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检索条件"任意字段=2023 International Conference on Computer Science and Automation Technology, CSAT 2023"

共 68829 条记录，以下是941-950 订阅

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Speech Recognition System for Upper-Limb Impairment: A Text Editor for Programming via Voice 2

Speech Recognition System for Upper-Limb Impairment: A Text ...

引用

2nd international conference on automation, Computing and Renewable Systems, ICACRS 2023

作者： Rampriya, R.S. Dharshan, R. Santhosh, S. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamilnadu Vellore India Department of Computer Technology Madras Institute of Technology Tamilnadu Chennai India

ISBN: (纸本)9798350340235

Programming is one of the most important skills to learn for the present and future generations. However, those with hand disabilities may find it difficult to program with a traditional keyboard and mouse. Disabled people would greatly benefit from assistive technology that allows them to use their voices to control computers. The existing system recognizes user input as voice and translates it into a program. However, the existing system only recognizes a limited number of keywords in a programming language. It would also be difficult to debug errors if the voice was misinterpreted. Our suggested work in speech recognition using natural language processing (NLP) would perform better than the previously available systems. It is possible to build a foundation for programming without a keyboard by creating tools that use a publicly accessible speech recognition API. Voice control of the user interface for program execution and code debugging would also be quite beneficial. This can be done with the help of modules such as Pynput. Keyboard, PyAutoGUI, which can simulate mouse cursor movements and clicks as well as keyboard button presses. The accuracy of our proposed system is 87%. When converting voice commands to text, the Word Error Rate (WER) is 18%. © 2023 IEEE.

关键词： Python Speech Recognition Speech-to-Text Vocal Programming

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An Innovation of Differential Unit Tests Based Smart Industrial automation Software Debugging Tool 2

An Innovation of Differential Unit Tests Based Smart Industr...

引用

2nd IEEE international conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Rengarajan, A. Raja Praveen, K.N. Department of Computer Science and It Bangalore India Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350347456

The Differential Unit Tests Based Smart Industrial automation Software Debugging Tool is a new and powerful tool designed to make debugging industrial automation software easier and faster. It uses a combination of differential unit tests, a debugging engine, and a graphical user interface (GUI) to help developers quickly locate and fix bugs in their software. Differential unit tests are a type of test that compares the differences between two versions of the same software. They can help identify any subtle changes that may have occurred since the last version was tested. This is especially useful when debugging industrial automation software, which often contains complex logic and calculations that can be difficult to trace. The debugging engine is the core of the tool and is responsible for analyzing the results of the differential unit tests. It uses a variety of algorithms to identify any potential errors or discrepancies. The debugging engine is also responsible for providing feedback to the developers so they can quickly locate and fix any issues. The GUI is the user interface of the tool and provides developers with an easy way to view and interact with the results of the differential tests. It allows developers to quickly identify any problems in their software and make the necessary changes. © 2023 IEEE.

关键词： Graphical user interfaces

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A Stuxnet-style malware propagation modeling study based on Tesla autonomous vehicles 3

A Stuxnet-style malware propagation modeling study based on ...

引用

3rd international conference on computer technology, Information Engineering, and Electron Materials, CTIEEM 2023

作者： Wang, Junling Chang, Xinxin Zhong, Lei Zeng, Kaifa School of Information Engineering Jiangxi University of Science and Technology Ganzhou China

ISBN: (纸本)9781510672925

Autonomous vehicles are the core of future smart transportation, and Tesla is a leader in the field. As vehicles become intelligent, cyber attack defense becomes a concern. Tesla Autonomous vehicles may be challenged by Stuxnet-style malware, whose self-replication and propagation capabilities may threaten transportation security. This study proposes a spatiotemporal mathematical model for such malware. Based on computer virus propagation dynamics, it is combined with Tesla Autonomous vehicles for the first time. The propagation characteristics of the malware are analyzed, and scientific recommendations are provided for future prevention. © 2024 SPIE.

关键词： Autonomous vehicles

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A Reliability Oriented Method for Optimal Placement of Sectionalizing Switches Using BPSO 17

A Reliability Oriented Method for Optimal Placement of Secti...

