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International Conference on Confluence The Next Generation Information Technology Summit (Confluence)

作者： S.Nikkath Bushra A. Syed Ismail P. Sasigresa Edwin Singh C Department of Computing Technologies SRM Institute of Scienece and Technology KattankulathurChengalpattu India Department of Data Science and Business Systems SRM Institute of Scienece and Technology KattankulathurChengalpattu India Department: Computer Science and Engineering Veltech University Department: Computer Science and Engineering Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology

data security is becoming increasingly important as cloud computing advances. data security is the fundamental problem of all distributed computing systems. Cloud computing enables access to distributed applications and services belonging to various organizations spread across different locations. Cloud computing raises security concerns, because it shares data with distributed users via network in an open terrain. In this system, some of the most important security services like image-based security are handled by the cloud computing system. The proposed scheme takes care of several attacks like botnets, malware and guessing attacks. This scheme is contrasted withseveral established schemesand a new form of authentication is used for the purpose of storing files in a secure manner.

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Exploring the Integration of Reinforcement Learning for Enhancing Game Performance: A Comprehensive Review

Exploring the Integration of Reinforcement Learning for Enha...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Munugapati Bhavana K Vijay Krupa Vatsal Yerra Anjali Satyavathi Navyatha Ravi J. Kavitha V. Thrimurthulu Department of CSE MLR Institute of Technology Affiliated to JNTUH Hyderabad Department of CSE Malla Reddy University Hyderabad Department of Data Science MLR Institute of Technology Hyderabad Department of CSE Koneru Lakshmaiah Education Foundation Bowrampet Hyderabad Department of Computer Science & Engineering MLR Institute of Technology Hyderabad

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Reinforcement learning, a subset of machine learning, encompasses the process by which an agent learns through trial-and-error feedback to anticipate its subsequent actions. Its versatility extends across various domains, with gaming being a prominent application. Success in gaming often pivots on the formulation of effective strategies, a task that necessitates repetitive game play, consuming valuable time, energy, and resources. This study aims tointegrate a reinforcement learning agent into gaming scenarios, replicating game dynamics and progressively refining outcomes with each iteration. By mimicking the agent’s performance, human players can augment their likelihood of success. This document highlights the utilization of reinforcement learning techniques, focusing on the application of Value-based methods (Q-learning, Deep Q Network (DQN)), and Model-based methods(State-Action-Reward-State-Action (SARSA)). Q-learning from Value-based methodis designed as an off-policy algorithm, whereas SARSA from Model-based methods functions as *** outcomes presented encompass insights from previous research on Q-learning and SARSA across diverse test fields or settings. Furthermore, the proposed reinforcement learning methodologies address key facets such as data comprehension, problem categorization, algorithm identification, and algorithm implementation.

关键词： Q-learning Machine learning algorithms Reviews Heuristic algorithms Refining Focusing Games Generative adversarial networks Deep reinforcement learning Real-time systems

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IoT Based Fish Pond Monitoring System to Enhance Its Productivity 3

IoT Based Fish Pond Monitoring System to Enhance Its Product...

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3rd International Conference on Innovative Practices in Technology and Management, ICIPTM 2023

作者： Kumar, S M Ravi Mohammed, Thayyaba Khatoon Rao, Seeram Srinivasa Dinesh Anton Raja, P. Bakhare, Ruhi Kumar, Ashok Sarkar, Swagata G. Pullaiah College of Engineering and Technology Department of Mechanical Andhra Pradesh India School of Engineering Malla Reddy University Telangana India Koneru Lakshmaiah Education Foundation Department of Mechanical Engineering Andhra Pradesh India R.M.K. Engineering College Department of Electronics & Communication Chennai India Dr. Ambedkar Institute of Management Studies & Research Department of Master of Business Administration Maharashtra India Banasthali Vidyapith Department of Computer Science Rajasthan India Sri Sai Ram Engineering College Department of Artificial Intelligence & Data Science Chennai India

