Distributed anomaly detection scheme based on lightweight data aggregation in wireless sensor network by Mohd. Zamry, Nurfazrina

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Optimized intelligent classifier for early breast cancer detection using ultra-wide band transceiver by Ahmad Ashraf, Abdul Halim, Andrew, Allan Melvin, Wan Azani, Mustafa, Mohd Najib, Mohd Yasin, Muzammil R.I., Mat Jusoh, Veeraperumal, Vijayasarveswari, Mohd Amiruddin, Abd Rahman, Norshuhani, Zamin, Mary, Mervin Retnadhas, Khatun, Sabira

“…Consequently, the dataset was fed into the MSFS–BPSO framework and started with feature normalization before it was reduced using feature dimension reduction. Then, the feature selection (based on time/frequency domain) using seven different classifiers selected the frequency domain compared to the time domain and continued to perform feature extraction. …”
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Breast cancer image classification via multi-network features and dual-network orthogonal low-rank learning by Wang, Yongjun, Lei, Baiying, Elazab, Ahmed, Tan, Ee-Leng, Wang, Wei, Huang, Fanglin, Gong, Xuehao, Wang, Tianfu

“…Specifically, we devise a multi-network feature extraction model by using pre-trained deep convolution neural networks (DCNNs), develop an effective feature dimension reduction method and train an ensemble support vector machine (E-SVM). …”
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Computational intelligence for predictive condition monitoring and approaches for online analysis by Torabi Jahromi, Amin

“…Considering the high dimension of the wavelet features‎, ‎clustering methods are used for dimension reduction and also as an interpretation layer between the signal feature extraction subsystem and artificial intelligence blocks‎. ‎…”
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Antenna optimization using slot techniques for wideband application / Mohamad Amir Imran Mohd Hasli by Mohd Hasli, Mohamad Amir Imran

“…The proposed antenna managed to achieve a total of 6.7% dimension reduction by utilizing these techniques. This thesis present an approach to respond to current design challenge and demand in wireless communication application. …”
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Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment by Sojodishijani, Omid

“…Experimental results on real and synthesized datasets with real and artificial changes demonstrate the performance of the proposed method in terms of accuracy and dimension reduction in dynamic environments. In the case of real datasets, the proposed method yields 12.16% average misclassification error while the average misclassification error for five different methods GAM, TSY, NWKNN, DWM and FISH is 19.54%. …”
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Self-adaptive evolving forecast models with incremental PLS space updating for on-line prediction of micro-fluidic chip quality by Lughofer, Edwin, Pollak, Robert, Zavoianu, Alexandru-Ciprian, Pratama, Mahardhika, Meyer-Heye, Pauline, Zörrer, Helmut, Eitzinger, Christian, Haim, Julia, Radauer, Thomas

“…We apply time-series based transformation for dimension reduction to the lagged time-series space using of partial least squares (PLS), and combine this with a generalized form of Takagi–Sugeno(TS) fuzzy systems to obtain a non-linear PLS forecast model (termed as PLS-fuzzy). …”
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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…Even if a ranking method is widely utilized in solving numerous of dimension reduction problems such as in bioinformatics and high spectral images, most of works are disregarding the boundary to discard the irrelevant features. …”
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Deconstructing complex diseases : identification of new phenotypical sub-clusters of Type 2 diabetes using machine learning by Mehta, Priyasha.

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Remote sensing applications for insurance: a predictive model for pasture yield in the presence of systemic weather by Porth, C. Brock, Porth, Lysa, Zhu, Wenjun, Boyd, Milton, Tan, Ken Seng, Liu, Kai

“…Other predictive models based on principal component analysis and shrinkage methods (such as lasso, ridge regression, and elastic net) are considered to address the issues of variable selection and dimension reduction in insurance design. This research makes an important contribution to the field of actuarial science and insurance, because it highlights potential new opportunities for insurance design and predictive analytics using large and comprehensive satellite datasets that remain relatively unexplored to date in insurance practice. …”
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Human action recognition by embedding silhouettes and visual words by Saghafi Khadem, Behrouz

“…The method not only outperforms other dimension reduction methods but is comparable to the state of the art on three public datasets. …”
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Poisson-based implicit shape space analysis with application to CT liver segmentation by Vesom, G

“…To the best of our knowledge, this study is novel in comparing several shape representations through a single dimension reduction method.</p><p>Our second contribution is a hybrid region-based level set segmentation that simultaneously infers liver shape given the image data, integrates the Poisson-based shape function prior into the segmentation, and evolves the level set according to the image data. …”

Modelling diffusion: around particles and into plants by Elliott, JR

“…Three solution methods are presented: the Thomas algorithm, the alternating direction implicit method, and fully implicit methods. Dimension reduction, grid construction, and the simulation validation is discussed.…”

Support vector machine and its applications for linear and nonlinear regression in the presence of outliers of high dimensional data by Sleabi, Waleed Dhhan

“…The comparison results show that the ENSI-SVR is an efficient method in dealing with sparse data to achieve dimension reduction which allows applying the SI-SVR easily.…”
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Age group classification based on facial images by Sai, Phyo Kyaw

“…Then a new framework where Extreme Learning Machine classifier took output of dimension reduction methods like PCA on local features as inputs was introduced to get a much better performance. …”
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Salivary based SERS analysia in recognition of NS1 for PCA-SVM classification of dengue fever / Afaf Rozan Mohd Radzol by Mohd Radzol, Afaf Rozan

“…Then, the clean spectra are analysed using PCA for feature extraction and dimension reduction. Finally, the extracted principal components are classified into dengue positive and negative using SVM algorithm. …”
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Salivary based sers analysis in recognition of ns1 for pcasvm classification of dengue fever / Afaf Rozan Mohd Radzol by Mohd Radzol, Afaf Rozan

“…Then, the clean spectra are analysed using PCA for feature extraction and dimension reduction. Finally, the extracted principal components are classified into dengue positive and negative using SVM algorithm. …”
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Enhancing spoken language identification and diarization for multilingual speech by Liu, Hexin

“…Two mechanisms are then employed to reduce the irrelevant information of the representations in LID—the first being the attentive squeeze-and-excitation (SE) block for dimension-wise scaling and the second being the linear bottleneck (LBN) block that reduces the irrelevant information by nonlinear dimension reduction. These two methods are incorporated within the XSA-LID model, named AttSE-XSA and LBN-XSA respectively. …”
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Label-free single cell electro-mechano-phenotyping using microfluidics impedance cytometry by He, Linwei

“…By applying Uniform Manifold Approximation and Projection (UMAP) as a dimension reduction technique for single cell impedance signatures, we demonstrated its utilities in 2 key biomedical applications including 1) rapid induced pluripotent stem cells (iPSCs) profiling in cell therapy, as well as 2) leukocyte characterization in type 2 diabetes mellitus (T2DM) for cardiovascular risk stratification. …”
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Photodegradation of micropollutants in water by UV/H2O2 and UV/persulfate by Zhang, Yiqing

“…Three descriptor filtration approaches were evaluated and compared, including non-dimension-reduction approach, correlation analysis approach, and principal component analysis approach. …”
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