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检索条件"机构=Dept. Computational Data Science and Engineering"

共 1624 条记录，以下是161-170 订阅

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Leveraging YOLOv8 for Real-Time Parking Space Detection

Leveraging YOLOv8 for Real-Time Parking Space Detection

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2024 Beyond Technology Summit on Informatics International Conference, BTS-I2C 2024

作者： Pallawabonang, Mahabintang Adnan, Muh. Zuhriyah, Sitti Mukmin, Amirul Prakasa, Esa Yuyun Handayani University of Makassar Dept. of informatics engineering Makassar Indonesia Handayani University of Makassar Dept. of Computers System Makassar Indonesia Research center for data and information science National Research and Innovation Agency Bandung Indonesia

ISBN: (纸本)9798331508579

This research develops a smart parking system based on computer vision integrated with the Firebase platform, utilizing the YOLOv8 algorithm and the OpenCV library. This system is designed to detect vehicles and determine the availability status of parking slots in real time through video recording analysis. The dataset was obtained from recorded parking activity videos, then processed using Roboflow for data labeling, and fine-tuned on Google Colab. The resulting model shows a vehicle detection accuracy of up to 99.1% with high stability, as indicated by the training loss graph. The process of mapping the parking area is carried out through an OpenCV-based application for the identification and configuration of parking slots. The status of each parking slot is automatically updated to the Firebase Realtime database, enabling efficient historical data recording and information management. Testing shows the system's reliable performance under various lighting conditions, with high capabilities in vehicle detection and real-time data management. This study makes a significant contribution to the development of parking management solutions through the integration of technology that supports operational efficiency and high accuracy. © 2024 IEEE.

关键词： Information management

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Synchronous Parallel Heuristics for Solving the Joint Order Batching and Picker Routing Problem 13

Synchronous Parallel Heuristics for Solving the Joint Order ...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Tran, Son Thai Almeida, Rui Jorge Defryn, Christof Van Nieuwenhuyse, Inneke School of Business and Economics Maastricth University Dept. of Quantitative Economics Maastricht Netherlands School of Business and Economics Maastricth University Dept. of Data Analytics and Digitization Maastricht Netherlands University of Antwerp Faculty of Business and Economics Dept. of Engineering Management Antwerp Belgium FlandersMake@UHasselt Data Science Institute Hasselt University Faculty of Sciences Hasselt Belgium

ISBN: (纸本)9798350308365

The joint order batching and picker routing problem is an important problem for improving warehouse efficiency. The goal is to minimize the total distance travel of picking customer orders. It is NP-hard, indicating that exact solutions are intractable for large instances. Many solution methods provided in the current literature use local search to solve the problem sequentially, often including a complex searching procedure for the order batching problem (OBP) followed by a simple heuristic for the picker routing problem (PRP). In this paper, we propose three heuristics that jointly solves the OBP and the PRP: two of these are combinations of variable neighborhood search, simulated annealing, and tabu search, while the third one uses guided local search. We discuss how the search procedure of the proposed algorithms can be parallelized, and benchmark them against state-of-the-art heuristics using well-studied instances. The results show a reduction of 3.06% to 7.63% in the geometric mean of the total travel distance across 64 instances. Increasing the number of threads in parallelization leads to diminishing returns in reducing running time and has no statistical effect on travel distance. In contrast, increasing the chunk size results in a linear increase in running time for all proposed algorithms, and improves the travel distance obtained when the batch size is 75 items. © 2024 IEEE.

关键词： Simulated annealing

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Grammar Error Correction in Indonesian Sports News: Comparing the Performance of Pre-Trained T5 and BART Models

Grammar Error Correction in Indonesian Sports News: Comparin...

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2024 Beyond Technology Summit on Informatics International Conference, BTS-I2C 2024

作者： Adnan, Muh Prakasa, Esa Yuyun Umar, Najirah Nasrullah Sadli, Adi Anatasya, A. Edeth Fuari Hazriani Razak, Mashur Handayani University of Makassar Dept. of informatics engineering Makassar Indonesia Research center for data and information science National Research and Innovation Agency Bandung Indonesia Handayani University Makassar Dept. of computer system Makassar Indonesia

