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检索条件"任意字段=Proceedings of the 9th Knowledge-Based Software Engineering Conference"

共 20365 条记录，以下是971-980 订阅

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9th conference on Transportation Systems engineering and Management, CTSEM 2023

9th Conference on Transportation Systems Engineering and Man...

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9th conference on Transportation Systems engineering and Management, CTSEM 2023

ISBN: (纸本)9789819760749

the proceedings contain 48 papers. the special focus in this conference is on Transportation Systems engineering and Management. the topics include: Comparison Study on Various Backcalculation Techniques for Estimating the Resilient Modulus of Asphalt Pavement Layers;enhancing Bituminous Mix Performance with Waste-Treated Bricks as Aggregate Partial Replacement: A Comprehensive Evaluation;Performance Evaluation of Full Depth Reclaimed Mixes with Varying RAP Incorporation Levels;evaluation of Recycled Asphalt Pavement Materials Using Simple Characterization Methods;rejuvenation of Scarified Bituminous Pavement Materials;Applicability of Cohesion Test in the Estimation of Effective RAP Binder;a Compressive Strength Model for Silica Fume Pervious Concrete: A Sustainable Material;utilization of Domestic and Automobile Waste Materials in the Application of Bituminous Concrete Mixes;laboratory Studies on Cement Stabilized Weathered Steel Slag for Use in Pavement Base Course;Experimental Response of Reinforced Wall with Bamboo Geocell and GBFS as Reinforced Fill Material;slope Stability Evaluation of Highway Embankments Using the Geo-slope Model;durability Analysis of the Nanomaterial Stabilized Granular Mix as Subbase Layer for High Volume Pavement;camera based Road Anomaly Detection Using Deep Learning;statistical Analysis of Network Level Pavement Maintenance and Management System;penalties Due to Deferred Maintenance in Network Level Pavement Management;methodology for Optimization of Routine Maintenance of Road Against Available Budget and Resources by Using Integer Programming;Household Proximity to Metro: A Perspective Related to TOD and Travel;impact of Commuting Stress on Urban Travel Behaviour—Case of Delhi Metropolitan City in India;analysis of Transportation Infrastructure Facilities Using Binary Logit Model.

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BnGraphemizer: A Grapheme-based Tokenizer for Bengali Handwritten Text Recognition 9

BnGraphemizer: A Grapheme-based Tokenizer for Bengali Handwr...

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9th IEEE International Women in engineering (WIE) conference on Electrical and Computer engineering, WIECON-ECE 2023

作者： Basher, Mohammad Jahid Ibna Noor, Mohammad Raghib Afroze, Sadia Ahmed, Ikbal Hoque, Mohammed Moshiul Chittagong University of Engineering & Technology Department of Computer Science and Engineering Chittagong Bangladesh University of Dhaka Department of Management Information Systems Dhaka Bangladesh CCN University of Engineering & Technology Computer Science and Engineering Cumilla Bangladesh

Bengali Handwritten Text Recognition (HTR) is a challenging task due to the text9;s cursive disposition and significant variations in the graphemic unit, the smallest written unit in alphasyllabary languages. these... 详细信息

ISBN: (纸本)9798350319651

Bengali Handwritten Text Recognition (HTR) is a challenging task due to the text's cursive disposition and significant variations in the graphemic unit, the smallest written unit in alphasyllabary languages. these graphemic units, or simply graphemes, may consist of multiple characters and diacritics, and the order of characters or diacritics between textual and visual representations is only sometimes preserved. Moreover, Bengali conjunct characters, a subset of the graphemes, often have unique visual representations vastly different from the characters they comprise. Because of these inherent characteristics, a character-based tokenizer fails to tokenize the label text appropriately for BHTR in a supervised setting, making it challenging to adapt the existing sequence-to-sequence frameworks often used for Handwritten Text Recog-nition (HTR). To address this, this paper proposes a trie- based text tokenizer (called BnGraphemizer) that allows one to tokenize text into a set of graphemes instead of characters. Experimental investigations show that the BnGraphemizer-based BHTR system performs better regarding higher Word Recognition Rate (WRR) than its character-based counterpart in two of three Bengali handwritten datasets. © 2023 IEEE.