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17th international conference on Protection and automation in Power System, IPAPS 2023

作者： Fayyazi, Saeed Azad-Farsani, Ehsan Isfahan University of Technology Golpayegan College of Engineering Department of Electrical and Computer Engineering Golpayegan Iran

ISBN: (纸本)9798350311532

Sectionalizing switches and lines play an essential role in improving the performance of the distribution automation system as well as reducing the outage duration of power grid customers. The operation of the sectionalizing switches and whether the lines are energized or de-energized are also dependent on each other. Considering the structural complexities related to the mathematical modeling of such problems, optimizing the planning and performance of switches and lines usually requires the use of heuristic and meta-heuristic approaches or oversimplification of network complex topology. To deal with such issues, this research presents an efficient computational model for reliability-based simultaneous switching in distribution networks with complex topologies. © 2023 IEEE.

关键词： Electric power distribution

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A Novel Approach to Degin Home automation using IoT Applications

A Novel Approach to Degin Home Automation using IoT Applicat...

引用

2023 international conference on Advancement in Computation and computer Technologies, InCACCT 2023

作者： Dubey, Parul Chourasia, Harshita Ghode, Shilpa G H Raisoni College of Engineering Department of Artificial Intelligence Nagpur India G H Raisoni College of Engineering Department of Information Technology Nagpur India

ISBN: (纸本)9798350396485

The design of home automation systems is getting more challenging as more and more people adopt new technologies. There is still a significant amount of work to be done before end users will have full control over the monitoring and programming capabilities of their own houses. There may be a need for a self-sufficient and scalable household system that is able to support a diverse collection of appliances, tools, and pieces of technology. This article demonstrates how apps for the Android operating system may be used to control and monitor home appliances from a distant location. Those who are unable to move without the use of a wheelchair would benefit tremendously from this. The practical goal of this research is to build an android home automation system that is capable of existing in both virtual and real environments. Orders are sent from an Android phone to a nodeMCU for all of the home appliances to function properly. The key purposes of this system are the control of the lighting and fans, as well as the detection of smoke in the case that there is a fire. We also compare the proposed design with the existing models and fund that this is much cheaper with no compromise in the features of the system. © 2023 IEEE.

关键词： Microcontrollers

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Bangla Malicious Comment Detection in Social Media Posts Using Ensemble Learning 26

Bangla Malicious Comment Detection in Social Media Posts Usi...

引用

26th international conference on computer and Information technology, ICCIT 2023

作者： Gupta, Asmita Das Huda, Moinul Uddin, Mohammed Nazim East Delta University Department of Computer Science and Engineering Chattogram Bangladesh

ISBN: (纸本)9798350359015

Information exchange and the growing usage of social media have greatly benefited human beings. However, social media often has a negative effect on freedom of speech and helps promote hatred, crimes, racial profiling, misogyny, and bullying. While reflecting public opinion and allowing for constructive criticism or admiration, the comment box on public websites can be seen by some as a platform to use obscene and abusive language without any consequences. It is considerably more difficult to identify malicious text in Bengali. In the age of technological automation, manually reviewing and eliminating offensive texts from publicly accessible websites may become tiresome. In this study, we used several machine learning algorithms and ensemble methods for identifying Bangla malicious text. We created a dataset by taking Bangla comments from Facebook and analyzed the effectiveness of different machine learning algorithms and ensemble methods in detecting malicious text accurately. According to the results of our tests, XGBoost, an ensemble technique, performed the best, with 70.23% accuracy in detecting malicious text. © 2023 IEEE.

关键词： Bangla Text Malicious Comment Detection social media XGBoost

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Big Data Analytics on Twitter Sentiments in Cloud Environment: A Review

Big Data Analytics on Twitter Sentiments in Cloud Environmen...

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2023 international conference on IoT, Communication and automation technology, ICICAT 2023

作者： Kumar, Durgesh Dwivedi, Rajendra Kumar Madan Mohan Malaviya University of Technology Dept. of Information Technology and Computer Application Gorakhpur India

ISBN: (纸本)9798350302820

The Internet plays a significant part in the digital world. With the expanding use of web and online applications, different ventures go to huge information answers for adapt up to the evolving request. In this large information period, information is the most important element as it is mainly utilized by organizations for future expectation and decision making. The internet has a seriously advanced a clever way for individuals to communicate their perspectives and suppositions about various themes, patterns and issues. The opinion examination recognized the sensations of client about a few items, subjects into three preset classes: positive, negative or impartial alongside the issue of mining. This paper presents a study on big information analytics on twitter opinion in cloud climate and how huge information controls a lot of information. This paper presents a concise investigation of methodologies which have been utilized in huge information analytics on twitter opinion in cloud climate. © 2023 IEEE.