ISBN: (纸本)9798331508579

This research compares the performance of two pre-trained models based on the transformer, namely text-to-text transfer transformer (T5) and bidirectional and auto-regressive transformer (BART), through a fine-tuned for correcting grammar in Indonesian sports news texts. We used vennify/t5-base-grammar-correction and onionLad/grammar-correction-bart-base, was trained using a dataset of 10,075 sentences from Indonesian language sports news sites. We tested the model performance using bilingual evaluation understudy (BLEU), google's language evaluation understanding (GLEU), training loss, and validation loss. The results show that BART was more efficient in learning data patterns and has better generalization ability, supported by BLEU and GLEU scores of 0.8560 and 0.9655. Meanwhile, T5 maintains simpler sentence structures, supported by BLEU and GLEU scores of 0.8120 and 0.9564. BART excels at handling more complex contexts, making it more effective at accurately correcting errors in dynamic sports news. Both models have their respective advantages, with BART being better at correcting detailed grammatical errors, while T5 offers consistent correction of more simple sentence structures. © 2024 IEEE.

关键词： Error correction

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Ocular Cataract Identification Using Deep Convolutional Neural Networks 6

Ocular Cataract Identification Using Deep Convolutional Neur...

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6th International Conference on Artificial Intelligence, Big data, Computing and data Communication Systems, icABCD 2023

作者： Manuel, Feliciana M. E. Saide, Saide Manuel Ali, Felermino D. M. A. Lotfi, Sanae Lurio University Faculty of Engineering Dept. of Computer Engineering Pemba Mozambique New York University Center for Data Science New York United States

ISBN: (纸本)9798350314809

Ocular cataract is among diseases that result in blindness if not treated in time. It affects people worldwide, primarily in underdeveloped countries. This health problem affects the quality of patients' lives. However, early diagnosis avoids blindness and allows the patient to have appropriate treatment. Developing countries, especially those with low income, have a precarious health system, even in the ophthalmology sector, where equipment is lacking. This research aims to develop a deep learning-based model to detect ocular cataracts based on retinal images. We collect 1000 retinal images from Kaggle, which are then equally divided into two classes: with and without cataracts. We then use several neural architectures to correctly classify these images, including ResNet18, ResNet34, InceptionResNetV2, and InceptionV4. We demonstrate that ResNet18 outperforms the other architectures, reaching 95.5% accuracy score. Our results suggest that deep convolutional neural networks can achieve a significant performance in ocular cataracts classification using retinal images. © 2023 IEEE.

关键词： Convolution

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Crowd Estimation Using Sensors for Public Transport (BUSES)

Crowd Estimation Using Sensors for Public Transport (BUSES)

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2023 International Conference on New Frontiers in Communication, Automation, Management and Security, ICCAMS 2023

作者： Sumathi, S. Soms, Nisha Gowtham, S. Pagalavan, M. Hariharan, S. Sri Eshwar College of Engineering Dept. of Artificial Intelligence and Data Science Coimbatore641 202 India Kpr Institute of Engineering and Technology Coimbatore India

ISBN: (纸本)9798350317060

The Population in Indian metropolitan metropolises have been growing at an intimidating rate. In these metropolises, motorcars are generally the most preferred last afar trip, due to their cheap rates and expansive routes. Crowd estimation ways using cameras inside the motorcars aren't suitable. Hence, we've enforced a result using Internet of effects. Crowd operation system is necessary in those circumstances to prevent crowd problems. Therefore, in order to preserve lives, it is very necessary for a frame to be in charge of these masses. In terms of crowd timing and used sweating, this frame shall be clever and efficient. The suggested framework is based on IoT, facilitates relationships between electronic devices, and presents information through smart operations with a tidy, straightforward interface for flexible and simple operation by individuals from all eras. The goal is to support directors' control in an explosive way and distribute to callers over the designated area. The detector, operation, and affiliate layers make up the three layers that make up the frame. The detector subcaste is in charge of gathering crowd data. As a mediator between detectors and affiliate layers, the operation subcaste. It consists of online or other services that are in charge of gathering and analyzing data flowing from the detectors. Additionally, it alerts managers of busy places so they can act appropriately. Later, the appropriate choice will be made and communicated to the interface subcaste. The proposed crowded the machine is and how far is it from their position for which They're staying. To reduce the vexation in the operation of Public Transport System(motorcars) through Integration of tackle and software technologies that provides stoner interface with 1. Live position of the machine (through GPS). 2. Crowd position in the machine (through Detectors). © 2023 IEEE.

