Search Results - (( variable learning content algorithm ) OR ( java application mining algorithm ))

Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

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

“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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A web-based implementation of k-means algorithms by Lee, Quan

“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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Classification model for chlorophyll content using CNN and aerial images by Wagimin, Mohd Nazuan, Ismail, Mohammad Hafiz, Mohd Fauzi, Shukor Sanim, Seng, Chuah Tse, Abd Latif, Zulkiflee, Muharam, Farrah Melissa, Mohd Zaki, Nurul Ain

“…The chlorophyll content is also a continuous number of data type, leading to a regression approach when developing the deep learning model. …”
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Predicting motorcycle customization preferences using machine learning by Saputra, Ananta, Utoro, Rio Korio, Roedavan, Rickman, Soegiarto, Duddy, Moorthy, Kohbalan, Pratondo, Agus

“…A dataset comprising 292 respondents was compiled, capturing variables such as age, social environment, financial capacity, and exposure to automotive communities and content. …”
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Crossover and mutation operators of genetic algorithms by Lim, Siew Mooi, Md. Sultan, Abu Bakar, Sulaiman, Md. Nasir, Mustapha, Aida, Leong, Kuan Yew

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A preliminary study of difficulties in learning java programming for secondary school by Majalin, M., Aslina Baharum, Ismail, R., Ismail, I., Ervin Gubin Moung, Noor, N.A.M.

“…Based on the study conducted using an online survey with 37 respondents, results indicated that they faced difficulties in various subtopics of programming from an easy to complex concept based on the scope of learning content they have learned. From the process of computational thinking techniques, algorithm concepts, declaring constant and variable, control structures, search and sorting approach, and several more, these subtopics of programming were hard for some of the respondents. …”
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Revolutionizing video analytics: a review of action recognition using 3D by Jeddah, Yunusa Mohammed, Hassan Abdalla Hashim, Aisha, Khalifa, Othman Omran, Ibrahim, Adamu Abubakar

“…It also addresses the practicalities of implementing action recognition algorithms in real-world situations, which include tools like deep learning frameworks, pre-trained models, open-source libraries, cloud services, GPU acceleration, and evaluation metrics. …”
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Machine learning model to predict the contact of angle using mineralogy, TOC and process parameters in shale by Ameenuddin Irfan, S., Fadhli, M.Z., Padmanabhan, E.

“…The developed model has successful in prediction the contact angle for different input variables of the machine learning model with high r squared values. …”
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Investigation of machine learning models in predicting compressive strength for ultra-high-performance geopolymer concrete: A comparative study by Abdellatief M., Hassan Y.M., Elnabwy M.T., Wong L.S., Chin R.J., Mo K.H.

“…Firstly, the findings of the 113 CS tests available in the previous studies were extracted. Twelve feature variables, including GGBS, silica fume, fly ash, and rice husk ash contents as precursors, the Na2SiO3, NaOH, KOH, and extra water content, polypropylene fiber, steel fiber, liquid-to-binder (L/B) ratio, and curing temperature, were investigated. …”

A deep learning approach for facial detection in targeted billboard advertising / Lau Sian En by Lau , Sian En

“…This system utilises sophisticated deep learning algorithm using Convolutional Neural Network (CNN) to identify and examine human faces, enabling advertisers to customise their content according to demographic variables including age and gender. …”
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Recommendation System Model For Decision Making in the E-Commerce Application by Mohammed Mahmudur Rahman

Multivariate Based Analysis of Methane Adsorption Correlated to Toc and Mineralogy Impact from Different Shale Fabrics by Irfan, S.A., Azli, N.M., Abdulkareem, F.A., Padmanabhan, E.

“…The statistical analysis presented in this study incorporated one of the best regression models algorithms based on machine learning approach to study the adsorption variation with shale fabric this study. …”
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Experimental analysis and data-driven machine learning modelling of the minimum ignition temperature (MIT) of aluminium dust by Arshad, U., Taqvi, S.A.A., Buang, A.

“…It is generally recognised that the ignition behaviour of combustible dust is influenced by a variety of parameters, including the chemical composition, particle size, moisture content, dispersion pressure, the concentration of dust and so on, but there is still a lack of understanding regarding the simultaneous effect of multiple influential variables. …”
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Experimental analysis and data-driven machine learning modelling of the minimum ignition temperature (MIT) of aluminium dust by Arshad, U., Taqvi, S.A.A., Buang, A.

“…It is generally recognised that the ignition behaviour of combustible dust is influenced by a variety of parameters, including the chemical composition, particle size, moisture content, dispersion pressure, the concentration of dust and so on, but there is still a lack of understanding regarding the simultaneous effect of multiple influential variables. …”
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Offline handwritten Chinese character using convolutional neural network: State-of-the-art methods by Zhong, Yingna, Kauthar, Mohd Daud, Ain Najiha, Mohamad Nor, Ikuesan, Richard Adeyemi, Moorthy, Kohbalan

“…With the advancement of deep learning, convolutional neural network (CNN)-based algorithms have demonstrated distinct benefits in offline HCCR and have achieved outstanding results. …”
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