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Quantum Computing and Engineering (QCE), IEEE International Conference on

作者： Yen-Jui Chang Hao-Yuan Chen Ying Chang Lu Lien-Po Yu Chao-Ming Fu Ching-Ray Chang Master Program in Intelligent Computing and Big Data Chung Yuan Christian University Taoyuan City Taiwan Department of Physics National Taiwan University Taipei Taiwan Fujitsu Taiwan Ltd. Taipei Taiwan Department of Computer Science University of London London United Kingdom Institute for Information Industry Taipei Taiwan Fo Guang University Yilan Taiwan Quantum Information Center Chung Yuan Christian University Taoyuan City Taiwan

The study investigates a quantum-inspired approach to image reconstruction using Ising machines and demonstrates its significant improvements over the contrastive divergence method in Restricted Boltzmann Machines tra... 详细信息

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

关键词： Training Quantum computing Image reconstruction

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Prediction of Stock Price and Direction Using Neural Networks: datasets Hybrid Modeling Approach

Prediction of Stock Price and Direction Using Neural Network...

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data analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI), International Conference on

作者： Mohamed Al Aradi Nabil Hewahi Big Data Science & Analytics Master Program Collage of Science Univestity of Bahain Sakhir Kingdom of Bahrain Collage of Information Technology Univestity of Bahain Sakhir Kingdom of Bahrain

ISBN: (数字)9781728196756

ISBN: (纸本)9781728196763

Stock prices prediction is one of the most daunting tasks to achieve for day traders, investors, and data scientists. They are complex functions of a wide array of contributing factors that affects the movement dynamics. Politics, social outlook, the company's sales performance, and socio-economic factors all have an influence of how the stock is perceived globally and thus affecting the price movement based on the supply/demand balance. In this work a Framework is proposed to predict the price and movement direction by using multiple datasets that includes news sentiment, social sentiment, company earnings announcement, and technical indicators. A case study was applied on the Apple Inc. stock using Long short-term Memory Neural Networks (LSTM) and Deep Neural Networks (DNN). Results showed superiority of the LSTM model in both predicting stock value [ 75.4 MSE, +-2.52 PE] and the direction with [70.1% classification accuracy] over the DNN model which suffered from prediction lag and dependency on trend indicators achieving [53.1%] in predicting the direction of the stock.

关键词： Predictive models Machine learning Companies Neural networks Market research data models Recurrent neural networks

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APPLICATION OF THE DIGITAL ANNEALER UNIT IN OPTIMIZING CHEMICAL REACTION CONDITIONS FOR ENHANCED PRODUCTION YIELDS

arXiv

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arXiv 2024年

作者： Li, Shih-Cheng Wang, Pei-Hwa Su, Jheng-Wei Chiang, Wei-Yin Huang, Shih-Hsien Lin, Yen-Chu Ou, Chia-Ho Chen, Chih-Yu Insilico Medicine Taiwan Ltd. Taipei City110208 Taiwan Department of Chemical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Quantum Information Center Chung Yuan Christian University Taoyuan City320314 Taiwan Master Program in Intelligent Computing and Big Data Chung Yuan Christian University Taoyuan City320314 Taiwan Department of Computer Science and Information Engineering National Pingtung University Pingtung City900392 Taiwan

Finding appropriate reaction conditions that yield high product rates in chemical synthesis is crucial for the chemical and pharmaceutical industries. However, due to the vast chemical space, conducting experiments for each possible reaction condition is impractical. Consequently, models such as QSAR (Quantitative Structure-Activity Relationship) or ML (Machine Learning) have been developed to predict the outcomes of reactions and illustrate how reaction conditions affect product yield. Despite these advancements, inferring all possible combinations remains computationally prohibitive when using a conventional CPU. In this work, we explore using a Digital Annealing Unit (DAU) to tackle these large-scale optimization problems more efficiently by solving Quadratic Unconstrained Binary Optimization (QUBO). Two types of QUBO models are constructed in this work: one using quantum annealing and the other using ML. Both models are built and tested on four high-throughput experimentation (HTE) datasets and selected Reaxys datasets. Our results suggest that the performance of models is comparable to classical ML methods (i.e., Random Forest and Multilayer Perceptron (MLP)), while the inference time of our models requires only seconds with a DAU. Additionally, in campaigns involving active learning and autonomous design of reaction conditions to achieve higher reaction yield, our model demonstrates significant improvements by adding new data, showing promise of adopting our method in the iterative nature of such problem settings. Our method can also accelerate the screening of billions of reaction conditions, achieving speeds millions of times faster than traditional computing units in identifying superior conditions. Therefore, leveraging the DAU with our developed QUBO models has the potential to be a valuable tool for innovative chemical synthesis. Copyright © 2024, The Authors. All rights reserved.

