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Science China(Information Sciences) 2024年第2期67卷 20-40页

作者： Peng YANG Laoming ZHANG Haifeng LIU Guiying LI department of Statistics and Data Science Southern University of Science and Technology Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and EngineeringSouthern University of Science and Technology Academy for Advanced Interdisciplinary studies Southern University of Science and Technology Guangdong OPPO Mobile Telecommunications Corp. Ltd Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology

In recent years, various companies have started to shift their data services from traditional data centers to the cloud. One of the major motivations is to save on operational costs with the aid of cloud elasticity. This paper discusses an emerging need from financial services to reduce the incidence of idle servers retaining very few user connections, without disconnecting them from the server side. This paper considers this need as a bi-objective online load balancing problem. A neural network based scalable policy is designed to route user requests to varied numbers of servers for the required elasticity. An evolutionary multi-objective training framework is proposed to optimize the weights of the policy. Not only is the new objective of idleness reduced by over 130% more than traditional industrial solutions, but the original load balancing objective itself is also slightly improved. Extensive simulations with both synthetic and real-world data help reveal the detailed applicability of the proposed method to the emergent problem of reducing idleness in financial services.

关键词： evolutionary reinforcement learning evolutionary multi-objective optimization load balance cloud computing

A Law of Large Numbers Under the Nonlinear Expectation

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Acta Mathematicae Applicatae Sinica 2015年第4期31卷 953-962页

作者： Miao ZHANG Zeng-jing CHEN Qilu Securities Institute for financial studies and department of Mathematics Shandong University

In this paper, we derive a law of large numbers under the nonlinear expectation generated by backward stochastic differential equations driven by G-Brownian motion.

关键词： law of large numbers nonlinear expectation backward stochastic differential equation

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Measures of Relative and Absolute Convergence and Pro-poor Growth with an Illustration based on China(2010–2018)

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China & World Economy 2024年第2期32卷 1-41页

作者： Elena Bárcena-Martin Jacques Silber Yuan Zhang Facultad de Ciencias Económicas y Empresariales Universidad de MálagaSpain department of Economics Bar-Ilan UniversityIsrael China Center for Economic studies Fudan UniversityChina

Income mobility is a key issue for understanding the process of economic growth and distributional *** economists have used the concept of“pro-poor growth”to examine,with individual-level panel data,whether the poor benefit more than the rich from economic growth by tracking the extent of income mobility among different population *** is also literature in macroeconomics on the measurement of *** paper introduces population-weighted relative and absolute indices of mobility,convergence,and pro-poor growth;it also distinguishes between anonymous and nonanonymous approaches to these *** empirical analysis is based on Chinese panel data for the period 2010–*** both absolute and relative terms,income growth in China was greater for individuals with an initially lower income but only for lower income deciles in relative *** was also an overall increase in individual welfare from anonymous and nonanonymous perspectives,which was higher among younger *** welfare of the poor did not increase more than that of the *** results shed light on the evolution of income distribution in China during the past decade's rapid economic growth.

关键词： anonymous and nonanonymous approach convergence exchange and structural mobility pro-poor growth

Dynamic Pricing Strategies Using Artificial Intelligence Algorithm

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Open Journal of Applied Sciences 2024年第8期14卷 1963-1978页

作者： Murat Basal Emel Saraç Kadir Özer Logistics Vocational School Istanbul Gelisim University Istanbul Turkey department of Business Administration Institute of Social Sciences Ostim Technical University Ostim Turkey department of Insurance Faculty of Financial Sciences Ankara Hac Bayram Veli University Ankara Turkey

