Noor Mualla¹, Essam H Houssein^{2, *}, M. R. Hassan¹

CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 591-605, 2020, DOI:10.32604/cmc.2020.08580

Abstract Chronological age estimation using panoramic dental X-ray images is an essential task in forensic sciences. Various statistical approaches have proposed by considering the teeth and mandible. However, building automated dental age estimation based on machine learning techniques needs more research efforts. In this paper, an automated dental age estimation is proposed using transfer learning. In the proposed approach, features are extracted using two deep neural networks namely, AlexNet and ResNet. Several classifiers are proposed to perform the classification task including decision tree, k-nearest neighbor, linear discriminant, and support vector machine. The proposed approach is evaluated More >

Yabin Xu^{1, 2, *}, Xuyang Meng¹, Yangyang Li³, Xiaowei Xu^{4, *}

CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 137-155, 2020, DOI:10.32604/cmc.2020.05825

Abstract In order to effectively detect the privacy that may be leaked through social networks and avoid unnecessary harm to users, this paper takes microblog as the research object to study the detection of privacy disclosure in social networks. First, we perform fast privacy leak detection on the currently published text based on the fastText model. In the case that the text to be published contains certain private information, we fully consider the aggregation effect of the private information leaked by different channels, and establish a convolution neural network model based on multi-dimensional features (MF-CNN) to More >

Quy Thy Truong¹ , Guillaume Touya², Cyril de Runz³

Revue Internationale de Géomatique, Vol.29, No.1, pp. 31-56, 2019, DOI:10.3166/rig.2019.00073

Abstract Dans un contexte où le vandalisme de l’information géographique volontaire constitue une réelle menace pour la qualité des données, cet article propose une technique permettant de le détecter. Tout d’abord, nous examinons les différentes définitions du vandalisme, mettant en avant la complexité de cette notion. Une étude des cas déjà avérés de vandalisme dans OpenStreetMap (OSM) est présentée. Puis, nous expérimentons la détection du vandalisme des données OSM en utilisant une méthode de détection d’anomalie par classification non supervisée. L’analyse de nos résultats initiaux conduit alors à une discussion sur la pertinence de construire un More >

J.-Y. Scoazec

Oncologie, Vol.21, No.2, pp. 119-124, 2019, DOI:10.3166/onco-2019-0052

Abstract La classification OMS des tumeurs des organes endocrines, parue en juillet 2017 et celle des tumeurs digestives, parue en juillet 2019, ont introduit plusieurs modifications dans la classification des tumeurs neuroendocrines (TNE) gastroentéropancréatiques, dont la précédente version remontait à 2010. La principale modification est l’introduction d’une catégorie supplémentaire de tumeurs bien diffé- renciées, les TNE G3, qui vient s’ajouter aux deux catégories déjà existantes. Les autres modifications concernent : 1) le seuil de l’index Ki-67 entre TNE G1 et G2, désormais fixé à 3 % et 2) la terminologie proposée pour désigner les tumeurs mixtes More >

Mohammad Behrouzian Nejad¹, Mohammad Ebrahim Shiri^1,2,*

Computer Systems Science and Engineering, Vol.34, No.2, pp. 91-100, 2019, DOI:10.32604/csse.2019.34.091

Abstract In this paper we propose a new image classification technique. According to this note that most research focuses on extraction of features in the frequency domain, location, and reduction of feature dimensions, in this research we focused on learning step in image classification. The main aim is to use the heuristic methods to increase the function of the estimator of the learning algorithm and continue to achieve the desired state, as well as categorization without user interference and automatically performed by the model produced from the above steps. So, in this paper, a new learning… More >

Byoung-Doo Oh^a,b, Hye-Jeong Song^a,b, Jong-Dae Kim^a,b, Chan-Young Park^a,b, Yu-Seop Kim^a,b

Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 343-350, 2019, DOI:10.31209/2019.100000095

Abstract Accurate prediction of fine dust (PM10) concentration is currently recognized as an important problem in East Asia. In this paper, we try to predict the concentration of PM10 using Deep Neural Network (DNN). Meteorological factors, yellow dust (sand), fog, and PM10 are used as input data. We test two cases. The first case predicts the concentration of PM10 on the next day using the day’s weather forecast data. The second case predicts the concentration of PM10 on the next day using the previous day’s data. Based on this, we compare the various performance results from More >

Lu Wu, Quan Liu, Ping Lou

Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 249-257, 2019, DOI:10.31209/2018.100000010

Abstract The scheme of spatial pyramid matching (SPM) causes feature ambiguity near dividing lines because it divides an image into different scales in a fixed manner. A new method called soft SPM (sSPM) is proposed in this paper to reduce feature ambiguity. First, an auxiliary area rotating around a dividing line in four orientations is used to correlate the feature relativity. Second, sSPM is performed to combine these four orientations to describe the image. Finally, an optimized multiple kernel learning (MKL) algorithm with three basic kernels for the support vector machine is applied. Specifically, for each More >

Brian A. Boe, Sharon L. Cheatham, Aimee K. Armstrong, Darren P. Berman, Joanne L. Chisolm, John P. Cheatham

Congenital Heart Disease, Vol.14, No.2, pp. 297-304, 2019, DOI:10.1111/chd.12728

Abstract Objective: We sought to describe the leaflet morphology variation in the Melody Transcatheter Pulmonary Valve (TPV) and evaluate associated outcomes. The Melody TPV is constructed from harvested bovine jugular venous valves which have been rigorously tested. Natural anatomic leaflet variations are seen in the Melody TPV but have not been evaluated.
Design: A Melody TPV leaflet morphology classification system was devised after reviewing a subset of photographed and implanted TPVs. All images were blindly re‐ viewed by implanters and classified. Midterm hemodynamic outcomes and complica‐ tions of the Melody TPVs were compared by leaflet morphology.
Results: Photographed Melody… More >

Ibnu Rusydy^1,3,*, Nafisah Al-Huda^1,2, M. Fahmi⁴, Naufal Effendi⁴

Structural Durability & Health Monitoring, Vol.13, No.4, pp. 379-398, 2019, DOI:10.32604/sdhm.2019.08192

Abstract Rock slope kinematic analysis and rock mass classifications has been conducted at the 17^th km to 26^th km of USAID (United States Agency for International Development) highway in Indonesia. This research aimed to examine the type of rock slope failures and the quality of rock mass as well. The scan-line method was performed in six slopes by using a geological compass to determine rock mass structure on the rock slope, and the condition of joints such as persistence, aperture, roughness, infilling material, weathering and groundwater conditions. Slope kinematic analysis was performed employing a stereographic projection. The… More >

Jingyi Wang¹, Jing Sun^1,*, Dehua Liu¹, Xiang Zhu¹

FDMP-Fluid Dynamics & Materials Processing, Vol.15, No.5, pp. 613-625, 2019, DOI:10.32604/fdmp.2019.08782

Abstract One of the important indicators of shale gas reservoir excavation is capacity evaluation, which directly affects whether large-scale shale gas reservoirs can be excavated. Capacity evaluation is the basis of system analysis and dynamic prediction. Therefore, it is particularly important to conduct capacity evaluation studies on shale gas horizontal wells. In order to accurately evaluate the horizontal well productivity of shale gas staged fracturing, this paper uses a new method to evaluate the productivity of Fuling shale gas. The new method is aimed at the dynamic difference of horizontal wells and effectively analyzes the massive More >