关键词： Machine learning

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programming Variational Quantum Circuits with Quantum-Train Agent

Programming Variational Quantum Circuits with Quantum-Train ...

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Quantum Communications, Networking, and Computing (QCNC), International Conference on

作者： Chen-Yu Liu Samuel Yen-Chi Chen Kuan-Cheng Chen Wei-Jia Huang Yen-Jui Chang Graduate Institute of Applied Physics National Taiwan University Taipei Taiwan Hon Hai (Foxconn) Research Institute Taipei Taiwan Wells Fargo New York NY USA Department of Electrical and Electronic Engineering Imperial College London London UK Centre for Quantum Engineering Science and Technology (QuEST) Imperial College London London UK Quantum Information Center Chung Yuan Christian University Taoyuan City Taiwan Master Program in Intelligent Computing and Big Data Chung Yuan Christian University Taoyuan City Taiwan

ISBN: (数字)9798331531591

ISBN: (纸本)9798331531607

This study introduces the Quantum-Train Quantum Fast Weight programmer (QT-QFWP) framework, enabling efficient and scalable programming of variational quantum circuits (VQCs) through quantum-driven parameter updates for the classical slow programmer controlling the fast programmer VQC. By optimizing quantum and classical parameter management, QT-QFWP significantly reduces parameters (by 70–90%) compared to Quantum Long Short-Term Memory (QLSTM) and Quantum Fast Weight programmer (QFWP) while maintaining accuracy. Benchmarking on time-series tasks—including Damped Simple Harmonic Motion (SHM), NARMA5, and Simulated Gravitational Waves (GW)—demonstrates superior efficiency and predictive accuracy. QT-QFWP is particularly advantageous for near-term quantum systems, addressing qubit and gate fidelity constraints, enhancing VQC deployment in time-sensitive applications, and expanding quantum computing’s role in machine learning.

关键词： Quantum system Accuracy Computational modeling Qubit Neural networks programming Predictive models Quantum circuit Physics Long short term memory

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Efficient Bitcoin Address Classification Using Quantum-Inspired Feature Selection

arXiv

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arXiv 2024年

作者： Sie, Ming-Fong Chang, Yen-Jui Lin, Chien-Lung Chang, Ching-Ray Liao, Shih-Wei Department of Computer Science and Information Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Rd. Taipei City10617 Taiwan Master Program in Intelligent Computing and Big Data Chung Yuan Christian University No. 499 Xingzhong N. Rd. Taoyuan City320317 Taiwan Department of Physics National Taiwan University Taiwan Quantum Information Center Chung Yuan Christian University No. 499 Xingzhong N. Rd. Taoyuan City320317 Taiwan

Over 900 million Bitcoin transactions have been recorded, posing considerable challenges for machine learning regarding computation time and maintaining prediction accuracy. We propose an innovative approach using quantum-inspired algorithms implemented with Simulated Annealing and Quantum Annealing to address the challenge of local minima in solution spaces. This method efficiently identifies key features linked to mixer addresses, significantly reducing model training time. By categorizing Bitcoin addresses into six classes—exchanges, faucets, gambling, marketplaces, mixers, and mining pools—and applying supervised learning methods, our results demonstrate that feature selection with SA reduced training time by 30.3% compared to using all features in a random forest model while maintaining a 91% F1-score for mixer addresses. This highlights the potential of quantum-inspired algorithms to swiftly and accurately identify high-risk Bitcoin addresses based on transaction features. © 2024, CC BY.

