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Churn Prediction in Financial Risk Management using Deep Learning Techniques

Churn Prediction in Financial Risk Management using Deep Lea...

Advanced Technologies in Intelligent Control, Environment, Computing & Communication engineering (ICATIECE), International Conference on

作者： V Sunil Kumar Sowmyashree S Piyush Kumar Pareek Ashish Khanna Victor Hugo Costa de Albuquerque Deepak Gupta Department of Artificial Intelligence & Machine Learning Nitte Meenakshi Institute of Technology Bengaluru Computer Science & Engineering East West Institute of Technology Bengaluru Graduate Program in Telecommunication Engineering Federal Institute of Education Science and Technology of Cearά Fortaleza Brazil CSE dept Maharaja Agrasen Institute of Technology GGSIPU Department of Teleinformatics Engineering Federal University of Cearά Brazil

ISBN: (纸本)9781665493970

It is essential to develop an efficient Client Relationship Model in order to make use of the estimations about customer turnover (CRM). Finding and breaking down the facts surrounding the business information understanding is necessary for client produce prediction, which should be made possible effectively by altering the strategies used for business insight. The tools that are provided by company insight allow for the historical, current, and prospective perspectives of business activity to be anticipated and dissected. It is possible to deal with it in an efficient way by providing the information mining approaches that choose the data from the created informative index that is the most helpful. Fundamental leadership should be possible to achieve in a fruitful way if one has this information. The actions that consumers have taken in the recent past are going to be analyzed, and an accurate forecast is going to be formed about those customers who are likely going to get unhappy in the near future based on the results of that prediction. The problem is that deciding on a certain period to investigate the client's activities and also establishing on a specific day and age for each of the clients won't be appropriate6. This is due to the fact that the problem is caused by the fact that deciding on a certain period to investigate the client's activities will take too long. The challenge lies just in this aspect. How to decide on a certain amount of time to spend researching the activities of the customer. For instance, when planning a model, 100 customers are used, 70 of those customers are considered “active,” which indicates that they are still conducting business with the organisation, and the remaining 30 customers are considered “agitate,” which indicates that they have severed their ties with the organisation. The primary purpose of the work that has been suggested is to carry out exploratory research and management as a multicriteria basic leadership issue, a

关键词： Leadership Roads Companies Predictive models Media Planning Data mining

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PPDONet: Deep Operator Networks for Fast Prediction of Steady-State Solutions in Disk-Planet Systems

arXiv

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arXiv 2023年

作者： Mao, Shunyuan Dong, Ruobing Lu, Lu Yi, Kwang Moo Wang, Sifan Perdikaris, Paris Department of Physics and Astronomy University of Victoria VictoriaBCV8P 5C2 Canada Department of Chemical and Biomolecular Engineering University of Pennsylvania PhiladelphiaPA19104 United States Department of Computer Science University of British Columbia VancouverBCV6T 1Z4 Canada Graduate Group in Applied Mathematics and Computational Science University of Pennsylvania PhiladelphiaPA19104 United States Department of Mechanical Engineering and Applied Mechanics University of Pennsylvania PhiladelphiaPA19104 United States

We develop a tool, which we name Protoplanetary Disk Operator Network (PPDONet), that can predict the solution of disk-planet interactions in protoplanetary disks in real-time. We base our tool on Deep Operator Networks (DeepONets), a class of neural networks capable of learning non-linear operators to represent deterministic and stochastic differential equations. With PPDONet we map three scalar parameters in a disk-planet system - the Shakura & Sunyaev viscosity α, the disk aspect ratio h0, and the planet-star mass ratio q - to steady-state solutions of the disk surface density, radial velocity, and azimuthal velocity. We demonstrate the accuracy of the PPDONet solutions using a comprehensive set of tests. Our tool is able to predict the outcome of disk-planet interaction for one system in less than a second on a laptop. A public implementation of PPDONet is available at https://***/smao-astro/PPDONet. Copyright © 2023, The Authors. All rights reserved.

关键词： Open source software

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Funneling of Lattice Vibrations Through Topological Phathways in Mid-Infrared Metasurfaces

Funneling of Lattice Vibrations Through Topological Phathway...

