Search Results - (( java implementation force algorithm ) OR ( knowledge utilization detection algorithm ))

An Innovative Signal Detection Algorithm in Facilitating the Cognitive Radio Functionality for Wireless Regional Area Network Using Singular Value Decomposition by Mohd. Hasbullah, Omar

“…The detection algorithm was developed analytically by applying the Signal Detection Theory (SDT) and the Random Matrix Theory (RMT). …”
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Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation by Chen, Qipeng, Xiong, Qiaoqiao, Huang, Haisong, Tang, Saihong, Liu, Zhenghong

“…In response to the current issues of poor real-time performance, high computational costs, and excessive memory usage of object detection algorithms based on deep convolutional neural networks in embedded devices, a method for improving deep convolutional neural networks based on model compression and knowledge distillation is proposed. …”
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

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Facial Drowsiness Signs Detection Algorithm Using Image Processing Techniques For Various Lighting Condition by Yuri, Nur Fatin Izzati

“…Viola-Jones algorithm is utilized for face detection. Upon acquiring the face location, the knowledge-based method is implemented to locate the eye and the mouth. …”
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Early detection of dengue disease using extreme learning machine by Suhaeri, Suhaeri, Mohd Nawi, Nazri, Fathurahman, Muhamad

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A detailed description on unsupervised heterogeneous anomaly based intrusion detection framework by Udzir, Nur Izura, Hajamydeen, Asif Iqbal

“…Observing network traffic flow for anomalies is a common method in Intrusion Detection. More effort has been taken in utilizing the data mining and machine learning algorithms to construct anomaly based intrusion detection systems, but the dependency on the learned models that were built based on earlier network behaviour still exists, which restricts those methods in detecting new or unknown intrusions. …”
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Electroencephalography Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation by Mohamed, Shakir, Qidwai, Uvais, Malik, Aamir Saeed, Kamel , Nidal

“…With controlled data types, healthy/normal, seizure and pre-seizure classes, tuning of algorithms for detection and classification applications can be attained. …”
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Twisted pair cable fault diagnosis via random forest machine learning by Ghazali, N. B., Seman, F. C., Isa, K., Ramli, K. N., Z. Abidin, Z., Mustam, S. M., Haek, Haek, Z. Abidin, A. N., Asrokin, A.

“…Secondly, the feature transformation, a knowledge-based method, is utilized to pre-process the fault data. …”
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Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak by Ishak, Najihah Salsabila

“…A comparison between built-in Scikit Learn Naive Bayes algorithm, and the scratch Naive Bayes algorithm is used to measure its effectiveness in terms of accuracy. …”
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Methods for identification of the opportunistic gut mycobiome from colorectal adenocarcinoma biopsy tissues by Aisyah, Yunus, Norfilza, Mohd Mokhtar, Raja Affendi, Raja Ali *, Siti Maryam, Ahmad Kendong, Hajar, Fauzan Ahmad

“…These findings suggest the utility of gut mycobiome as biomarkers for the detection of colorectal adenocarcinoma. …”
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Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction by Alkawsi G., Al-amri R., Baashar Y., Ghorashi S., Alabdulkreem E., Kiong Tiong S.

On equivalence of FIS and ELM for interpretable rule-based knowledge representation by Wong S.Y., Yap K.S., Yap H.J., Tan S.C., Chang S.W.

Real-time anomaly detection using clustering in big data technologies / Riyaz Ahamed Ariyaluran Habeeb by Riyaz Ahamed , Ariyaluran Habeeb

“…Subsequently, comparative analysis to further establish the problems has been carried out via utilization of various existing algorithms which were then validated using three openly available datasets. …”
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Robust overlapping community detection in complex networks with graph convolutional networks and fuzzy C-means by Mohammed Al-Andoli, Mohammed Nasser, Che Ku Mohd, Che Ku Nuraini, Harny, Irianto, Jamil Alsayaydeh, Jamil Abedalrahim, Alwayle, Ibrahim M., Ahmed Abuhoureyah, Fahd Saad

“…Existing methods often struggle to capture both network topology and node features, leading to suboptimal overlapping community detection. In this paper, we propose an efficient method called GCNFCM, which utilizes Graph Convolutional Networks (GCNs), Fuzzy C-means (FCM), and the modularity Q algorithm for overlapping community detection. …”
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Cheating Detection in Examinations Using Improved YOLOv8 with Attention Mechanism by Yan, Zuo, Chai, Soo See, Goh, Kok Luong

“…To improve the efficiency of video reviews during invigilation, save labor costs, and strengthen invigilation efforts, this study proposes the use of target detection algorithms to achieve automatic detection of cheating actions in the exam room. …”
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Assisting novice researchers in utilizing the web as a platform for research: semantic approach by Ismail, M.A., Yaacob, M., Kareem, S.A., Nasaruddin, F.H.

“…The algorithms involved with each of the support features will be discussed. …”
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Arcing Faults Detection in Switchgear with Extreme Learning Machine by Ishak S., Koh S.P., Tan J.D., Tiong S.K., Chen C.P., Yaw C.T.

EEG Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation by Shakir, Mohamed, Qidwai, Uvais, Malik, Aamir Saeed, Kamel, Nidal

“…With controlled data types, healthy/normal, seizure and pre-seizure classes, tuning of algorithms for detection and classification applications can be attained. …”
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Combination of GREEN and SHRed AQM for short-lived traffic by Shaii, Ahmad Qadafi, Ismail, Roslan, Jais, Jamilin

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Road Crack Detection Using Adaptive Multi Resolution Thresholding Techniques by Othman, Zuraini, Abdullah, Azizi, Kasmin, Fauziah, Syed Ahmad, Sharifah Sakinah

“…For this reason, many studies had been focusing on automatic image-based crack detection as a replacement for manual inspection that had depended on the specialist's knowledge and expertise. …”
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