Pricing strategies can have a huge impact on a company’s success. This paper focuses on the advantages and disadvantages of using artificial intelligence in dynamic pricing strategies. A good understanding of the possible benefits and challenges will help companies to understand the impact of their chosen pricing strategies. AI-driven Dynamic pricing has great opportunities to increase a firm’s profits. Firms can benefit from personalized pricing based on personal behavior and characteristics, as well as cost reduction by increasing efficiency and reducing the need to use manual work and automation. However, AI-driven dynamic rewarding can have a negative impact on customers’ perception of trust, fairness and transparency. Since price discrimination is used, ethical issues such as privacy and equity may arise. Understanding the businesses and customers that determine pricing strategy is so important that one cannot exist without the other. It will provide a comprehensive overview of the main advantages and disadvantages of AI-assisted dynamic pricing strategy. The main objective of this research is to uncover the most notable advantages and disadvantages of implementing AI-enabled dynamic pricing strategies. Future research can extend the understanding of algorithmic pricing through case studies. In this way, new, practical implications can be developed in the future. It is important to investigate how issues related to customers’ trust and feelings of unfairness can be mitigated, for example by price framing.

关键词： Artificial Intelligence Algorithm Dynamic Pricing Strategy

An Improved Enterprise Resource Planning System Using Machine Learning Techniques

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Journal of Software Engineering and Applications 2024年第5期17卷 203-213页

作者： Ahmed Youssri Zakaria Elsayed Abdelbadea Atef Raslan Tarek Ali Mervat Gheith Al-Sayed Khater Essam A. Amin department of Software Engineering Faculty of Graduate Studies for Statistical Research (FGSSR) Cairo University Giza Egypt

Traditional Enterprise Resource Planning (ERP) systems with relational databases take weeks to deliver predictable insights instantly. The most accurate information is provided to companies to make the best decisions through advanced analytics that examine the past and the future and capture information about the present. Integrating machine learning (ML) into financial ERP systems offers several benefits, including increased accuracy, efficiency, and cost savings. Also, ERP systems are crucial in overseeing different aspects of Human Capital Management (HCM) in organizations. The performance of the staff draws the interest of the management. In particular, to guarantee that the proper employees are assigned to the convenient task at the suitable moment, train and qualify them, and build evaluation systems to follow up their performance and an attempt to maintain the potential talents of workers. Also, predicting employee salaries correctly is necessary for the efficient distribution of resources, retaining talent, and ensuring the success of the organization as a whole. Conventional ERP system salary forecasting methods typically use static reports that only show the system’s current state, without analyzing employee data or providing recommendations. We designed and enforced a prototype to define to apply ML algorithms on Oracle EBS data to enhance employee evaluation using real-time data directly from the ERP system. Based on measurements of accuracy, the Random Forest algorithm enhanced the performance of this system. This model offers an accuracy of 90% on the balanced dataset.

关键词： ERP HCM Machine Learning Employee Performance Pythonista Pythoneer

Unscented Kalman filter for a low-cost GNSS/IMU-based mobile mapping application under demanding conditions

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Geodesy and Geodynamics 2024年第2期15卷 166-176页

作者： Mokhamad Nur Cahyadi Tahiyatul Asfihani Hendy Fitrian Suhandri Risa Erfianti department of Geomatics Engineering Institut Teknologi Sepuluh NopemberSurabaya 6011Indonesia Research Center of Marine and Earth Science Technology Directorate of Research and Community ServiceInstitut Teknologi Sepuluh NopemberSurabaya 60111Indonesia department of Mathematics Institut Teknologi Sepuluh NopemberSurabaya 60111Indonesia Centre of studies for Surveying Science&Geomatics Universiti Teknologi Mara(UiTM)Shah Alam 40450Malaysia

