTM), gated recurrent unit (GRU), bidirectional LSTM (BiLSTM), bidirectional GRU (BiGRU), convolutional neural network (CNN)-LSTM, CNN-GRU, CNN-BiLSTM, and CNN-BiGRU models for breath phase detection and adventitious sound detection. We also conducted a performance comparison between the LSTM-based and GRU-based models, between unidirectional and bidirectional models, and between models with and without a CNN. The results revealed that these models exhibited adequate performance in lung sound analysis. The GRU-based models outperformed, in terms of F1 scores and areas under the receiver operating characteristic curves, the LSTM-based models in most of the defined tasks. Furthermore, all bidirectional models outperformed their unidirectional counterparts. Finally, the addition of a CNN improved the accuracy of lung sound analysis, especially in the CAS detection tasks.Comment: 48 pages, 8 figures. To be submitte

Acute Kidney Injury Biomarkers for Patients in a Coronary Care Unit: A Prospective Cohort Study

Background: Renal dysfunction is an established predictor of all-cause mortality in intensive care units. This study analyzed the outcomes of coronary care unit (CCU) patients and evaluated several biomarkers of acute kidney injury (AKI), including neutrophil gelatinase-associated lipocalin (NGAL), interleukin-18 (IL-18) and cystatin C (CysC) on the first day of CCU admission. Methodology/Principal Findings: Serum and urinary samples collected from 150 patients in the coronary care unit of a tertiary care university hospital between September 2009 and August 2010 were tested for NGAL, IL-18 and CysC. Prospective demographic, clinical and laboratory data were evaluated as predictors of survival in this patient group. The most common cause of CCU admission was acute myocardial infarction (80%). According to Acute Kidney Injury Network criteria, 28.7 % (43/150) of CCU patients had AKI of varying severity. Cumulative survival rates at 6-month follow-up following hospital discharge differed significantly (p,0.05) between patients with AKI versus those without AKI. For predicting AKI, serum CysC displayed an excellent areas under the receiver operating characteristic curve (AUROC) (0.89560.031, p,0.001). The overall 180-day survival rate was 88.7 % (133/150). Multiple Cox logistic regression hazard analysis revealed that urinary NGAL, serum IL-18, Acute Physiology, Age and Chronic Health Evaluation II (APACHE II) and sodium on CCU admission day one were independent risk factors for 6-month mortality. In terms of 6-month mortality, urinary NGAL had the best discriminatory power, the best Youden index, and the highest overall correctness of prediction