ISBN: (纸本)9798350336238

Modernizing fish ponds for agricultural production face major challenges in terms of capital expenditure and operational expenses. Fish farming of particular types of fish species necessitates the fulfilment of several requirements because, like several other living organisms, fish have a precise limit for an assortment of environmental criteria. For the good health and development of the organisms, big farms typically have certain kinds of water surveillance and replacement mechanization systems. To preserve the ecosystems for living fish, the people who work in the fish farming ponds must be active throughout the day. Local farmers who operate on relatively small ponds couldn't afford to compensate employees to manage daily tasks, which typically include keeping an eye on water levels, temperature, and pH levels. As a result, the prime motive for this paper is to monitor and take steps to keep the habitat's eco-friendly environment for specific species of fish, which will decrease the time required for some basic actions. This article puts forth a smart Internet of Things (IoT) based fish pond water monitoring system. Such a smart system consists of several real-time sensors that monitor and send inputs to a microcontroller and the data is stored in a real-time database. The user can track these values through a phone app that is assimilated with the cloud by having them transmitted to the cloud at periodic intervals and this helps the fish pond owners to take required action quickly and effectively when needed. As embedding devices are typically made up of an Arduino board, internet and relay frames, and a computer interface, a farmer could easily source these parts. With the help of this integration system, farmers can reduce operating costs and boost overall effectiveness by avoiding the need to hire employees for their location. © 2023 IEEE.

关键词： Fish

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High-Resolution and High-Rate Dual-Comb FMCW Lidar with Coherent Comb Stitching

High-Resolution and High-Rate Dual-Comb FMCW Lidar with Cohe...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Xianyi Cao Long Wang Tianyi Li Minglu Cai Guiling Wu Jianping Chen Kan Wu Department of Electronic Engineering State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Institute for Advanced Communication and Data Science Shanghai Jiao Tong University Shanghai China

A dual-comb FMCW Lidar with coherent comb stitching (CCS) technique is firstly demonstrated. CCS can simultaneously achieve 65 GHz high frequency sweeping range, millimeter-level ranging resolution and 100 kHz high vo... 详细信息

ISBN: (纸本)9798350369311

关键词： Laser radar Lasers and electrooptics Distance measurement High frequency Electro-optical waveguides

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Animal Shapes, Modal Analysis, and Visualization of Motion (III): Giraffe, Duck, Goose, T-Rex Dinosaur, and the Flying Modes of Eagle

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Journal of Geometric Analysis 2023年第10期33卷 1-28页

作者： Yang, Jing Chen, Goong Wei, Chunqiu Sergeev, Alexey Huang, Jingtong Scully, Matthew M. Krantz, Steven G. Yao, Pengfei Guo, Tiexin Wang, Junmin Chen, Ming-Chieh Corti, Darrell School of Mathematics and Statistics Beijing Institute of Technology Beijing 102488 China Department of Mathematics Texas A &M University College Station 77843 TX United States Institute for Quantum Science and Engineering Texas A &M University College Station 77843 TX United States Hsinchu Branch National Center for Theoretical Sciences National Tsing Hua University Hsinchu Taiwan Department of Mathematics and Data Science Beijing University of Civil Engineering and Architecture Beijing 100044 China Department of Mathematics Washington University at St. Louis St. Louis 63130 MO United States Key Laboratory of Complex Systems and Data Science of Ministry of Education School of Mathematics Shanxi University Shanxi Taiyuan 030006 China Institute of Systems Science Academy of Mathematics and Systems Science Academia Sinica Beijing 100190 China School of Mathematics and Statistice Central South University Hunan Changsha 410075 China Department of Mechanical Engineering Cheng Shiu University Kaohsiung Taiwan Corti Brothers 5810 Folsom Blvd. Sacramento 95819 CA United States

This paper contains more varieties of animals, including the giraffe, bird species duck, goose and eagle, and the T-Rex dinosaur. They range across mammals, birds and reptiles. For each of them, we present their first one hundred modes of motion. Three objectives of this paper are as follows: (i)To see more different types of modes of motion from a larger varieties of animals so as to make visual comparisons between interspecies behavioral patterns.(ii)To illustrate the wing-flapping flying modes of an eagle.(iii)To show the modes of motions of an extinct animal, the T-Rex dinosaur. © 2023, Mathematica Josephina, Inc.

