SLAM: Sales Lead AMplification Through GenAI and ML for e-Learning Platforms by Ganesan Ramachandran, Tanmay Narang, Vallidevi Krishnamurthy

“…In the domain of sales, the accurate prediction of leads is deemed essential for optimizing resource allocation and maximizing conversion rates. …”
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Enhancing revenue generation in Bangladesh’s FinTech sector: a comprehensive analysis of real-time predictive customer behavior modeling in AWS using a hybrid OptiBoost-EnsembleX m... by Avijit Chowdhury

“…The anticipation of future customer conduct is a cornerstone for resource allocation in sales and marketing, enabling strategic decision-making in manufacturing operations, inventory planning, and point-of-sale scenarios. …”
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Workload Forecasting Methods in Cloud Environments: An Overview by Samah Aziz, Manar Kashmoola

“…Cloud computing is becoming increasingly popular due to its on-demand resource allocation and scalability. It is essential to precisely anticipate workload as applications and users on cloud-based services increase to distribute resources effectively and avoid service interruptions. …”
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Explainable machine learning models for mortality prediction in patients with sepsis in tertiary care hospital ICU in low- to middle-income countries by Saumya Diwan, Vinay Gandhi, Esha Baidya Kayal, Puneet Khanna, Amit Mehndiratta

“…Conclusions The proposed approach could provide preemptive estimations into prognostication and outcome prediction of patients with sepsis in low-resource settings. This will aid in clinical decision-making, resource allocation and research for new treatment modalities.…”
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Optimizing Energy Efficiency in Cloud Data Centers: A Reinforcement Learning-Based Virtual Machine Placement Strategy by Abdelhadi Amahrouch, Youssef Saadi, Said El Kafhali

“…The proposed method, RLVMP, classifies VMs as sensitive or insensitive and dynamically allocates resources to minimize energy consumption while ensuring compliance with service level agreements (SLAs). …”
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Generalized BER Performance Analysis for SIC-Based Uplink NOMA by Mahmoud AlaaEldin, Emad Alsusa, Mohammad Al-Jarrah, Karim G. Seddik, Michail Matthaiou

“…It is shown that these expressions are essential for designing optimal uplink power allocation (PA) strategies and mitigating SIC error floors, as evidenced by the proposed PA algorithm which achieves significant performance gains. …”
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Energy Simulation and Optimal Scheduling of Integrated Energy System Considering Hybrid Energy Storage by Yongwei LUO, Chengren LI, Ling ZHANG, Jianmin ZHANG, Xinhong WU, Jinbu LIAN, Jin FAN

“…The complementary multi-energy based integrated energy system (IES) is an important way to improve regional energy efficiency and optimize energy resources allocation. An energy flow matrix model is established for the IES equipment with the minimal operating cost of the IES as the objective function, and a hybrid algorithm combining dynamic programming and the improved PSO is proposed. …”
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Robust Expansion Planning of Electric Vehicle Charging System and Distribution Networks by Yue Xiang, Ping Xue, Yanliang Wang, Lixiong Xu, Wang Ma, Miadreza Shafie-khah, Junlong Li, Junyong Liu

“…Finally, it is solved to perform distributionally robust expansion planning by the column and constraint generation algorithm. Effectiveness and scalability of the proposed planning method are illustrated by numerical case studies. …”
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Designing a work program for the discipline based on the elements of competencies by A. M. Polyanskiy, E. A. Smirnova

“…According to the authors, the use of the elements of competences allocated from the texts of standards, scientific and methodological developments and other sources of the subject field of activity of the university graduate, allows to determine the set and content of knowledge, skills and knowledge necessary for training in the field of preparation more fully, rationally distribute them among educational disciplines and practices, to form the main didactic units of the work program of the academic discipline, to ensure the traceability of the requirements to the results of mastering the disciplines to a specific source of requirements.In the process of research, a methodology for the collection, processing and systematization of information necessary for the preparation of documents for the organization of the educational process at the department of the university was developed and approved; the analysis of professional and branch standards of software engineering is carried out; an array of elements of competencies required by the graduate training directions 09.03.04 is formed; software tools for processing and structuring information, managing changes in the elements of competences, taking into account the interrelations between them are proposed.The article describes the structure of the data array of competencies required by the graduate of the bachelor’s degree in the direction of training 09.03.04 “Software Engineering”; the results of the analysis of the main types of competence sources are presented: the educational standard in the specified direction of bachelor’s degree, professional standards and branch standards of software engineering, ontological and architectural models of entities of the subject domain; an algorithm for the collection, processing and systematization of information necessary for the formation of competency elements; examples of forming various types elements of competences are given.The study has showed that the competence approach, expanded in the proposed methodology, to the formation of working programs of educational disciplines and practices of the basic professional educational program of higher education allows to ensure the completeness, relevance and consistency of the requirements for the preparation of students, the rational distribution of the subject matter of the teaching material between disciplines and their mutual coherence in the educational process.…”
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Aircraft Routing and Crew Pairing Solutions: Robust Integrated Model Based on Multi-Agent Reinforcement Learning by Chengjin Ding, Yuzhen Guo, Jianlin Jiang, Wenbin Wei, Weiwei Wu