关键词： Simulated annealing

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Projected Time for the Elimination of Cervical Cancer Under Various Intervention Scenarios: Age-Period-Cohort Macrosimulation Study

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JMIR Public Health and Surveillance 2024年 10卷 e46360页

作者： Chen, Yi-Chu Chen, Yun-Yuan Su, Shih-Yung Jhuang, Jing-Rong Chiang, Chun-Ju Yang, Ya-Wen Lin, Li-Ju Wu, Chao-Chun Lee, Wen-Chung Institute of Epidemiology and Preventive Medicine College of Public Health National Taiwan University Taipei Taiwan Head Office Taiwan Blood Services Foundation Taipei Taiwan Master Program in Statistics National Taiwan University Taipei Taiwan Institute of Statistical Science Academia Sinica Taipei Taiwan Taiwan Cancer Registry Taipei city Taiwan Health Promotion Administration Ministry of Health and Welfare Taipei Taiwan Institute of Health Data Analytics College of Public Health National Taiwan University Taipei Taiwan

BACKGROUND: The World Health Organization aims for the global elimination of cervical cancer, necessitating modeling studies to forecast long-term outcomes. OBJECTIVE: This paper introduces a macrosimulation framework using age-period-cohort modeling and population attributable fractions to predict the timeline for eliminating cervical cancer in Taiwan. METHODS: data for cervical cancer cases from 1997 to 2016 were obtained from the Taiwan Cancer Registry. Future incidence rates under the current approach and various intervention strategies, such as scaled-up screening (cytology based or human papillomavirus [HPV] based) and HPV vaccination, were projected. RESULTS: Our projections indicate that Taiwan could eliminate cervical cancer by 2050 with either 70% compliance in cytology-based or HPV-based screening or 90% HPV vaccination coverage. The years projected for elimination are 2047 and 2035 for cytology-based and HPV-based screening, respectively;2050 for vaccination alone;and 2038 and 2033 for combined screening and vaccination approaches. CONCLUSIONS: The age-period-cohort macrosimulation framework offers a valuable policy analysis tool for cervical cancer control. Our findings can inform strategies in other high-incidence countries, serving as a benchmark for global efforts to eliminate the disease. ©Yi-Chu Chen, Yun-Yuan Chen, Shih-Yung Su, Jing-Rong Jhuang, Chun-Ju Chiang, Ya-Wen Yang, Li-Ju Lin, Chao-Chun Wu, Wen-Chung Lee. Originally published in JMIR Public Health and Surveillance (https://***), 18.04.2024.

关键词： Age-period-cohort model Cancer screening Cervical cancer Cervical screening HPV Human papillomavirus Intervention Macrosimulation Population attributable fraction Public health intervention Women

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Trends and sex-specific incidence of upper urinary tract cancer in Taiwan: A birth cohort study

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Cancer medicine 2023年第14期12卷 15350-15357页

作者： Yu-Hsuan Chang Wan-Lun Hsu Yu-Kwang Lee Chun-Ju Chiang Ya-Wen Yang San-Lin You Yong-Chen Chen Tai-Shuan Lai School of Medicine Fu-Jen Catholic University New Taipei City Taiwan. Data Science Center College of Medicine Fu-Jen Catholic University New Taipei City Taiwan. Master Program of Big Data Analysis in Biomedicine College of Medicine Fu-Jen Catholic University New Taipei City Taiwan. Department of Surgery Division of General Surgery National Taiwan University Hospital Taipei Taiwan. Graduate Institute of Epidemiology and Preventive Medicine College of Public Health National Taiwan University Taipei Taiwan. Department of Internal Medicine National Taiwan University Hospital Taipei Taiwan. Department of Internal Medicine College of Medicine National Taiwan University Taipei Taiwan.

BACKGROUND:Taiwan has one of the highest incidences of upper tract urothelial cancer (UTUC) worldwide, especially in women; however, no nationwide, long-term follow-up study has evaluated this. METHODS:We investigated the incidence of UTUC in Taiwan using data from the national population-based Taiwan Cancer Registry database (1985-2019). We divided the birth cohort into nine 5-year age groups and calculated the age-specific incidence for these groups according to the corresponding birth years. RESULTS:The average annual percent change in the incidence of renal pelvis cancer from 1985 to 2019 showed sex-specific differences, with 3.5% and 5.3% increases in the incidences in men and women, respectively. The age-specific incidence rate for renal pelvis cancer among women showed a gradual increase in the group with older women as well as an increase over time in each age group. The results of a birth cohort analysis revealed that younger cohorts had higher incidence rates of renal pelvis cancer than older cohorts did. CONCLUSION:We demonstrated that the incidence of UTUC is unusually high among older Taiwanese women and that younger cohorts have a high risk of UTUC than older cohorts.