关键词： Big data

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Research on Multi-Model Fusion Method for Similar Multi-domain 5

Research on Multi-Model Fusion Method for Similar Multi-doma...

引用

5th international conference on Robotics and computer Vision, ICRCV 2023

作者： Zhao, Junhua Song, Qingzeng Xue, Yongjiang Yu, Jing School of Computer Science and Technology Tiangong University Tianjin China School of Computer Science and Technology Tiangong University Haihe Lab of ITAI Tianjin China School of Telecommunication Engineering Beijing Polytechnic Beijing China

ISBN: (纸本)9798350326369

In order to improve the classification accuracy of test samples from different datasets in multi-domain image classification, this paper proposes a multi-domain sample classification method based on Baidu AI open platform image recognition and multi-model fusion. The classification task is divided into two steps: first, the domain to which the sample belongs is determined based on the predicted label and its probability output by the Baidu API, and then the deep learning model trained on that domain is used to predict the label of the sample. The effectiveness of the proposed method is verified through extensive experiments on three public datasets: Cifar-10, Cifar-100, and Mini-ImageNet. In addition, compared with existing algorithms, the proposed method shows significant improvements in classification performance. © 2023 IEEE.

关键词： Image classification

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Research on automatic generation algorithm of duct system based on secondary development of Revit 4

Research on automatic generation algorithm of duct system ba...

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4th international conference on Artificial Intelligence and Electromechanical automation, AIEA 2023

作者： Han, Fengyi Wang, Kaixiang Kong, Dejun Du, Fei Zhu, Zhihan BIM Institute of Technology and Industry Changchun Institute of Technology Changchun130012 China

ISBN: (纸本)9781510666412

In the design and modeling process of air duct system, due to the large number of pipes and the rich types of pipe fittings, it is easy to cause problems such as low modeling efficiency and repetitive work, and an intelligent algorithm for automatically generating the BIM model of air duct system is proposed to solve the above problems;This algorithm is based on the Revit secondary development program interface and LibreDWG third-party class library, uses the C # object-oriented programming language, automatically identifies the duct information on the CAD layer by calling the relevant functions, and automatically generates the BIM model of the duct through the algorithm calculation and processing, thus realizing intelligent modeling. It is verified that the algorithm can extract various parameters of the duct model, accurately locate the duct coordinates, and automatically generate duct connectors at the intersection of the ducts, effectively improving the efficiency of the designers in modeling. © 2023 SPIE.

关键词： computer aided design

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Explainable Artificial Intelligence Techniques for Image Classification Models in Diverse Domains 7

Explainable Artificial Intelligence Techniques for Image Cla...

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2023 7th international conference On Computing, Communication, Control And automation, ICCUBEA 2023

作者： Joshi, Pranjali P. Bagade, Anant M. SCTR's Pune Institute of Computer Technology Department of Computer Engineering Pune India SCTR's Pune Institute of Computer Technology Department of Information Technology Pune India

ISBN: (纸本)9798350304268

Over the past few decades, Deep Learning (DL), which is a subpart of Machine Learning (ML), has gained recognition as the dominant technique in diverse domains such as computer Vision, Natural Language Processing, and Image Recognition. However, despite the exceptional performance of DL models, they are often referred to as of 'Black Box' nature, due to their limited ability to explain the decisions. This has led to a need for explainability of DL models. Therefore to address this issue of lack of explainability in DL models, Explainable Artificial Intelligence (XAI) techniques have been improving in recent era. Unlike DL, XAI has the ability to provide both decision-making and model explanations for data. This research review comprises articles that utilize XAI techniques for image classification tasks. The purpose of this paper is to showcase the utility of the most recent XAI techniques employed in Image Classification Models (ICM). This paper will assist researchers to develop a better intepretation of XAI techniques for image classification as well as related challenges and future research directions. © 2023 IEEE.

关键词： Deep Learning (DL) Explainable Artificial Intelligence (XAI) Image Classification Model (ICM) Machine Learning (ML)

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