关键词： Internet of things

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CAPLC: Cellular Automata-Powered Lightweight Cipher-Unveiling Secure Communication in Resource-Constrained Environments Using Cellular Automata and Henon Map

CAPLC: Cellular Automata-Powered Lightweight Cipher-Unveilin...

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Next Generation Communication & Information Processing (INCIP), International Conference on

作者： Biswarup Yogi Satyabrata Roy Umashankar Rawat Shweta Redkar Utsav Upadhyay Dept. of Computational Sciences Brainware University Kolkata West Bengal India Dept. of Computer Science and Engineering Manipal University Jaipur Rajasthan India Dept. of Data Science and Engineering Manipal University Jaipur Rajasthan India Dept. of Computer Science & Engineering Sir Padampat Singhania University Udaipur Rajasthan India

ISBN: (数字)9798331528140

ISBN: (纸本)9798331528157

In today's interconnected world, ensuring secure communication in resource-constrained contexts is still challenging. This study offers CAPLC, a novel technique for lightweight encryption that uses Cellular Automata (CA) and Henon maps. Its goal is to improve security in such situations. The method uses 1D Cellular Automata for initial data transformation and incorporates the Henon map to improve encryption strength. We used conventional metrics to evaluate CAPLC's effectiveness on image encryption, and the findings were promising: NPCR of 99.6154%, UACI of 33.88235, and PSNR of 9.1924. These numbers show the method's capacity to dramatically change image while maintaining quality and anonymity. The implications of CAPLC go beyond image encryption, providing a scalable solution for secure communication in circumstances with limited computational resources. Future studies ought to explore CAPLC's real-time application and performance across various kinds of datasets, with a focus on the potential of merging CA with Henon maps to create efficient encryption methods for improving secure communications technology.

关键词： Measurement Merging Automata Medical services Information processing Parallel processing Real-time systems Encryption Resilience Principal component analysis

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Auction based Resource Allocation in Cloud Computing using Blockchain Techniques 14

Auction based Resource Allocation in Cloud Computing using B...

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14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Kamaleshwar, T. Jayaraj, R. Vijayaraj, N. Sundaranarayana, D. Dr.Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Dept. of Computer Science & Engineering Chennai India SRM Institute of Science and technology Dept. of Data Science and Business systems Kattankulathur Chennai India

As the spine innovation of decentralized cryptocurrencies, blockchain has additionally proclaimed numerous applications in different fields, for example, resource allocation in cloud computing, Internet of Things (IoT) and resource offloading. The database state is decentrally kept up, and any part hub in the overlay blockchain organize is allowed to partake in the state support without character confirmation. The exchanges among part hubs are recorded in cryptographic hash-connected information structures known as squares. A progression of affirmed blocksis orchestrated in ordered request to shape a consecutive chain, henceforth named blockchain. All part hubs in the system are required to pursue consensus protocol on the value-based information, cryptographic hashes and computerized marks put away in the block to ensure trustworthiness of the blockchain. © Grenze Scientific Society, 2023.

关键词： Blockchain

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Smart City Solutions Leveraging Internet of Things (IoT) Technology 1

Smart City Solutions Leveraging Internet of Things (IoT) Tec...

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1st IEEE International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Kumawat, Bhawesh Shalini, E. Tomar, Vinay Upadhyay, Rajesh Kumar Gupta, Divyanshu Geetha, P.V. Madhav University Dept. of CSE Pindwara India Meenakshi A.H. Edu. & Research Dept. of Computer Science Chennai India Jiwaji University Dept. of Chemistry Gwalior India Usha Martin University Dept. of EEE Jharkhand India J.S. University Dept. Electronics & Comm. Engineering Shikohabad India Dhanalakshmi Srinivasan College Dept. of AI & Data Science Coimbatore India

ISBN: (纸本)9798350356816

The widespread adoption of the Internet of Things (IoT) is facilitating the development of Smart City initiatives globally. Everyday objects are increasingly equipped with electronic gadgets and connected through various protocol suites, becoming part of a vast network. According to a recent Gartner study, by 2020, smart cities are projected to deploy 50 billion connected devices. This advancement is expected to make urban environments more adaptive and resilient to future changes. This paper explores current and future trends in smart cities and IoT, highlighting the technologies and applications driving their growth. We examine how the expansion of IoT directly impacts the evolution of smart cities and discuss the interplay between the two, as well as the factors motivating their development. Smart cities have the potential to reduce manual labor, mitigate disaster risks, and streamline daily life. Lastly, we address some of the challenges associated with IoT in the context of smart cities and propose potential solutions to these issues. © 2024 IEEE.