关键词： age period cohort incidence sex upper tract urothelial cancer

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Morphological and metabolic asymmetries of the thalamic subregions in temporal lobe epilepsy predict cognitive functions

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Scientific Reports 2023年第1期13卷 1-9页

作者： Tung, Hsin Tsai, Shih-Chuan Huang, Pu-Rong Hsieh, Peiyuan F. Lin, Yi-Ching Peng, Syu-Jyun Department of Post-Baccalaureate Medicine College of Medicine National Chung Hsing University Taichung Taiwan Center of Faculty Development Taichung Veterans General Hospital Taichung Taiwan Neurological Institute Taichung Veterans General Hospital Taichung Taiwan Institute of Clinical Medicine National Yang Ming Chiao Tung University Taipei Taiwan Department of Nuclear Medicine Taichung Veterans General Hospital Taichung Taiwan Department of Medical Imaging and Radiological Technology Institute of Radiological Science Central Taiwan University of Science and Technology Taichung Taiwan Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Medical University No.250 Wuxing St. Xinyi Dist. Taipei City 110 Taiwan Clinical Big Data Research Center Taipei Medical University Hospital Taipei Medical University Taipei Taiwan

Both morphological and metabolic imaging were used to determine how asymmetrical changes of thalamic subregions are involved in cognition in temporal lobe epilepsy (TLE). We retrospectively recruited 24 left-TLE and 15 right-TLE patients. Six thalamic subnuclei were segmented by magnetic resonance imaging, and then co-registered onto Positron emission tomography images. We calculated the asymmetrical indexes of the volumes and normalized standard uptake value ratio (SUVR) of the entire and individual thalamic subnuclei. The SUVR of ipsilateral subnuclei were extensively and prominently decreased compared with the volume loss. The posterior and medial subnuclei had persistently lower SUVR in both TLE cases. Processing speed is the cognitive function most related to the metabolic asymmetry. It negatively correlated with the metabolic asymmetrical indexes of subregions in left-TLE, while positively correlated with the subnuclei volume asymmetrical indexes in right-TLE. Epilepsy duration negatively correlated with the volume asymmetry of most thalamic subregions in left-TLE and the SUVR asymmetry of ventral and intralaminar subnuclei in right-TLE. Preserved metabolic activity of contralateral thalamic subregions is the key to maintain the processing speed in both TLEs. R-TLE had relatively preserved volume of the ipsilateral thalamic volume, while L-TLE had relatively decline of volume and metabolism in posterior subnucleus. © 2023, The Author(s).

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Surveillance of Multidrug-Resistant Bacterial Infections in Non-Adult Patients-Zhejiang Province,China,2014-2019

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China CDC weekly 2021年第47期3卷 1005-1013,I0004页

作者： Yuchen Wu Shi Chen Jiaping Li Chang Cai Hanyu Wang Mingming Zhou Junmin Cao Qiang Wang Shenghai Wu Shibiao Ding Xiaofei Zhao Long Sun Qingfeng Hu Hongwei Zhou Xiang Qian Qing Yang Sheng Chen Rong Zhang Department of Clinical Laboratory the Second Affiliated Hospital of Zhejiang UniversityZhejiang UniversityHangzhouZhejiangChina Clinical Microbiology Laboratory the Third People’s Hospital of HangzhouHangzhouZhejiangChina China Australia Joint Laboratory for Animal Health Big Data Analytics College of Animal Science and TechnologyZhejiang Agricultural and Forestry UniversityHangzhouZhejiangChina Master of Science New Jersey Institute of TechnologyNewarkNew Jerseythe United States of America National Clinical Research Center for Child Health the Children’s HospitalZhejiang University School of MedicineHangzhouZhejiangChina Department of Hospital Infection Control Zhejiang Provincial Hospital of Traditional Chinese MedicineHangzhouZhejiangChina Department of Clinical Laboratory the Second Affiliated Hospital of Zhejiang Chinese Medical UniversityHangzhouZhejiangChina Department of Laboratory Medicine the First Affiliated People’s Hospital of HangzhouZhejiang University School of MedicineHangzhouZhejiangChina Hangzhou Red Cross Hospital HangzhouZhejiangChina Department of Clinical Laboratory the Affiliated Hospital of Hangzhou Normal UniversityHangzhouZhejiangChina Department of Clinical Laboratory Hangzhou Women’s HospitalHangzhou Maternity and Child Health Care HospitalHangzhouZhejiangChina Clinical Diagnostic Laboratory People’s Hospital of ZhejiangHangzhouZhejiangChina Department of Clinical Laboratory Hangzhou Hospital of Traditional Chinese MedicineHangzhouZhejiangChina The First Affiliated Hospital of Zhejiang University Zhejiang UniversityHangzhouZhejiangChina Department of Infectious Diseases and Public Health Jockey Club College of Veterinary Medicine and Life SciencesCity University of Hong KongHong Kong Special Administrative RegionChina

