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Custom Transformer-Based Approach for Enhanced Bengali automatic Speech Recognition 1

Custom Transformer-Based Approach for Enhanced Bengali Autom...

引用

1st international conference on Innovations in Communications, electrical and Computer engineering, ICICEC 2024

作者： Deepa, R. Jayalakshmi, V. Thilakavathy, P. Manikandan, G. Surendran, R. SRM Institute of Science and Technology School of Computing Department of Computing Technologies Chennai India SRM Institute of Science and Technology Department of Computer Science and Applications Ramapuram Chennai India Vels Institute of Science and Engineering Vels Institute of Science Technology and Advanced Studies Chennai India Anna University St. Joseph's College of Engineering Department of Artificial Intelligence and Machine Learning Chennai India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Chennai India

ISBN: (数字)9798350376517

ISBN: (纸本)9798350376517

Automated speech recognition (ASR) systems struggle with Bengali, which is the fifth most spoken language. Bengali has a varied morphology, many dialects, and limited high-quality annotated voice data. Traditional voice recognition techniques work well however struggle with Bengali phonetics and syntax. This method eliminates the need for large amounts of tagged data and the difficulties of differentiating sounds in different languages, both issues are addressed by this procedure. The research in this paper offers an Intellectual Bengali Speech Recognition System using Deep Learning Techniques (IBSRS-DLT). The model in this system uses transformer architecture and attention processes to manage Bengali speech pattern long-range dependencies. The IBSRS-DLT outperforms standard models in recognition accuracy using a pre-trained transformer model modified for phonetic and lexical correctness and fine-tuned on Bengali datasets. After training on a vast Bengali speech corpus, real-world datasets and rigorous simulations confirm the system. IBSRS-DLT can be used for automatic transcription, voice-controlled devices, and Bengali virtual assistants, such applications are efficient and accessible. The simulation showed a considerable boost in recognition speed and a decrease in keyword mistakes compared to current methods. This paper shows that deep learning can solve linguistic issues in ASR systems, enabling scalable regional language detection. © 2024 IEEE.

关键词： Deep learning

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A Survey of Machine Learning Algorithms for Defective Steel Plates Classification 8th

A Survey of Machine Learning Algorithms for Defective Steel ...

引用

8th international conference on computing, control and Industrial engineering, CCIE 2024

作者： Gao, Meiyan Wei, Yuanzhou Li, Zhenglin Huang, Bolin Zheng, Changyang Mulati, Aliya College of Engineering and Computing Florida International University Miami United States Department of Computer Science and Engineering Texas A&M University College Station United States Viterbi School of Engineering University of Southern California CaliforniaCA United States School of Engineering Brown University Rhode Island United States Biological Science Florida International University Florida United States

ISBN: (纸本)9789819769339

This paper aims to explore various classification models and data processing techniques for classifying defects on steel plates. The study is based on a dataset of steel plates with seven different types of defects and seeks to identify the most effective combination of machine learning models and data processing techniques for automatic defect recognition. Key methodologies include data augmentation, feature selection, and dimensionality reduction techniques like SMOTE, PCA, and REF. Various models, including Naive Bayes, Logistic Regression, SVM, Decision Trees, Random Forests, and Neural Networks, are evaluated. The results indicate that Hyperparameter Tuning and REF significantly enhance model performance, with Random Forest and Neural Networks achieving the highest accuracy. Random Forest, due to its interpretability and efficiency, is identified as the best model for this classification task. This research lays a foundation for applying machine learning algorithms in industrial defect detection, promising improvements in automation, efficiency, and production quality. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Dimensionality reduction

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Design of automatic Power Generation control of Power System Based on MPC 5

Design of Automatic Power Generation Control of Power System...

引用

5th international conference on Smart Grid and Energy engineering, SGEE 2024

作者： Jing, Shaopeng Peng, Yu Changsha University of Science and Technology Department of Electrical Engineering Hunan Changsha China

ISBN: (纸本)9798331530686

The power system frequency stability is the basis of its safe and reliable operation, this paper puts forward the model prediction control (MPC) system into power system frequency control, with the help of MATLAB/Simulink structures with frequency deviation as the input MPC system, simulation results show that the frequency control deviation gradually tend to zero, it also proves that applying this method to frequency control in power systems can simply and efficiently ensure the matching of system output and load power, reduce operating costs, and have considerable economic benefits. © 2024 IEEE.

关键词： Frequency stability

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Design of Transcutaneous electrical Nerve Stimulator Machine for Chronic Low Back Pain 5

Design of Transcutaneous Electrical Nerve Stimulator Machine...