关键词： Smart city

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Design and Implementation of a Mobile Application for Intelligent Attendance Tracking 1

Design and Implementation of a Mobile Application for Intell...

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1st IEEE International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Kaushik, Priyanka Nadhiya, S. Jain, Deepak Verma, Anupama Kumar, Saurabh Bhavadharani, S. Chandigarh University Dept. of Computer Science Engineering Chandigarh India Dhanalakshmi Srinivasan College Dept. of AI & Data Science Coimbatore India IIM Indore Dept. of Management Indore India Usha Martin University Dept. of Business Management & Comm Jharkhand India Mangalayatan University Dept. of Business Management & Commerce Aligarh India A.H. Edu. & Research Dept. of Commerce Meenakshi Chennai India

ISBN: (纸本)9798350356816

Taking attendance is an important task in schools, universities, and other institutions. However, traditional attendance taking methods such as paper-based attendance sheets or manual entry into an electronic system are time-consuming and prone to errors. In recent years, the emergence of facial recognition technology has opened up new possibilities for attendance management systems. This research paper discusses the development and implementation of a Smart Attendance System using Facial Recognition technology using OpenCV in educational institutions. The study explores the benefits, limitations, and ethical considerations associated with this technology and its implications for the future of attendance management systems. This model takes use of LBPH and gja, exfilaface recognition to increase accuracy over conventional models. After this, the connection of recognized faces is compared with the kdatabase containing student's faces. This model will be an effective method for controlling student attendance. © 2024 IEEE.

关键词： Students

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A New Holistic Approach for Prosthesis Polymeric Aortic Valve Design

A New Holistic Approach for Prosthesis Polymeric Aortic Valv...

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Thermal, Mechanical and Multiphysics Simulation and Experiments in Micro-Electronics and Micro-Systems EuroSimE

作者： Müge Yaren Yaşartürk Emirhan Yığıt Reza Daryanı Emre Cenk Ersan Mustafa Serdar Çelebı Dept. of Computational Science and Engineering Istanbul Technical University Istanbul Turkey Dept. of Computer Engineering Istanbul Beykent University Istanbul Turkey Dept. of Mechanical Engineering Istanbul Technical University Istanbul Turkiye Dept. of Computational Science and Engineering Istanbul Technical University Istanbul Turkiye

ISBN: (数字)9798350393002

ISBN: (纸本)9798350393019

Aortic valve insufficiency is a life-threatening condition. The primary treatment approach is the replacement of the native valve with prosthetic valves in severe cases. However, current prostheses often lead to complications such as durability issues, the need for lifelong anticoagulation medicine usage, and tissue rejection. As a result, multiple surgical interventions are frequently required for prosthesis replacement. This study highlights the importance of a comprehensive prosthetic design process by encompassing patient-specific design, careful material selection, and advanced three-dimensional fabrication, which is essential for addressing these challenges. To enhance the mechanical durability of polymeric heart valve prostheses, we introduce a framework that combines fluid-structure interaction (FSI) simulations to obtain hemodynamic properties prior to advanced structural analyses. While our methodology is based on determining hemodynamic loads with FSI simulations and transferring them to an additional finite element model (FEM) that captures the detailed mechanical properties of valve tissue, the results presented in this study are obtained using more traditional loading conditions in FEM to ensure the validity and comparability of our findings. These results serve as a foundation for future studies incorporating full FSI-driven structural simulations. These analyses lead to the creation of a geometrically optimized design, fabricated with a digital light processing-based (DLP) method. Subsequently, mechanical testing was conducted to evaluate the effects of this manufacturing technique on material behavior, producing more realistic material model coefficients for use in numerical simulations. Consequently, different ratios of material rigidity in fiber-reinforced models are investigated with FEM analysis. An important novelty of this approach is to be able to detect stress accumulations by taking hemodynamic indices into account to optimize the stress di

关键词： Analytical models Valves Finite element analysis Hemodynamics Numerical models Polymers Heart valves Stress Prosthetics Load modeling

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