“…Every year, airlines invest considerable resources in recovering from irregular operations caused by delays and disruptions to aircraft and crew. …”
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Evolutionary game-based cooperative strategy for effective capacity of multiple-input-multiple-output communications by Jianhua Liu, Jiadi Yu, Minglu Li, Luqun Li, Dazhi Li, Shigen Shen

“…Numerical results show that the proposed algorithm can effectively improve the quality of service for mobile two-dimensional multiple-input-multiple-output communication networks.…”
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A Matching Game for LLM Layer Deployment in Heterogeneous Edge Networks by Benedetta Picano, Dinh Thai Hoang, Diep N. Nguyen

“…Performance evaluation was conducted considering both simulations and a small-scale testbed to measure the effectiveness of the proposed algorithm compared to state-of-the-art alternatives. …”
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Using the clustering method to find the final environmental parameters coefficients in road construction projects by Eshagh Rasouli Sarabi, Ramin Vafaei Poursorkhabi, Mehdi Ravanshadnia

“…In the first phase, the Genetic Optimization Algorithm was implemented to determine convenient coefficients for the relevant parameters. …”
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Abiotic drivers of activity in a large, free-ranging, freshwater teleost, Murray cod (Maccullochella peelii). by Jason D Thiem, Ian J Wooden, Lee J Baumgartner, Gavin L Butler, Jamin Forbes, Matthew D Taylor, Robyn J Watts

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Predicting clinical outcomes at hospital admission of patients with COVID-19 pneumonia using artificial intelligence: a secondary analysis of a randomized clinical trial by Caio César Souza Conceição, Camila Marinelli Martins, Mayck Medeiros Silva, Hugo Caire de Castro Faria Neto, Davide Chiumello, Davide Chiumello, Davide Chiumello, Patricia Rieken Macedo Rocco, Fernanda Ferreira Cruz, Pedro Leme Silva

“…BackgroundPredicting clinical improvement after hospital admission in patients with COVID-19 is crucial for effective resource allocation. Machine-learning tools can help identify patients likely to show clinical improvement based on real-world data. …”
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Research on Prediction and Optimization of Airport Express Passenger Flow Based on Fusion Intelligence Network Model by Jin He, Yinzhen Li, Yuhong Chao

“…The purpose of this paper is to optimize the accuracy of airport express passenger flow prediction so as to meet the need for the optimal allocation of traffic resources against the background of accelerated urbanization and the rapid development of airport express services. …”
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Research on multidimensional dynamic defense strategy for microservice based on deep reinforcement learning by Dacheng ZHOU, Hongchang CHEN, Weizhen HE, Guozhen CHENG, Hongchao HU

“…Aiming at the problem that it is hard for security defense strategies in cloud native to guarantee the quality of service under dynamic requests, a multidimensional dynamic defense strategy for microservice based on deep reinforcement learning, named D2RA strategy, was proposed to provide dynamic configuration schemes that ensure security defense performance and quality of service for microservices under dynamical requests.Firstly, based on the characteristics of multiple replicas and invocation chains of microservices, a microservices state graph was established to depict the maps between requests, system configuration and security performance, quality of service, and resource overhead of microservices.Secondly, the D2RA framework was designed and a dynamic strategy optimization algorithm based on deep Q-network was proposed for microservices to provide fast and optimal system configurations update scheme under dynamic requests.The simulation results show that D2RA effectively allocate resources under dynamic requests, and achieve 19.07% more defense effectiveness and 42.31% higher quality of service as compared to the existing methods.…”
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Patterns and risk factors of falls among older adults: a systematic review by Tetiana Yermakova

“…The first algorithm is based on extracting documents with the highest citation metrics. …”
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A Transmit Beamforming and Nulling Approach with Distributed Scheduling to Improve Cell Edge Throughput by Wendy C. Wong, Qinghua Li, Shilpa Talwar

“…First, cell edge users suffering from severe interferences are identified. Next, the RRM unit allocates resource to serving cell edge users only. …”
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Equitable hospital length of stay prediction for patients with learning disabilities and multiple long-term conditions using machine learning by Emeka Abakasanga, Rania Kousovista, Georgina Cosma, Ashley Akbari, Francesco Zaccardi, Navjot Kaur, Navjot Kaur, Danielle Fitt, Gyuchan Thomas Jun, Reza Kiani, Satheesh Gangadharan

“…Predicting the length of stay (LOS) for patients with LD and multiple long-term conditions (MLTCs) is critical for improving patient care and optimising medical resource allocation. However, there is limited research on the application of machine learning (ML) models to this population. …”
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