引用

5th international conference on Circuits, control, Communication and computing, I4C 2024

作者： Moyya, Priscilla Dinkar Bindu, Katikala Hima Kumar, N Kiran Reddy, S Venkateswarlu Manikanta, G. Rahul, S.G. Scai Vit Bhopal University Division of Ai Madhya Pradesh India Vignan's Foundation for Science Technology & Research Dept. of Biomedical Engineering Vadlamudi India M S Ramaiah Institute of Technology Dept. of Electrical Engineering Bengaluru India Annamacharaya University Dept. of Electrical Engineering Rajampet India Dayananda Sagar College of Engineering Electrical and Electronics Engineering Bengaluru India School of Electronics Engineering Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology India

ISBN: (纸本)9798331528539

Using electrical current to stimulate and excite a living body's nervous system is known as Transcutaneous electrical Nerve Stimulation(TENS). The word electrotherapy has been used to describe a wide range of medical procedures, including shock therapy and the use of devices like deep brain stimulators for neurological disorders. The use of electrical current to accelerate the process of healing of wounds has also been included in this definition. This treatment also belongs to alternative medications in particularly for spinal cord and remedies because it is non-pharmacological. It acts as a nonphar-macological therapy that minimizes hyperalgesia by descending inhibitory mechanisms in the nervous system's center, which in turn stimulates a complicated neural network that decreases pain. To control pain, TENS devices apply electrical current through electrodes applied to the skin to provide a non-invasive nerve stimulation system that can reduce acute and chronic pain. This paper describes the development, implementation, and maintenance of a system that may be used to treat illnesses at a relatively low cost. The user can also vary the system's frequency from low to high depending on the intended purpose. © 2024 IEEE.

关键词： Electrotherapeutics

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Development of a Face Recognition Door Lock System with OpenCV Integration for Securing Residential Properties 15

Development of a Face Recognition Door Lock System with Open...

引用

15th international conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Haque, Samirul Sarker, Biplob Mawla, Atm Rafiqul Reza, Md Naeem Riya, Aparna Sarker American International University-Bangladesh Electrical and Electronics Engineering Dhaka Bangladesh Brac University Electrical and Electronic Engineering Dhaka Bangladesh International Islamic University Chittagong Electrical and Electronic Engineering Chittagong Bangladesh Eastern University Electrical and Electronics Engineering Dhaka Bangladesh Brac University Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350370249

The Face Recognition Door Lock System project presents a novel strategy for enhancing home security by combining face recognition technology with automated access control features. This technique is intended to be used in order to implement the system. It is the intention of this system to enhance security standards while simultaneously providing a means of property entrance that is both user-friendly and efficient. Through the use of face recognition algorithms, other hardware components such as a camera sensor and an Arduino Uno microcontroller, and software programs such as OpenCV and Python programming, the system is able to reliably identify authorized persons and manage door access based on facial features. The project has an emphasis on the development of security, convenience, and system operability in order to adapt to the changing expectations of modern homeowners who are looking for sophisticated access management solutions. © 2024 IEEE.

关键词： Locks (fasteners)

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Voice Bluetooth control Car 5

Voice Bluetooth Control Car

引用

5th international conference on Computer engineering and Intelligent control, ICCEIC 2024

作者： Chen, Zhiwen Chen, Chuixin School of Electrical Engineering China University of Mining and Technology Xuzhou China School of Intelligent Manufacturing and Electrical Engineering Guangzhou Institute of Science and Technology Guangzhou China

ISBN: (纸本)9798331507992

With the continuous development of technology, speech recognition and control are becoming increasingly important. The user sends a voice signal, and the system recognizes it, extracts valid commands from the voice, and transmits the commands to the car via Bluetooth. After recognizing the command, the car completes functions such as starting, forward, backward, left turn, right turn, acceleration, deceleration, stop, turning on lights, turning off lights, and automatic obstacle avoidance. The system can also pair with the Bluetooth on the car through a mobile phone and Bluetooth to control the car. For the convenience of information display, the car is equipped with LCD 12864 and ultrasonic distance sensor, which can avoid obstacles during movement. This system has a good reference value for the development of smart homes, industrial automation, robot assisted rescue, etc. © 2024 IEEE.

关键词： Bluetooth

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Research on the stroke control algorithm of agricultural push rod motor

Research on the stroke control algorithm of agricultural pus...

引用

2024 international conference on Electronics, electrical and Information engineering, ICEEIE 2024

作者： Liu, Yong Wang, Yunsheng Hu, Wenwen Xu, Shipu Zhou, Zhiwen An, Mingming Guo, Xiaokun Jiang, Wenfei Institute of Agricultural Science and Technology Information Shanghai Academy of Agricultural Sciences Shanghai201403 China Shanghai Engineering and Technology Research Center for Digital Agriculture Shanghai201403 China

ISBN: (数字)9781510686809

ISBN: (纸本)9781510686793

This paper studies and realizes a low-cost stroke control algorithm for agricultural push rod motor. The algorithm is based on the hall counting principle. By adding two hall sensors to the ordinary agricultural push rod motor, the motor can output two square wave signals when it is running. When the motor is running, each revolution will trigger a hall sensor to output a pulse signal. The two signals have a phase difference of 90 degrees. Through the phase relationship of the two signals, the forward and reverse state of the motor can be judged, and the pulse signal can be counted by adding or subtracting. The algorithm realizes the automatic control of motor stroke according to the user set stroke percentage, hall count value and total stroke hall count value. This algorithm has the advantages of stable and reliable stroke control, low cost, suitable for high humidity and dusty environment in agriculture, and can be applied to the on-site automatic control of related equipment in facility agriculture and field agriculture, as well as remote precision control based on Agricultural Internet of things. © 2024 SPIE.