ABSTRACT Introduction:Antimicrobial resistance has become a major public health threat *** prevalence of multidrug-resistant(MDR)bacterial infections increased substantially among inpatients under 18 years of age in recent *** Zhejiang Province,China,the trends of drug-resistance in non-adult patients from 2014 to 2019 were monitored,aiming to determine the variation patterns and epidemiological features of MDR strains.

关键词： globally threat Zhejiang

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Risks of liver cirrhosis,hepatocellular carcinoma,hepatic-related complications,and mortality in patients with type 2 diabetes in Taiwan

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World Journal of Diabetes 2025年第5期16卷 202-215页

作者： Hua-Fen Chen Yung-Yueh Chang Peter Chen Xiao-Han Shen Chin-Huan Chang Wan-Lun Hsu Department of Endocrinology Far Eastern Memorial HospitalNew Taipei City 220TaiwanChina School of Medicine College of MedicineFu Jen Catholic UniversityNew Taipei City 242TaiwanChina Department of Public Health College of MedicineFu Jen Catholic UniversityNew Taipei City 242TaiwanChina Institute of Epidemiology and Preventive Medicine College of Public HealthNational Taiwan UniversityTaipei City 100TaiwanChina Department of Gastroenterology Choninn HospitalChoninn Medical GroupNew Taipei City 220TaiwanChina Master Program of Big Data in Medical Healthcare Industry College of MedicineFu Jen Catholic UniversityNew Taipei City 242TaiwanChina Data Science Center Fu Jen Catholic UniversityNew Taipei City 242TaiwanChina

BACKGROUND Hepatitis B and C and alcoholic liver disease are the principal causes of hepaticrelated morbidity and ***,evidence of the associations between diabetes without the above risk factors and hepatic-related study endpoints is not well *** addition,the effects of associated metabolic dysfunction and exercise on hepatic outcomes are still not *** To investigate the incidence and relative hazards of cirrhosis of the liver,hepato cellular carcinoma(HCC),hepatic-related complications and mortality in patients with type 2 diabetes(T2D)who were nonalcoholic and serologically negative for hepatitis B and C in *** A total of 33184 T2D patients and 648746 nondiabetic subjects selected from Taiwan’s adult preventive health care service were linked to various National Health Insurance databases,cancer registry,and death registry to identify cirrhosis of the liver,HCC,hepatic-related complications,and *** Poisson assumption and Cox proportional hazard regression model were used to estimate the incidences and relative hazards of all hepatic-related study endpoints,*** also compared the risk of hepatic outcomes stratified by age,sex,associated metabolic dysfunctions,and regular exercise between T2D patients and nondiabetic *** Compared with nondiabetic subjects,T2D patients had a significantly greater incidence(6.32 vs 17.20 per 10000 person-years)and greater risk of cirrhosis of the liver[adjusted hazard ratio(aHR)1.45;95%CI:1.30-1.62].The aHRs for HCC,hepatic complications,and mortality were 1.81,1.87,and 2.08,*** older age,male sex,obesity,hypertension,and dyslipidemia further increased the risks of all hepatic-related study endpoints,and regular exercise decreased the risk,irrespective of diabetes *** Patients with T2D are at increased risk of cirrhosis of the liver,HCC,hepatic-related complications,and mortality,and associated metabolic dysfunctions provide additional

关键词： Type 2 diabetes mellitus Liver cirrhosis Hepatocellular carcinoma Hepatic-related complications Mortality Metabolic dysfunction-associated steatotic liver disease Metabolic dysfunction-associated steatohepatitis

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