关键词： Character recognition

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2023 9th International conference on Control, Automation and Robotics, ICCAR 2023

2023 9th International Conference on Control, Automation and...

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9th International conference on Control, Automation and Robotics, ICCAR 2023

ISBN: (纸本)9798350322514

the proceedings contain 71 papers. the topics discussed include: design research on electronic sphygmomanometer for the elderly based on Miryoku engineering;dynamic modeling and validation of soft robotic snake locomotion;modeling and implementation of a 3 degrees of freedom delta robot through gestalt framework;robotic arm for unfastening screws in automated disassembly process;research on backstepping control of flexible joint manipulator with state constraint;cuckoo search algorithm optimization of holt-winter method for distribution transformer load forecasting;motion planning of dual-chain manipulator based on artificial bee colony algorithm;state feedback fault tolerant control for flexible bevel-tip needle based on proportional multiple-integral observer;neural-adaptive quantized consensus tracking control of high-order power-chained nonlinear multi-agent networks with switched dynamics: a specified-time convergence protocol;the path integral motion planning of the cable-driven segmented redundant manipulators;and global information attention based dual-pathway network for oxidized slag segmentation of metal ingot images.

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Hybrid CNN Classifier for Accurate Detection of Oral Cysts in Panoramic Dental Radiograph 9

Hybrid CNN Classifier for Accurate Detection of Oral Cysts i...

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9th International conference on Communication and Electronics Systems, ICCES 2024

作者： Sivagami, S. Senthilvadivu, S. Geetha, P. Yukthavarshika, J. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Computer Science and Engineering Tamil Nadu Chennai India Srm Institute of Science and Technology Department of Computational Intelligence Kattankulathur Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Artificial Intelligence and Machine Learning Tamil Nadu Chennai India

ISBN: (数字)9798350377972

ISBN: (纸本)9798350377972

In dentistry, machine learning approaches play a significant role in the early detection and diagnosis of oral cysts. When planning accurate medical treatment, oral and maxillofacial surgeons can benefit from preoperative detection of these cysts. Surgical planning is directly affected by classifying oral cysts as dentigerous, radicular, ameloblastoma, odontogenic carcinoma, and odontogenic keratocyte. In dentistry, the outcomes of differential diagnosis based solely on imaging are unacceptable. this research proposes a three-step framework for autonomous cyst classification, segmentation, and detection based on a Convolutional Neural Network (CNN). To begin, DENT-CNN, a modified CNN architecture is proposed to classify the oral cyst as normal or abnormal. Second, UNet is a CNN variant used to segment the categorized cyst regions on panoramic dental images. third, the Gray Level Co-occurrence Matrix (GLCM) is combined with CNN to identify segmented cysts as benign or malignant. the proposed work is extensively evaluated using 1500 real-time dental panoramic radiographic images of the oral cyst collected from a dental hospital. To alleviate overfitting, the data augmentation approach is used. the performance of the proposed work is analyzed in terms of a cyst classification rate of 96.8 %, a Dice Score of 96.3 % for cyst segmentation, and an accuracy for the Identification phase of 96.5%. © 2024 IEEE.

关键词： Dentistry

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9th International conference on Variable Neighborhood Search, ICVNS 2023

9th International Conference on Variable Neighborhood Search...

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9th International conference on Variable Neighborhood Search, ICVNS 2023

ISBN: (纸本)9783031344992

the proceedings contain 11 papers. the special focus in this conference is on Variable Neighborhood Search. the topics include: A Basic Variable Neighborhood Search Approach for the Bi-objective Multi-row Equal Facility Layout Problem;A VNS-based Heuristic for the Minimum Number of Resources Under a Perfect Schedule;BVNS for Overlapping Community Detection;a Simulation-based Variable Neighborhood Search Approach for Optimizing Cross-Training Policies;multi-objective Variable Neighborhood Search for Improving software Modularity;An Effective VNS for Delivery Districting;BVNS for the Minimum Sitting Arrangement Problem in a Cycle;Assigning Multi-skill Configurations to Multiple Servers with a Reduced VNS;multi-Round Influence Maximization: A Variable Neighborhood Search Approach.