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CLEO: science and Innovations, S and I 2022

作者： Guddala, S. Komissarenko, F. Kiriushechkina, S. Vakulenko, A. Li, M. Menon, V.M. Alù, A. Khanikaev, A.B. Department of Electrical Engineering City College of the City University of New York New YorkNY10031 United States Department of Physics City College of New York New YorkNY10031 United States Physics Program Graduate Center of the City University of New York New YorkNY10016 United States Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States

We demonstrate novel hybrid states of strongly-coupled photon and lattice vibrations in hexagonal boron nitride (hBN) integrated with mid-infrared metasurface and show their unconventional helical nature and resilient... 详细信息

ISBN: (纸本)9781557528209

关键词： Infrared devices

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Discovering an aid policy to minimize student evasion using offline reinforcement learning

arXiv

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arXiv 2021年

作者： De Lima, Leandro M. Krohling, Renato A. Graduate Program in Computer Science PPGI Federal University of Espirito Santo UFES Vitória Brazil Graduate Program in Computer Science PPGI Production Engineering Department LABCIN Federal University of Espirito Santo UFES Vitória Brazil

High dropout rates in tertiary education expose a lack of efficiency that causes frustration of expectations and financial waste. Predicting students at risk is not enough to avoid student dropout. Usually, an appropriate aid action must be discovered and applied in the proper time for each student. To tackle this sequential decision-making problem, we propose a decision support method to the selection of aid actions for students using offline reinforcement learning to support decision-makers effectively avoid student dropout. Additionally, a discretization of student's state space applying two different clustering methods is evaluated. Our experiments using logged data of real students shows, through off-policy evaluation, that the method should achieve roughly 1.0 to 1.5 times as much cumulative reward as the logged policy. So, it is feasible to help decision-makers apply appropriate aid actions and, possibly, reduce student dropout. © 2021, CC BY.

关键词： Students

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Special issue on genome wide association study

引用

Quantitative Biology 2021年第2期9卷 105-106页

作者： Lin Hou Qiongshi Lu Can Yang Hongyu Zhao Center for Statistical Science Department of Industrial EngineeringMOE Key Laboratory of BioinformaticsSchool of Life SciencesTsinghua UniversityBeijing 100084China Department of Biostatistics and Medical Informatics Department of StatisticsCenter for Demography of Health and AgingUniversity of Wisconsin-MadisonWl 53726USA Department of Mathematics the Hong Kong University of Science and TechnologyHong KongChina Department of Biostatistics Yale School of Public HealthNew HavenCT 06510USA Department of Genetics Yale UniversityNew HavenCT 06510USA Program of Computational Biology and Bioinformatics Yale UniversityNew HavenCT 06510USA

Since the first success of genome wide association study(GWAS)was reported in 2005 by Hoh and colleagues on the identification of a major gene for age related macular degeneration,many thousands of published studies have reported reproducible association signals between hundreds of thousands of genetic variants and thousands of traits and diseases in the past 16 *** is a growing number of biobanks with up to one million participants developed across the world to facilitate genetic studies of complex traits through ***,many consortium projects have been initiated to collect diverse types of data that have proved very valuable for integrated analysis of GWAS *** rich data present both great opportunities and challenges to scientists on data management,computation,analysis,integration,and *** special issue of Quantitative Biology collects nine papers that cover major progresses,challenges,and future directions for GWAS analysis.

关键词： hundreds GWAS initiated

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Microscopic picture of paraelectric perovskites from structural prototypes

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Physical Review Research 2022年第1期4卷 L012042-L012042页

作者： Michele Kotiuga Samed Halilov Boris Kozinsky Marco Fornari Nicola Marzari Giovanni Pizzi Theory and Simulation of Materials (THEOS) National Centre for Computational Design and Discovery of Novel Materials (MARVEL) École Polytechnique Fédérale de Lausanne CH-1015 Lausanne Switzerland Designed Material Technologies LLC P.O. Box 14548 Richmond Virginia 23221-9998 USA John A. Paulson School of Engineering and Applied Sciences Harvard University 29 Oxford Street Cambridge Massachusetts 02138 USA Robert Bosch LLC Research and Technology Center Cambridge Massachusetts 02139 USA Department of Physics and Science of Advanced Materials Program Central Michigan University Mt. Pleasant Michigan 48859 USA

We highlight with first-principles molecular dynamics the persistence of intrinsic 〈111〉 Ti off-centerings for BaTiO3 in its cubic paraelectric phase. Intriguingly, these are inconsistent with the Pm3¯m space group often used to atomistically model this phase using density-functional theory or similar methods. Therefore, we deploy a systematic symmetry analysis to construct representative structural models in the form of supercells that satisfy a desired point symmetry but are built from the combination of lower-symmetry primitive cells. We define as structural prototypes the smallest of these that are both energetically and dynamically stable. Remarkably, two 40-atom prototypes can be identified for paraelectric BaTiO3; these are also common to many other ABO3 perovskites. These prototypes can offer structural models of paraelectric phases that can be used for the computational engineering of functional materials. Last, we show that the emergence of B-cation off-centerings and the primitive-cell phonon instabilities is controlled by the equilibrium volume, in turn, dictated by the filler A cation.

关键词： Crystal symmetry Ferroelectricity Structural order parameter Paraelectrics

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Speech AI for All: Promoting Accessibility, Fairness, Inclusivity, and Equity

Speech AI for All: Promoting Accessibility, Fairness, Inclus...