关键词： Animal shapes Duck, Goose, Dinosaur, and the flying modes of an eagle Motion patterns

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Structuring Clinical Notes of Italian ST-elevation Myocardial Infarction Patients 1

Structuring Clinical Notes of Italian ST-elevation Myocardia...

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1st Workshop on Patient-Oriented Language Processing, CL4Health 2024

作者： Torri, Vittorio Mazzucato, Sara Dalmiani, Stefano Paradossi, Umberto Passino, Claudio Moccia, Sara Micera, Silvestro Ieva, Francesca MOX - Modelling and Scientific Computing Lab Department of Mathematics Politecnico di Milano Italy Biorobotics Institute Department of Excellence in Robotics and AI Scuola Superiore Sant’Anna Italy Fondazione Toscana Gabriele Monasterio Italy Health Science Interdisciplinary Center Scuola Superiore Sant’Anna Italy Bertarelli Foundation Chair in Translational Neural Engineering Center for Neuroprosthetics Institute of Bioengineering Ecole Polytechnique Federale de Lausanne Switzerland HDS - Health Data Science Centre Human Technopole Italy

ISBN: (纸本)9782493814258

In recent years, it has become common for patients to get full access to their Electronic Health Records (EHRs), thanks to the advancements in the EHRs systems of many healthcare providers. While this access empowers patients and doctors with comprehensive and real-time health information, it also introduces new challenges, in particular due to the unstructured nature of much of the information within EHRs. To address this, we propose a pipeline to structure anamneses, providing patients with a clear and concise overview of their health data and its longitudinal evolution, also allowing clinicians to focus more on patient care during consultations. In this paper, we present preliminary results on extracting structured information from EHRs of patients diagnosed with ST-Elevation Myocardial Infarction from an Italian hospital. Our pipeline exploits text classification models to extract relevant clinical variables, comparing rule-based, recurrent neural network and BERT-based models. While various approaches utilized ontologies or knowledge graphs for Italian data, our work represents the first attempt to develop this type of pipeline. The results for the extraction of most variables are satisfactory (f1-score > 0.80), with the exception of the most rare values of certain variables, for which we propose future research directions to investigate. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Recurrent neural networks

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Monolithic 50 GHz Tunable Microwave Signal Generation Based on Erbium-Doped Lithium Niobate Dual Lasers

Monolithic 50 GHz Tunable Microwave Signal Generation Based ...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Minglu Cai Xujia Zhang Tianyi Li Hao Shi Tieying Li Xianyi Cao Zekun Cui Jianping Chen Kan Wu Department of Electronic Engineering State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Institute for Advanced Communication and Data Science Shanghai Jiao Tong University Shanghai China

The monolithic erbium-doped lithium niobate lasers can achieve a tunable wavelength range of 56.25 GHz and generate a 50 GHz microwave signal with a side-mode suppression ratio of 35 dB by dual lasers.

ISBN: (纸本)9798350369311

关键词： Lithium niobate Masers Lasers and electrooptics Electro-optical waveguides

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CONVERGENCE ANALYSIS OF THE TRANSFORMED GRADIENT PROJECTION ALGORITHMS ON COMPACT MATRIX MANIFOLDS

arXiv

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arXiv 2024年

作者： Ding, Wentao Li, Jianze Zhang, Shuzhong School of Data Science Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Guangdong Shenzhen China Shenzhen International Center for Industrial and Applied Mathematics Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Guangdong Shenzhen China Department of Industrial and Systems Engineering University of Minnesota MinneapolisMN55455 United States