关键词： Hall effect transducers

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Extending Internet of Things Systems with Fog and Edge computing 30

Extending Internet of Things Systems with Fog and Edge Compu...

引用

30th IEEE international conference on engineering, Technology, and Innovation

作者： Dumitru, Marian Cosmin Moisescu, Mihnea Alexandra Pietraru, Radu Nicolae Pop, Eugen Natl Univ Sci & Technol Fac Automat Control & Comp Politehn Bucuresti Bucharest Romania

ISBN: (纸本)9798350362442;9798350362435

In recent years, whether we are talking about industrial implementations or whether we are talking about products offered to the masses, there is an accelerated trend of the appearance of IoT devices, devices that collect information and, depending on their specifics, can make certain decisions in the process. This increase automatically leads to the generation of more generated data that must be sent for processing, analyzed, stored, a certain decision being made based on the result of the analysis. This process can be long, the duration strictly determined by the volume of data and the performance of the Cloud infrastructure. Fog and Edge computing has come to our aid with an innovative solution, acting as an additional layer between IoT and Cloud devices. This layer aims to reduce the response time by analyzing the data at the edge of the network, in this way it is no longer necessary to send all the information directly to the Cloud. Whether we are talking about smart cities, the health field or the industrial fields, the presence of IoT devices shows the usefulness of the need to implement Fog and Edge systems. Starting from this growth in the IoT field, the authors wish through this article to analyze the existing implementations that use Fog and Edge computing, the existing architectural levels, the analysis of the areas that present vulnerabilities, as well as the possible improvements that can be added to make the processes more efficient.

关键词： Fog computing Edge computing Internet of Things (IoT) Cloud

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Application of ANFIS Systems in Mill Process control in Thermal Power Plants 11

Application of ANFIS Systems in Mill Process Control in Ther...

引用

11th international conference on electrical, Electronic and computing engineering, IcETRAN 2024

作者： Stojić, Aleksa Marković, Andela Kvaščev, Goran University of Belgrade School of Electrical Engineering Dept. of Signals and Systems Belgrade Serbia

ISBN: (纸本)9798350386998

The daily increase in electricity consumption necessitates continuous expansion and increase of production capacities. Although the world is shifting toward renewable energy sources, fossil fuel power plants still maintain their dominance, continuously improving and expanding their capacities. With the aim of extracting the maximum amount of electrical energy from coal, many advanced methods for combustion control in thermal power plant furnaces have been developed. However, few of these methods take into consideration the condition of the coal mills as a parameter, instead leaving this assessment to operators based on their personal experience. If an incorrect assessment of the mills' condition is made, it could reduce the potential capacity of the entire plant or worse, endanger the mill itself. With the intention of minimizing human error and achieving maximum production capacity, the development of an appropriate algorithm is being considered. The development of the algorithm, which relies on expert knowledge, involved considering neuro-fuzzy systems for decision-making to preserve specific methods of thinking and learning characteristic of individuals. © 2024 IEEE.

关键词： Coal

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Brain Tumor Detection using Optimized Stochastic Gradient Descent Function

Brain Tumor Detection using Optimized Stochastic Gradient De...

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2024 international conference on electrical, Electronics and computing Technologies, ICEECT 2024

作者： Mishra, Annu Chaturvedi, Ravi Prakash Sharma, Hirdesh Kumar, Prashant Asthana, Sameer Parashar, Mayank Sharda School of Engineeringand Technology Department of Computer Science and Engineering Greater Noida India Sharda School of Engineeringand Technology Department of Computer Science and Applications Greater Noida India JEMTEC Department of Computer Science and Engineering Greater Noida India ITS Engineering College Department of Computer Science and Engineering Greater Noida India GNIOT Department of Computer Science and Engineering Greater Noida India

ISBN: (纸本)9798350378092

The learning rate of a CNN determines the efficiency of the neural network. In brain tumor detection, the learning rate and the optimization function plays a key role in deciding the final output. The Optimized Stochastic Gradient Descent (OSGD) optimizer giver better result in terms of Accuracy, Recall and other determining factors. We have also compared the results obtained with other optimizers and it could be clearly stated that our proposed model. The OSGD optimizer controls the maxima and minima, and move the near optimum solution buy controlling the learning rate. So via this method we can control our right *** we detect our object in les error. © 2024 IEEE.

关键词： Stochastic systems

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