引用

2025 CHI Conference on Human Factors in Computing Systems, CHI EA 2025

作者： Wu, Shaomei Wenzel, Kimi Li, Jingjin Li, Qisheng Pradhan, Alisha Kushalnagar, Raja Lea, Colin Koenecke, Allison Vogler, Christian Hasegawa-Johnson, Mark Su, Norman Makoto Ratner, Nan Bernstein *** Mountain ViewCA United States Human-Computer Interaction Institute Carnegie Mellon University PittsburghPA United States *** SeattleWA United States Department of Informatics Ying Wu College of Computing New Jersey Institute of Technology NewarkNJ United States Gallaudet University WashingtonDC United States Apple CupertinoCA United States Cornell University IthacaNY United States Technology Access Program Gallaudet University WashingtonDC United States The Grainger College of Engineering University of Illinois Urbana-Champaign Urbana-ChampaignIL United States Department of Computational Media University of California Santa Cruz Santa CruzCA United States Department of Hearing and Speech Sciences University of Maryland College Park College ParkMD United States Neuroscience and Cognitive Science University of Maryland College Park College ParkMD United States

ISBN: (纸本)9798400713958

Trained and optimized for typical and fluent speech, speech AI works poorly for people with speech diversities, often interrupting them and misinterpreting their speech. The increasing deployment of speech AI in automated phone menus, AI-conducted job interviews, and everyday devices poses tangible risks to people with speech diversities. To mitigate these risks, this workshop aims to build a multidisciplinary coalition and set the research agenda for fair and accessible speech AI. Bringing together a broad group of academics and practitioners with diverse perspectives, including HCI, AI, and other relevant fields such as disability studies, speech language pathology, and law, this workshop will establish a shared understanding of the technical challenges for fair and accessible speech AI, as well as its ramifications in design, user experience, policy, and society. In addition, the workshop will invite and highlight first-person accounts from people with speech diversities, facilitating direct dialogues and collaboration between speech AI developers and the impacted communities. The key outcomes of this workshop include a summary paper that synthesizes our learnings and outlines the roadmap for improving speech AI for people with speech diversities, as well as a community of scholars, practitioners, activists, and policy makers interested in driving progress in this domain. © 2025 Copyright held by the owner/author(s).

关键词： Speech enhancement

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Enabling AI-Generated Content (AIGC) Services in Wireless Edge Networks

arXiv

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arXiv 2023年

作者： Du, Hongyang Li, Zonghang Niyato, Dusit Kang, Jiawen Xiong, Zehui Shen, Xuemin Kim, Dong In The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Information and Communication Engineering University of Electronic Sciences and Technology of China Chengdu China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering University of Waterloo Canada The Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

Artificial Intelligence-Generated Content (AIGC) refers to the use of AI to automate the information creation process while fulfilling the personalized requirements of users. However, due to the instability of AIGC models, e.g., the stochastic nature of diffusion models, the quality and accuracy of the generated content can vary significantly. In wireless edge networks, the transmission of incorrectly generated content may unnecessarily consume network resources. Thus, a dynamic AIGC service provider (ASP) selection scheme is required to enable users to connect to the most suited ASP, improving the users’ satisfaction and quality of generated content. In this article, we first review the AIGC techniques and their applications in wireless networks. We then present the AIGC-as-a-service (AaaS) concept and discuss the challenges in deploying AaaS at the edge networks. Yet, it is essential to have performance metrics to evaluate the accuracy of AIGC services. Thus, we introduce several image-based perceived quality evaluation metrics. Then, we propose a general and effective model to illustrate the relationship between computational resources and user-perceived quality evaluation metrics. To achieve efficient AaaS and maximize the quality of generated content in wireless edge networks, we propose a deep reinforcement learning-enabled algorithm for the optimal ASP selection. Simulation results show that the proposed algorithm can provide a higher quality of generated content to users and achieve fewer crashed tasks by comparing with four benchmarks, i.e., overloading-avoidance, random, round-robin policies, and the upper-bound schemes. © 2023, CC BY.

关键词： Reinforcement learning

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Isolation of 24-homoscalarane sesterterpenoids from a sponge of the genus Lendenfeldia

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Phytochemistry Letters 2024年 61卷 177-181页

