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

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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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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Design Of Robot Motion Planning Algorithm For Wall Following Robot by Ali Hassan, Muhamad Khairul

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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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Human activity recognition via accelerometer and gyro sensors by Tee, Jia Lin

“…To implement the data engineering system proposed, two mobile applications, SensorData and SensorDataLogger with user-friendly interfaces and intuitive functionalities are developed using Java programming language and Android Studio. …”
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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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Design & Development of a Robotic System Using LEGO Mindstorm by Abd Manap, Nurulfajar, Md Salim, Sani Irwan, Haron, Nor Zaidi

“…Since the model is built using LEGO bricks, the model is fully customized, in term of its applications, to perform any relevant tasks. Ultimately, the algorithm development program designed earlier is linked up directly to the robotic model for program implementation and verification. …”
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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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