Search Results - (( chain integration learning algorithm ) OR ( java application path algorithm ))

Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

“…In creating this application, NetBeans IDE 6.5and Java Micro Edition (Java ME) are used. …”
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Visdom: Smart guide robot for visually impaired people by Lee, Zhen Ting

“…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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A review and comparative analysis of predictive models for supply chain demand forecasting by Ibrahim Ahmed Omer, Rehab, Hassan, Raini, S. Abd. Aziz, Madihah

“…This study reviews key techniques, including statistical time-series models, supervised and unsupervised learning algorithms, ensemble methods, and deep learning architectures. …”
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Navigating challenges and opportunities of machine learning in hydrogen catalysis and production processes: Beyond algorithm development by Salehmin M.N.I., Tiong S.K., Mohamed H., Umar D.A., Yu K.L., Ong H.C., Nomanbhay S., Lim S.S.

“…With the projected global surge in hydrogen demand, driven by increasing applications and the imperative for low-emission hydrogen, the integration of machine learning (ML) across the hydrogen energy value chain is a compelling avenue. …”

The duality of technological innovation and dynamic capabilities: the micro-foundation of China's construction machinery industry's rise up the global value chain by Xia, Weifu, Alwie, Aryaty, Taasim, Shairil Izwan, Jin, Wong Tze, Naning, Fatin Hana

“…Based on organizational learning theory and dynamic capability perspective, this study constructs a theoretical framework of dual integration of technological innovation (exploratory innovation and pioneering innovation) and dynamic capability, and explores its impact mechanism on the global value chain upgrading of Chinese construction machinery enterprises. …”
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Automated rockmelon grading technology / Chua Hong Kheng ... [et al.] by Chua, Hong Kheng, Selvaraju, Haarinesh, Taufik, Intan Amani, Sahabudin, Muhammad Afiq

“…Moreover, the system's scalability and adaptability, facilitated by customisable options, cater to stakeholders' diverse scales and requirements across the agricultural supply chain, from farms to distributors. The technology provides real-time data insights and adaptive learning capabilities by leveraging sensors and machine learning (ML) algorithms, enabling continuous refinement and optimisation of grading processes. …”
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A Bio-Inspired Behavior-Based Hybrid Framework for Ransomware Detection by Mohammed A. F. Salah, Mohd Fadzli Marhusin, Rossilawati Sulaiman

Non-halal gelatin prediction: a comparative machine learning analysis between OPLS–DA and ANN models by Mohd Hafis Yuswan, Norazlina Ali, Syaiful Izwan Ismail, Basyirah Muda, Mohamad Habeeb Helmy Idris, Mazidah Md Nor, Nur Suhadah Nawi, Muhamad Shirwan Abdullah Sani, Lai, Kok Song

“…These findings can be integrated with existing analytical methods to complement the halal analysis, thus ensuring product integrity and upholding halal sanctity.…”
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Towards paddy rice smart farming: a review on big data, machine learning, and rice production tasks by Rayner Alfred, Joe Henry Obit, Christie Chin Pei Yee, Haviluddin Haviluddin, Yuto Lim

“…Big Data (BD), Machine Learning (ML) and Internet of Things (IoT) are expected to have a large impact on Smart Farming and involve the whole supply chain, particularly for rice production. …”
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Non-halal gelatin prediction: a comparative machine learning analysis between OPLS–DA and ANN models by Yuswan, Mohd Hafis, Ali, Norazlina, Ismail, Syaiful Izwan, Muda, Basyirah, Helmy Idris, Mohamad Habeeb, Md Nor, Mazidah, Nawi, Nur Suhadah, Abdullah Sani, Muhamad Shirwan, Kok Song, Lai

“…These findings can be integrated with existing analytical methods to complement the halal analysis, thus ensuring product integrity and upholding halal sanctity…”
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Non-halal gelatin prediction: a comparative machine learning analysis between OPLS–DA and ANN modelsramalan gelatin tidak halal: perbandingan analisis pembelajaran mesin antara mod... by Yuswan, Mohd Hafis, Ali, Norazlina, Ismail, Syaiful Izwan, Muda, Basyirah, Helmy Idris, Mohamad Habeeb, Md Nor, Mazidah, Nawi, Nur Suhadah, Abdullah Sani, Muhamad Shirwan, Lai, Kok Song

“…These findings can be integrated with existing analytical methods to complement the halal analysis, thus ensuring product integrity and upholding halal sanctity.…”
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Leaf condition analysis using convolutional neural network and vision transformer by Yong, Wai Chun, Ng, Kok Why, Haw, Su Cheng, Naveen, Palanichamy, Ng, Seng Beng

“…Through the use of a hybrid deep learning model that combines vision transformer and convolutional neural networks for classification, the algorithm can be optimized. …”
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Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei by Chen , Shilei

“…By integrating ISMA, both supervised and unsupervised machine learning algorithms were investigated to develop real-time damage identification schemes. …”
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Artificial intelligence revolutionising the automotive sector: A comprehensive review of current insights, challenges, and future scope by Hossain, Md Naeem, Rahim, Md. Abdur, Rahman, Md Mustafizur, D., Ramasamy

“…The review highlights that AI has significantly expedited the development of autonomous vehicles regarding navigation, decision-making, and safety features through the use of advanced algorithms and deep learning structures. Furthermore, it identifies advanced driver assistance systems, vehicle health monitoring, and predictive maintenance as the most impactful AI applications, transforming operational safety and maintenance efficiency in modern automotive technologies. …”
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