作者： Zheng, Li-Guo Chen, You-Yan Liaw, Chia-Ching Lin, Yu-Chi Chien, Su-Ying Lo, Yi-Hao Tsai, Yu-Chi Hu, Hao-Chun Chen, You-Ying Hwang, Tsong-Long Ou, Tzu-Ming Sung, Ping-Jyun Doctoral Degree Program in Marine Biotechnology National Sun Yat-sen University Kaohsiung 804201 Taiwan National Museum of Marine Biology and Aquarium Pingtung 944401 Taiwan School of Traditional Chinese Medicine College of Medicine Chang Gung University Taoyuan 333323 Taiwan Division of Chinese Materia Medica Development National Research Institute of Chinese Medicine Ministry of Health and Welfare Taipei 112304 Taiwan Department of Biochemical Science and Technology National Chiayi University Chiayi 600355 Taiwan Instrumentation Center National Taiwan University Taipei 106319 Taiwan Department of Family Medicine Zuoying Armed Forces General Hospital Kaohsiung 813204 Taiwan Shu-Zen Junior College of Medicine and Management Kaohsiung 821004 Taiwan Institute of Medical Science and Technology National Sun Yat-sen University Kaohsiung 804201 Taiwan School of Chinese Medicine College of Chinese Medicine China Medical University Taichung 404333 Taiwan Graduate Institute of Natural Products College of Medicine Chang Gung University Taoyuan 333323 Taiwan Research Center for Chinese Herbal Medicine College of Human Ecology Chang Gung University of Science and Technology Taoyuan 333324 Taiwan Graduate Institute of Health Industry Technology College of Human Ecology Chang Gung University of Science and Technology Taoyuan 333324 Taiwan Department of Anesthesiology Chang Gung Memorial Hospital Taoyuan 333423 Taiwan Department of Chemical Engineering Ming Chi University of Technology New Taipei City 243303 Taiwan Division of Gastroenterology Department of Internal Medicine Kaohsiung Armed Forces General Hospital Kaohsiung 802301 Taiwan Department of Marine Biotechnology and Resources National Sun Yat-sen University Kaohsiung 804201 Taiwan Chinese Medicine Research and Development Center China Medical University Hospital Taichung 404394 Taiwan Graduate Institute of Natural Products Kaohsiung Medical University Kaohsiung 807378 Taiwan Program in Ph

The chemical screening of an algae-containing marine sponge identified as Lendenfeldia species has isolated two 24-homoscalarane sesterterpenoids, including a known compound, felixin A (1) and a new analogue, lendenfeldarane V (2). The structure of 1, obtained in a previous study, was cited for the first time in this study via single-crystal X-ray diffraction analysis. The structure of 2 was ascertained via 2D NMR experiments and a literature review. The absolute configurations of 1 and 2 were delineated with DP4+ computation and specific optical rotation. Homoscalarane 1 exhibited cytotoxicity towards MG63 human osteosarcoma cells. © 2024 Phytochemical Society of Europe

关键词： Felixin Homoscalarane Lendenfeldarane Lendenfeldia MG63

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Comparative genomics based exploration of xenobiotic degradation patterns in Glutamicibacter, Arthrobacter, and Pseudarthrobacter isolated from diverse ecological habitats

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Heliyon 2024年第22期10卷 e40280页

作者： Ghimire, Nisha Kim, Byeollee Han, So-Ra Oh, Tae-Jin Department of Life Science and Biochemical Engineering Graduate School SunMoon University Asan 31460 South Korea Bio Big Data-based Chungnam Smart Clean Research Leader Training Program SunMoon University Asan 31460 South Korea Genome-based BioIT Convergence Institute Asan 31460 South Korea Department of Pharmaceutical Engineering and Biotechnology SunMoon University Asan 31460 South Korea

Xenobiotics pose a substantial threat to environmental integrity by disrupting normal ecosystems. The genus Arthrobacter, known for its metabolic versatility can degrade several xenobiotic compounds. Arthrobacter strains have also undergone frequent taxonomic revisions and reclassifications to strains including Pseudarthrobacter and Glutamicibacter. Here, we present the complete genome sequence of Glutamicibacter protophormiae strain NG4, isolated from a coastal area surrounded by chemical plants. Further, through comparative genomics involving 55 strains from Glutamicibacter, Arthrobacter, and Pseudarthrobacter, we elucidated taxonomic relationships and xenobiotic degradation potential. Our genomics-based findings revealed a generally even distribution of xenobiotic-degrading genes and pathways among the studied strains. Glutamicibacter species emerged as potential candidate for steroid degradation. A significant number of host-specific and environmental isolates predominantly possessed pathways for 4-hydroxybenzoate (4-HB) degradation and only the environmental isolates possessed benzoate degradation pathway. Certain Arthrobacter and Pseudarthrobacter species isolated from the environmental settings were identified as potential degraders of toluene, xylene, and phenanthrene. Notably, most strains contained pathways for azathioprine, capecitabine, and 5-fluorouridine pharmaceutical drug metabolism. Overall, our findings shed light on microbial metabolic diversity among 55 strains isolated from diverse sources and hint the importance of strict environmental monitoring. Further, for the application of the putative xenobiotic degrading strains, experimental validation is required in the future. © 2024

关键词： Arthrobacter Glutamicibacter KEGG pathway Pseudarthrobacter Xenobiotic

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