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All Journal Journal of Computer Science Advancements Journal of Moeslim Research Technik Journal of Tecnologia Quantica
Snyder Bradford
International University of Monaco
Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Physics

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Optimizing Renewable Energy System Performance with Real-Time Monitoring Techniques Deng Jiao; Bouyea Jonathan; Snyder Bradford
Journal of Moeslim Research Technik Vol. 1 No. 1 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/technik.v1i1.830

Abstract

Research Background: In the face of climate change challenges and the need for sustainable energy, renewable energy systems are becoming increasingly important. However, to maximize the efficiency and performance of renewable energy systems, monitoring techniques are needed that can provide real-time information about the operational conditions of the system. Research Objectives: This research aims to optimize the performance of renewable energy systems through the application of real-time monitoring techniques. This is done by utilizing data obtained directly from sensors connected to the energy system. Research Methods: The research methods used include literature study, system requirements analysis, real-time monitoring infrastructure design, prototype implementation, and functionality testing. The collected data was analyzed to evaluate the system performance and effectiveness of real-time monitoring techniques. Research Results: The implementation of real-time monitoring techniques successfully improves the performance of renewable energy systems by providing accurate and timely information about operational conditions. This allows for more efficient management and responsiveness to changes in environmental conditions or energy demand. Research Conclusion: The application of real-time monitoring techniques can significantly improve the efficiency and performance of renewable energy systems. With real-time information, better decision-making can be made, enabling more effective management and responsiveness to system and environmental dynamics.
The Role of Mechanical Engineering in the Development of Environmentally Friendly Electric Vehicles Zhang Wei; Snyder Bradford; Xie Guilin
Journal of Moeslim Research Technik Vol. 1 No. 3 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/technik.v1i3.941

Abstract

In an effort to address environmental issues caused by greenhouse gas emissions and air pollution from fossil fuel vehicles, the development of electric vehicles is a promising solution. Electric vehicles offer a more environmentally friendly alternative and have the potential to reduce dependence on fossil fuels. The role of mechanical engineering in the innovation and development of electric vehicle technology is crucial to achieve higher efficiency and minimal environmental impact. This research aims to analyze the contribution of mechanical engineering in the development of environmentally friendly electric vehicles, including the identification of technologies and methods used to improve the performance and efficiency of electric vehicles. This research uses a qualitative method with a literature study approach and comparative analysis. Data were collected from various scientific and technical sources, including relevant journals, books, and industry publications. Technical innovations in the design of electric motors, energy storage systems, and materials used in electric vehicles were analyzed. The results show that mechanical engineering has an important role in various aspects of electric vehicle development. Innovations in electric motor design such as the use of permanent magnet synchronous motors (PMSM) and induction motors have improved efficiency and performance. The development of batteries with high energy density and good thermal management is also key in improving the range and reliability of electric vehicles. In addition, the use of lightweight and strong materials in vehicle construction contributes to reducing energy consumption. Mechanical engineering plays a crucial role in the development of more efficient and environmentally friendly electric vehicles. Through various technical innovations, electric vehicles can be a sustainable solution for future transportation, with great potential to reduce negative impacts on the environment. The implementation of new technologies in motor design, energy storage systems, and vehicle materials are decisive factors i
Quantum Optics Research Prospects: Transformation Towards Faster Quantum Computing Uwe Barroso; Mahon Nitin; Snyder Bradford
Journal of Tecnologia Quantica Vol. 1 No. 2 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/quantica.v1i2.895

Abstract

Advancements in quantum computing have become a primary focus in modern computer science. However, one of the major challenges in creating more powerful quantum computers is developing more stable and efficient qubits. In this context, research in quantum optics offers game-changing solutions. By leveraging quantum physics principles and quantum optics technology, this research aims to transform the quantum computing landscape by creating more stable and faster qubits. The goal of this study is to explore the potential of quantum optics in creating more stable and efficient qubits for quantum computing. This research method involves a combination of experimental and theoretical approaches. Data obtained from these experiments will be analyzed using advanced theoretical methods to understand the quantum properties of the produced qubits. The results indicate that the quantum optics approach can be key in creating more stable and faster qubits for quantum computing. Experiments have successfully demonstrated better control over qubits in photonic systems and compressed matter, producing qubits with higher reliability. Theoretical analysis also reveals a deeper understanding of the quantum properties of the produced qubits, opening the door for further development in this field. The conclusion of this research shows that quantum optics has great potential to transform quantum computing by creating more stable and faster qubits. By continuing to develop quantum optics technology and deepening the understanding of quantum properties of compressed matter and photonic systems, quantum computing can be taken to a new level.
Implementation of Deep Learning in a Voice Recognition System for Virtual Assistants Apriyanto Apriyanto; Rohmat Sahirin; Snyder Bradford
Journal of Computer Science Advancements Vol. 2 No. 6 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v2i6.1533

Abstract

Voice recognition technology has become a vital component in virtual assistants, enabling more natural and efficient user interactions. However, traditional voice recognition systems face challenges in accurately interpreting diverse accents, dialects, and background noise, which can limit their usability. This study investigates the implementation of deep learning techniques to improve the accuracy and adaptability of voice recognition systems within virtual assistant applications. The research aims to enhance voice recognition performance by leveraging deep learning models that can process complex speech patterns and adapt to varied linguistic nuances. A convolutional neural network (CNN) architecture combined with recurrent neural networks (RNN) was used to train the voice recognition model on a large, diverse dataset of audio samples. The dataset included multiple languages, accents, and noisy environments to test the robustness of the model. Results indicate a 25% improvement in word error rate (WER) and a significant increase in recognition accuracy across diverse voice inputs compared to traditional voice recognition systems. The model demonstrated high adaptability, accurately interpreting speech in varying acoustic conditions, thus improving user experience with virtual assistants. These findings suggest that deep learning can significantly enhance voice recognition systems, offering more reliable performance in real-world applications. Implementing deep learning models in voice recognition systems can bridge the gap between human and machine communication, making virtual assistants more accessible and user-friendly.
Co-Authors Apriyanto Apriyanto Bouyea Jonathan Deng Jiao Mahon Nitin Rohmat Sahirin Uwe Barroso Xie Guilin Zhang Wei