For the last two decades,low-cost Global Navigation Satellite System(GNSS)receivers have been used in various *** receivers are mini-size,less expensive than geodetic-grade receivers,and in high *** of these outstanding features,low-cost GNSS receivers are potentially poorer hardwares with internal signal processing,resulting in lower *** typically come with low-cost GNSS antenna that has lower performance than their counterparts,particularly for multipath ***,this research evaluated the low-cost GNSS device performance using a high-rate kinematic *** this purpose,these receivers were assembled with an Inertial Measurement Unit(IMU)sensor,which actively transmited data on acceleration and orientation rate during the *** position and navigation parameter data were obtained from the IMU readings,even without GNSS signals via the U-blox F9R GNSS/IMU device mounted on a *** research was conducted in an area with demanding conditions,such as an open sky area,an urban environment,and a shopping mall basement,to examine the device’s *** data were processed by two approaches:the Single Point Positioning-IMU(SPP/IMU)and the Differential GNSS-IMU(DGNSS/IMU).The Unscented Kalman Filter(UKF)was selected as a filtering algorithm due to its excellent performance in handling nonlinear system *** result showed that integrating GNSS/IMU in SPP processing mode could increase the accuracy in eastward and northward components up to 68.28%and 66.64%.Integration of DGNSS/IMU increased the accuracy in eastward and northward components to 93.02%and 93.03%compared to the positioning of standalone *** addition,the positioning accuracy can be improved by reducing the IMU noise using low-pass and high-pass *** application could still not gain the expected position accuracy under signal outage conditions.

关键词： LoW-cost GNSS GNSS/IMU Single Point Positioning-IMU(SPP/IMU) Differential GNSS-IMU(DGNSS/IMU) Unscented Kalman Filter(UKF) Outageconditions

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Strengthening Active Aging through Older People’s Association and Economic Activity of the Older People in Nepal

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Advances in Aging Research 2024年第2期13卷 15-24页

作者： Hom Nath Chalise James Brightman Central department of Population studies Tribhuvan University Kathmandu Nepal University of Central Florida Orlando Florida USA

Aging is a natural lifelong process ending in death. Many older people are living in poverty. Older people are generally considered dependent on others as they grow older. The purpose of this article is to explore the entrepreneurship activities of Nepalese older adults. Data for this study were collected from the project Help Age International (HAI) implemented in Nepal. Qualitative data observations and interviews were used to collect data. The findings of this study show the formation of the Older People’s Association (OPA) has supported many older people to participate outside the home in various social activities. Moreover, regular deposits through OPAs offer little help. OPAs support older people in their need of financial support to implement minor entrepreneurship. Older people who received support were pleased and were actively involved in their activities and also regularly deposited money in them. Subsequently, older people’s participation in social activities has increased and also helped to lower elderly abuse, loneliness, and depression. Local governments should promote such activities which will help with healthy aging.

关键词： Aging in Nepal Active Aging Older People’s Association Older People Healthy Aging

Unleashing the Power of Multi-Agent Reinforcement Learning for Algorithmic Trading in the Digital financial Frontier and Enterprise Information Systems

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Computers, Materials & Continua 2024年第8期80卷 3123-3138页

作者： Saket Sarin Sunil K.Singh Sudhakar Kumar Shivam Goyal Brij Bhooshan Gupta Wadee Alhalabi Varsha Arya Chandigarh College of Engineering and Technology Chandigarh160019India department of Computer Science and Information Engineering Asia UniversityTaichung413Taiwan Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPune411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India department of Computer Science Immersive Virtual Reality Research GroupKing Abdulaziz UniversityJeddah21589Saudi Arabia department of Business Administration Asia UniversityTaichung413Taiwan department of Electrical and Computer Engineering Lebanese American UniversityBeirut11022801Lebanon UCRD Chandigarh UniversityChandigarh140413India

In the rapidly evolving landscape of today’s digital economy,financial Technology(Fintech)emerges as a trans-formative force,propelled by the dynamic synergy between Artificial Intelligence(AI)and Algorithmic *** in-depth investigation delves into the intricacies of merging Multi-Agent Reinforcement Learning(MARL)and Explainable AI(XAI)within Fintech,aiming to refine Algorithmic Trading *** meticulous examination,we uncover the nuanced interactions of AI-driven agents as they collaborate and compete within the financial realm,employing sophisticated deep learning techniques to enhance the clarity and adaptability of trading *** AI-infused Fintech platforms harness collective intelligence to unearth trends,mitigate risks,and provide tailored financial guidance,fostering benefits for individuals and enterprises navigating the digital *** research holds the potential to revolutionize finance,opening doors to fresh avenues for investment and asset management in the digital ***,our statistical evaluation yields encouraging results,with metrics such as Accuracy=0.85,Precision=0.88,and F1 Score=0.86,reaffirming the efficacy of our approach within Fintech and emphasizing its reliability and innovative prowess.