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Categorization of Alzheimer's Disease and Memory Loss by Using Fusion of Feature Reduction and Kernel SVR 9

Categorization of Alzheimer's Disease and Memory Loss by Usi...

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9th International conference on Communication and Electronics Systems, ICCES 2024

作者： Mariyal, C. Latha, R. Selvi, C. Elango, S. Kirubakaran, J. Praveena, R. Psn College of Engineering and Technology Department of Ece Tirunelveli India Srm Institute of Science and Technology Department of English and Foreign Languages Chennai India Muthayammal Engineering College Department of Ece Namakkal India Cmr University Department of Cse Bangalore India

Physicians often face challenges in determining the significance of a patient9;s memory difficulties. Aging individuals who notice a decline in their memory are frequently worried about the possibility of developin... 详细信息

ISBN: (纸本)9798350377972

Physicians often face challenges in determining the significance of a patient's memory difficulties. Aging individuals who notice a decline in their memory are frequently worried about the possibility of developing Alzheimer's disease (AD). Mild memory Loss is a medical condition where cognitive impairment, typically in the memory domain, is present but does not meet the criteria for dementia. Resting-state functional magnetic resonance imaging (rs-fMRI) is a technique used to assess brain functional abnormalities. In this study, pre-processing is applied to eliminate noise and correct parameter variations in the captured images. Edges are detected, and contours are removed. Regions of grey and white matter, along with gyri and sulci contours, are segmented from the images, and the area and volume of these segmented regions are calculated. the extracted features are then labeled and used in a feature selection process to reduce dimensionality. To categorize Alzheimer's disease (AD), mild cognitive impairment (MCI), and normal cognitive function using rs-fMRI data, a structured approach can be used. A kernel-based tSNE method is proposed for dimensionality reduction. For the classification of AD and mild cognitive impairment (MCI), a polynomial kernel-based Support Vector Regression (SVR) is employed. © 2024 IEEE.

关键词： Neurodegenerative diseases

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A 1-Source 3- φ Boost Transformer-less Multilevel Inverter without Leakage Current 9

A 1-Source 3- φ Boost Transformer-less Multilevel Inverter ...

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9th International conference on Technology and Energy Management, ICTEM 2024

作者： Ardashir, Jaber Fallah Ogly, Aydin Mohammad Ghadim, Hadi Vatankhah Sarhangzadeh, Mitra Azarbaijan, Hossein Khoun Jahan Shotorbani, Amin Mohammadpour Islamic Azad University Tabriz Department of Electrical Engineering Tabriz Branch Tabriz Iran University of Canterbury Department of Civil and Natural Resources Engineering Christchurch New Zealand Azarbaijan Regional Electric Company Tabriz Iran University of Tabriz Faculty of Electrical and Computer Engineering Tabriz Iran

ISBN: (纸本)9798350329797

this paper addresses the common issue of leakage current in transformer-less grid-tied inverters, rendering them unsuitable for photovoltaic (PV) system applications. To overcome this challenge, a 3- φ boost switched capacitor-based inverter is introduced, specifically designed for versatility. the innovative design employs a single dc power source, eliminating leakage current concerns. the paper conducts a thorough examination and discussion of the operational principles and theoretical analysis of the proposed topology. Notably, the inverter structure ensures a consistent dc source for all three phases, with each phase independently powered by a single dc source. this direct connection mitigates leakage current issues, enhancing the inverter's applicability across various scenarios. To achieve a 5-level output voltage in each phase and a 9 -level output voltage in the line voltage, the Sinusoidal Pulse Width Modulation (SPWM) method is employed. Simulation results, conducted in the MATLAB software environment, validate the efficacy of the proposed inverter design. the outcomes demonstrate successful voltage level generation and affirm the elimination of leakage current due to the direct connection of each phase to the dc source. the use of a single dc power source and direct connection to each phase provides a versatile, leakage-free solution for diverse applications, as validated by simulation results in the MATLAB environment. © 2024 IEEE.

