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Joan D. Gonzalez-Franco, Jorge E. Preciado-Velasco, Jose E. Lozano-Rizk, Raul Rivera-Rodriguez, Jorge Torres-Rodriguez and Miguel A. Alonso-Arevalo
Improving the quality of service (QoS) and meeting service level agreements (SLAs) are critical objectives in next-generation networks. This article presents a study on applying supervised learning (SL) algorithms in a 5G/B5G service dataset after being ...
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Tulsi Patel, Mark W. Jones and Thomas Redfern
We present a novel approach to providing greater insight into the characteristics of an unlabelled dataset, increasing the efficiency with which labelled datasets can be created. We leverage dimension-reduction techniques in combination with autoencoders...
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Yu Wang, Alister Machado and Alexandru Telea
Visualization techniques for understanding and explaining machine learning models have gained significant attention. One such technique is the decision map, which creates a 2D depiction of the decision behavior of classifiers trained on high-dimensional ...
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Nikhil Iyengar, Dushhyanth Rajaram and Dimitri Mavris
Uncertainties in the atmosphere and flight conditions can drastically impact the performance of an aircraft and result in certification delays. However, uncertainty propagation in high-fidelity simulations, which have become integral to the design proces...
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Shingchern D. You and Ming-Jen Hung
This paper studies the use of three different approaches to reduce the dimensionality of a type of spectral?temporal features, called motion picture expert group (MPEG)-7 audio signature descriptors (ASD). The studied approaches include principal compone...
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Karaj Khosla, Indra Prakash Jha, Ajit Kumar and Vibhor Kumar
Dimension reduction is often used for several procedures of analysis of high dimensional biomedical data-sets such as classification or outlier detection. To improve the performance of such data-mining steps, preserving both distance information and loca...
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Siyang Chen, Yunsheng Zhang, Ke Nie, Xiaoming Li and Weixi Wang
This paper presents an automatic building extraction method which utilizes a photogrammetric digital surface model (DSM) and digital orthophoto map (DOM) with the help of historical digital line graphic (DLG) data. To reduce the need for manual labeling,...
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Songze Lei, Boxing Zhang, Yanhong Wang, Baihua Dong, Xiaoping Li and Feng Xiao
UAVs (unmanned aerial vehicles) have been widely used in many fields, where they need to be detected and controlled. Small-sample UAV recognition requires an effective detecting and recognition method. When identifying a UAV target using the backward pro...
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Boris Kovalerchuk and Dmytro Dovhalets
The exploration of multidimensional datasets of all possible sizes and dimensions is a long-standing challenge in knowledge discovery, machine learning, and visualization. While multiple efficient visualization methods for n-D data analysis exist, the lo...
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Gabriella Kicska and Attila Kiss
Nowadays, the high-dimensionality of data causes a variety of problems in machine learning. It is necessary to reduce the feature number by selecting only the most relevant of them. Different approaches called Feature Selection are used for this task. In...
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Sheikh S. Abdullah, Neda Rostamzadeh, Kamran Sedig, Amit X. Garg and Eric McArthur
Recent advancement in EHR-based (Electronic Health Record) systems has resulted in producing data at an unprecedented rate. The complex, growing, and high-dimensional data available in EHRs creates great opportunities for machine learning techniques such...
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Sungkun Hwang, Recep M. Gorguluarslan, Hae-Jin Choi and Seung-Kyum Choi
Interests in strain gauge sensors employing stretchable patch antenna have escalated in the area of structural health monitoring, because the malleable sensor is sensitive to capturing strain variation in any shape of structure. However, owing to the nar...
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Guoqing Chao, Yuan Luo and Weiping Ding
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Uraiwan Buatoom and Muhammad Usman Jamil
In image classification, various techniques have been developed to enhance the performance of principal component analysis (PCA) dimension reduction techniques with guiding weighting features to remove redundant and irrelevant features. This study propos...
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Alfio Di Giovanni, Carmine Todaro, Marilena Cardu, Stefano Bianchini and Brunello Forfori
This paper presents a laboratory test campaign focused on the reduction of the wear phenomenon related to a material extracted from a marble quarry. The aim of the work is to propose a potential solution for the wear reduction pertaining to chainsaw cutt...
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Nikita Andriyanov
The article is devoted to the study of convolutional neural network inference in the task of image processing under the influence of visual attacks. Attacks of four different types were considered: simple, involving the addition of white Gaussian noise, ...
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Ching-Yun Mu, Tien-Yin Chou, Thanh Van Hoang, Pin Kung, Yao-Min Fang, Mei-Hsin Chen and Mei-Ling Yeh
Spatial information technology has been widely used for vehicles in general and for fleet management. Many studies have focused on improving vehicle positioning accuracy, although few studies have focused on efficiency improvements for managing large tru...
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Ibrahim Furkan Ince
Human activity recognition (HAR) has been an active area in computer vision with a broad range of applications, such as education, security surveillance, and healthcare. HAR is a general time series classification problem. LSTMs are widely used for time ...
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Kai Li, Quan Liu, Yuan Tian, Cong Du and Zhixiang Xu
Asphalt mixtures exhibit complex mechanical behaviors due to their multiphase internal structures. To provide better characterizations of asphalt pavements under various forms of potential distress, a two-dimensional (2D) finite element simulation based ...
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Ning Wang, Zhong Ma, Pengcheng Huo, Xi Liu, Zhao He and Kedi Lu
Crop yield prediction is essential for tasks like determining the optimal profile of crops to be planted, allocating government resources, effectively planning and preparing for aid distribution, making decisions about imports, and so on. Crop yield pred...
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