关键词： Neurodynamic Fintech multi-agent reinforcement learning algorithmic trading digital financial frontier

An Overview of Chemical Constituents, Medicinal Properties, Clinical Trials, and Patents of Twigs of Morus alba(Ramulus Mori)

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World Journal of Traditional Chinese Medicine 2024年第2期10卷 149-158页

作者： Eric Wei Chiang Chan Hung Tuck Chan Siu Kuin Wong department of Food Science and Nutrition Faculty of Applied SciencesUCSI UniversityCherasKuala LumpurMalaysia Secretariat of International Society for Mangrove Ecosystems Faculty of AgricultureUniversity of the RyukyusOkinawaJapan School of Foundation studies Xiamen University MalaysiaSepangSelangorMalaysia

The rich chemical constituents and diverse pharmacological properties of Ramulus Mori(RM) or the twig of Morus alba with evidence supported by clinical trials and patents are reviewed. Known as Sangzhi in Chinese, RM is widely used in traditional Chinese medicine to treat gout, arthritis, and rheumatism. Chemical constituents include flavonoids, benzofurans, alkaloids, stilbenes, chalcones, phenolic acids, and coumarins. Bioactivities of RM include antidiabetic, anti-obesity, anti-inflammatory, antityrosinase, neuroprotective, antioxidant, hepatoprotective, cytoprotective, renoprotective, antihyperuricemic, analgesic, antifungal, DNA protective, anticancer, gastroprotective, cardioprotective, anti-hair aging, anti-arthritic, and antiplatelet aggregation properties. The most active compounds from RM are mulberrin, oxyresveratrol, and mulberroside A. All four clinical trials on RM are focused on the treatment of diabetes. The patents entail using RM extracts as cosmetics for skin whitening and as agents for hypoglycemia. Topics for further research on RM are suggested.

关键词： Clinical trials mulberrin mulberroside A oxyresveratrol patents Sangzhi

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Rhodium-Catalyzed Asymmetric Transfer Hydrogenation of Heterocyclic Diaryl Ketones:Facile Access to Key Intermediate of Baloxavir

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Chinese Journal of Chemistry 2024年第1期42卷 43-47页

作者： Li Wang Renwei Xiao Jingyuan Song Long-Sheng Zheng Qiwei Lang Gen-Qiang Chen Xumu Zhang Shenzhen Key Laboratory of Small Molecule Drug Discovery and Synthesis Department of Chemistryand Medi-PingshanSouthern University of Science and TechnologyShenzhenGuangdong 518000China Academy for Advanced Interdisciplinary studies Southern Universityof Science and TechnologyShenzhenGuangdong 518000China Chemistry and Chemical Engineering Guangdong Laboratory ShantouGuangdong 515031China

Transition metal-catalyzed asymmetric transfer hydrogenation has been proven to be a powerful approach for the synthesis of chiral ***,a highly efficient and enantioselective transfer hydrogenation of dibenzoheptaheterocyclic ketones catalyzed by an arene-tethered TsDPEN-based Rh(ll)catalyst has been successfully developed,and a variety of dibenzoheptaheterocyclic ketones were reduced by a 1/1 mixture of formic acid and DBU(1,8-diazabicyclo[5.4.0]undec-7-ene)with high yields and *** this method,the asymmetric reduction of 7,8-difluorodibenzo[b,e]thiepin-11(6H)-one has been realized,providing the key intermediate of baloxavir marboxil with>99% yield and>99% ee at a substrate/catalyst molar ratio of 1000.

关键词： Asymmetric transfer hydrogenation Baloxavir Chiral alcohol Enantioselectivity Heterocyclic diaryl ketone Rhodium(Ⅱ)