关键词： MATLAB

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A Virtual Network Topology Spoofing Defense Method based On DCGAN 9

A Virtual Network Topology Spoofing Defense Method Based On ...

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9th International conference on Computer and Communications, ICCC 2023

作者： Chang, Dexian Yang, Yingjie Information Engineering University Henan Key Laboratory of Information Security Zhengzhou China

ISBN: (纸本)9798350317251

Aiming at network scanning and sniffing attacks, this paper designs an active defense mechanism based on virtual network topology, which generates a large number of random and independent fake networks through generative adversarial networks, and uses the traffic traction capability of software-defined networks to trick attackers into accessing preset defense hosts, making it impossible to detect the real internal network topology, and it is difficult to collect the element information required for attacks, such as key link sets and sensitive server collections. Experiments show that compared with the relevant defense mechanism, the proposed method has obvious advantages in protecting the server response experiment and file transfer rate. © 2023 IEEE.

关键词： Generative adversarial networks

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Plant Disease Classification using Deep Learning Approach (VGG19) 9

Plant Disease Classification using Deep Learning Approach (V...

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9th International conference on Advanced Computing and Communication Systems, ICACCS 2023

作者： Jude Rithik, P. Sandhya Devi, R.S. Medwin Brendan, A. Sugumar, R. Electrical and Electronics Engineering Kumaraguru College of Technology Coimbatore India

ISBN: (纸本)9798350397376

Plant disease classification is a prime research area in precision agriculture. Artificial Intelligence (AI) based automatic disease prediction using machine learning or deep learning models is gaining momentum in recent years to protect sensitive economy crops such as tomato and potato blight at the early stages of the fungal infection. One of the challenges in implementing deep learning framework is limited dataset availability. In this proposed work, VGG-19 a Convolution Neural Network (CNN) model are being used to predict the disease classes based on transfer learning approach. Early detection of diseases aids in minimizing the yield losses by 30 % and CNN based models such as VGG-19 plays a significant role in extracting the low-level spatial information. this VGG-19 is pre-trained on ImageNet dataset with more than thousand classes and CIFAR 100 dataset. this VGG-19 is like VGG-16 with three additional fully connected layers. the knowledge learnt from the benchmarked dataset is applied to the ten classes of diseased tomato leaves. the accuracy metrics are plotted, and the highest accuracy obtained is 94 %. the confusion matrix results are also obtained to validate the performance. © 2023 IEEE.

关键词： Plants (botany)

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Unveiling the Future: Design and Development of an Intelligent Raspberry PI based Smart Mirror Design using Internet of things Assistance 9

Unveiling the Future: Design and Development of an Intellige...

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9th International conference on Science, Technology, engineering and Mathematics, ICONSTEM 2024

作者： Ramya, M. Vishal, M. Varshiga, R. Babu, Tanuha D. Dinakaran, S. Madhana Gopal, S. S.A. Engineering College Department of Ece Chennai India

ISBN: (纸本)9798350365092

Smart mirrors, which are now in development and will play a significant role in future technologies, offer consumers mirror and computer-assisted information services. these systems are able to link to an internet connection and retrieve data from the internet;the onboard microcontroller cards allow them to display this data on the mirror. Using a Raspberry Pi 3 microcontroller card, the researchers were able to build an intelligent mirror system that displays data from several online sources, such as weather reports, current events, user profiles, and camera images. the smart mirror has a built-in microphone, so you can operate some devices just by speaking into it. In order to keep yourself informed about the weather, local news, and other relevant information while you get ready for the day, a smart mirror shows relevant applications. In a clever approach, the mirror will perform the user's thinking. It is a system that can display the current date, time, temperature, and weather data, among other things. One definition of a smart mirror is a bi-directional mirror that also has an integrated screen. the intelligence of the system is built on the Internet of things (IoT), which helps the user and makes them more aware. In order to assess the efficacy of the suggested technique, which is known as Intelligent Raspberry PI based Smart Mirror (IRPISM), it is crossvalidated with the usual model called Arduino Powered Smart Mirror (APSM). this is evident from the results that the model is effective. © 2024 IEEE.

关键词： Mirrors

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