In this paper, to address the optimization problem on a compact matrix manifold, we introduce a novel algorithmic framework called the Transformed Gradient Projection (TGP) algorithm, using the projection onto this compact matrix manifold. Compared with the existing algorithms, the key innovation in our approach lies in the utilization of a new class of search directions and various stepsizes, including the Armijo, nonmonotone Armijo, and fixed stepsizes, to guide the selection of the next iterate. Our framework offers flexibility by encompassing the classical gradient projection algorithms as special cases, and intersecting the retraction-based line-search algorithms. Notably, our focus is on the Stiefel or Grassmann manifold, revealing that many existing algorithms in the literature can be seen as specific instances within our proposed framework, and this algorithmic framework also induces several new special cases. Then, we conduct a thorough exploration of the convergence properties of these algorithms, considering various search directions and stepsizes. To achieve this, we extensively analyze the geometric properties of the projection onto compact matrix manifolds, allowing us to extend classical inequalities related to retractions from the literature. Building upon these insights, we establish the weak convergence, convergence rate, and global convergence of TGP algorithms under three distinct stepsizes. In cases where the compact matrix manifold is the Stiefel or Grassmann manifold, our convergence results either encompass or surpass those found in the literature. Finally, through a series of numerical experiments, we observe that the TGP algorithms, owing to their increased flexibility in choosing search directions, outperform classical gradient projection and retraction-based line-search algorithms in several *** Codes 15A23, 49M37, 65K05, 90C26, 90C30 Copyright © 2024, The Authors. All rights reserved.

关键词： Optimization

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Automated Assignment Management System: Integrating Email Inbox Parsing, database Updates, and Notification

Automated Assignment Management System: Integrating Email In...

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Advances in Computing, Communication and Applied Informatics (ACCAI), International Conference on

作者： P Varun R.S. Rashika S Kayalvizhi D Preetha P Naveen T A Mohanaprakash Department of Data Science and Business Systems School of Computing SRM Institute of Science and Technology Kattankulathur Department of CSE Panimalar Engineering College Chennai Department of Computer Science and Engineering Velammal Engineering College Department of Information Technology Alpha College of Engineering Department of Computational Intelligence SRM Institute of Science and Technology Kattankulathur Chennai Department of CSE School of Engineering & Technology CMR University Bengalunu Karnataka

ISBN: (数字)9798350389449

ISBN: (纸本)9798350389456

This paper presents the design and implementation of an automated assignment management system utilizing a bot interface. The system’ s primary objective is to streamline the process of collecting and tracking student assignments, ensuring timely updates to a central database, and facilitating communication between students and teachers. The bot employs email inbox parsing techniques to identify incoming assignment submissions, extracting relevant data such as student names, assignment details, and submission timestamps. Upon receiving a submission, the bot updates an Excel database with the pertinent information, maintaining an organized record of completed ***, the system incorporates a notification feature to promptly alert students who have not yet submitted their assignments by the deadline. Leveraging email integration, the bot sends personalized notifications reminding students of impending deadlines and urging them to submit their work promptly. Additionally, the bot generates a list of incomplete assignments and forwards it to the respective teacher, providing a consolidated overview of students who require *** automating the assignment management process, this system reduces manual intervention, minimizes administrative burden, and enhances efficiency in monitoring student progress. The integration of email parsing, database updates, and notification functionalities ensures seamless communication and facilitates timely submission of assignments, contributing to improved academic outcomes and instructor-student engagement

关键词： Automation databases Manuals Chatbots Feature extraction data mining Informatics

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As an AI Language Model, "Yes I Would Recommend Calling the Police": Norm Inconsistency in LLM Decision-Making

arXiv

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arXiv 2024年

作者： Jain, Shomik Calacci, D. Wilson, Ashia Institute for Data Systems and Society Massachusetts Institute of Technology United States Center for Information Technology Policy Princeton University United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology United States

We investigate the phenomenon of norm inconsistency: where LLMs apply different norms in similar situations. Specifically, we focus on the high-risk application of deciding whether to call the police in Amazon Ring home surveillance videos. We evaluate the decisions of three state-of-the-art LLMs – GPT-4, Gemini 1.0, and Claude 3 Sonnet – in relation to the activities portrayed in the videos, the subjects’ skin-tone and gender, and the characteristics of the neighborhoods where the videos were recorded. Our analysis reveals significant norm inconsistencies: (1) a discordance between the recommendation to call the police and the actual presence of criminal activity, and (2) biases influenced by the racial demographics of the neighborhoods. These results highlight the arbitrariness of model decisions in the surveillance context and the limitations of current bias detection and mitigation strategies in normative decision-making. © 2024, CC BY.

关键词： Decision making

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