Wavelet-Based Kernel Construction for Heart Disease Classification

© 2019 ADVANCES IN ELECTRICAL AND ELECTRONIC ENGINEERINGHeart disease classification plays an important role in clinical diagnoses. The performance improvement of an Electrocardiogram classifier is therefore of great relevance, but it is a challenging task too. This paper proposes a novel classification algorithm using the kernel method. A kernel is constructed based on wavelet coefficients of heartbeat signals for a classifier with high performance. In particular, a wavelet packet decomposition algorithm is applied to heartbeat signals to obtain the Approximation and Detail coefficients, which are used to calculate the parameters of the kernel. A principal component analysis algorithm with the wavelet-based kernel is employed to choose the main features of the heartbeat signals for the input of the classifier. In addition, a neural network with three hidden layers in the classifier is utilized for classifying five types of heart disease. The electrocardiogram signals in nine patients obtained from the MIT-BIH database are used to test the proposed classifier. In order to evaluate the performance of the classifier, a multi-class confusion matrix is applied to produce the performance indexes, including the Accuracy, Recall, Precision, and F1 score. The experimental results show that the proposed method gives good results for the classification of the five mentioned types of heart disease.Peer reviewedFinal Published versio

R PEAK DETERMINATION USING A WDFR ALGORITHM AND ADAPTIVE THRESHOLD

The determination of the R peak position in the ECG signal helps physicians not only to know the heart rate per minute, but also to monitor the patient’s health related to heart disease. This paper proposes a system to accurately determine the R peak position in the ECG signal. The system consists of a pre-processing block for filtering out noise using a WDFR algorithm and highlighting the amplitude of the R peak and a threshold value is calculated for determining the R peak. In this research, the MIT-BIH ECG dataset with 48 records are used for evaluation of the system. The results of the SEN, +P, DER and ACC parameters related to the system quality are 99.70%, 99.59%, 0.70% and 99.31%, respectively. The obtained performance of the proposed R peak position determination system is very high and can be applied to determine the R peak of the ECG signal measuring devices in practice

Genetic diversity of Afzelia xylocarpa (Kurz) Craib in Vietnam based on analyses of chloroplast markers and random amplified polymorphic DNA (RAPD)

Afzelia xylocarpa (Kurz) Craib is not only an endangered species in Vietnam, but also around the world. The wood of this tree species is very valuable as it is used to construct houses and high quality furniture. Habitat loss and exploitation of A. xylocarpa by man have threatened the population to such an extent that the number of mature trees of this species has dwindled to quite a low quantity. Declining numbers of A. xylocarpa in turn causes a constriction of the gene pool. Thus, it is very important to evaluate the genetic diversity of A. xylocarpa (Kurz) Craib in order to conserve and sustain the surviving population of these trees. 50 samples of A. xylocarpa (Kurz) Craib were collected from seven locations in four provinces (Gia Lai, Dac Lac, Dong Nai and Ninh Thuan) and used to evaluate the genetic diversity of these trees based on the analysis of chloroplast 16S rRNA, non-coding regions between trnH-trnK, trnD-trnT and psbC-trnS chloroplast genes using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and random amplified polymorphic DNA (RAPD) markers. The data obtained reveals that the 50 samples of A. xylocarpa (Kurz) Craib have low level of genetic diversity, as supported by the fact that the genetic similarity coefficients of the trees ranged from 49 to 100%. At the similarity level of 49%, the 50 samples were grouped into two main groups. There was no clear local specificities of the samples as the samples from same locality were not found in same group. Due to low level of genetic diversity, low numbers of trees and scattered occurrence, setting up suitable conservation strategies are urgently needed.Key words: Afzelia xylocarpa (Kurz) Craib, genetic diversity, non-coding sequences, random amplified polymorphic DNA (RAPD) markers

Factors Affecting the Agricultural Restructuration: A Case of Cham Community in Chau Phu District, An Giang Province, Vietnam

The national policy of agricultural restructuring plays a vital role in adapting to climate change's effects and economic development in the Mekong Delta of Vietnam. Unproductive areas have been converted into other crops with higher efficiency. Drawn by the sustainable livelihoods approach, this article explores the current situation and factors challenging the Cham community in implementing the agricultural restructuring. The mixed method included in-depth interviews, focus group discussions, and a questionnaire survey. The results showed that the Xuong Com Vang longan (Dimocarpus longan) variety has occurred in Khanh Hoa commune for a long time as an indigenous fruit tree of this area. In terms of the farming system, the polyculture system combining fruit trees and upland crops brought more income sources than the monoculture system. The asset abilities of the Cham farmers are various from one to the others. Soil and weather conditions are appropriate for planting. But farm size is small, which is one of the difficulties of developing fruit areas. Human and social assets were good since farmers had enough knowledge to manage the gardens, and a close connection existed among the Cham community. It was not a case of the financial status since a lot of money needs to be invested in the starting year. Therefore, the private loan still exists as one of the farmer's choices. For better future development, land management and financial resource should be considered for better agricultural restructuring aims. To increase farmers' incomes, create production chains helping enterprises and farmers work more efficiently for the better life of Cham gardeners in An Giang province in Vietnam

ShortcutFusion: From Tensorflow to FPGA-based accelerator with reuse-aware memory allocation for shortcut data

Residual block is a very common component in recent state-of-the art CNNs such as EfficientNet or EfficientDet. Shortcut data accounts for nearly 40% of feature-maps access in ResNet152 [8]. Most of the previous DNN compilers, accelerators ignore the shortcut data optimization. This paper presents ShortcutFusion, an optimization tool for FPGA-based accelerator with a reuse-aware static memory allocation for shortcut data, to maximize on-chip data reuse given resource constraints. From TensorFlow DNN models, the proposed design generates instruction sets for a group of nodes which uses an optimized data reuse for each residual block. The accelerator design implemented on the Xilinx KCU1500 FPGA card significantly outperforms NVIDIA RTX 2080 Ti, Titan Xp, and GTX 1080 Ti for the EfficientNet inference. Compared to RTX 2080 Ti, the proposed design is 1.35-2.33x faster and 6.7-7.9x more power efficient. Compared to the result from baseline, in which the weights, inputs, and outputs are accessed from the off-chip memory exactly once per each layer, ShortcutFusion reduces the DRAM access by 47.8-84.8% for RetinaNet, Yolov3, ResNet152, and EfficientNet. Given a similar buffer size to ShortcutMining [8], which also mine the shortcut data in hardware, the proposed work reduces off-chip access for feature-maps 5.27x while accessing weight from off-chip memory exactly once.Comment: 12 page

Multi-correlation between nematode communities and environmental variables in mangrove-shrimp ponds, Ca Mau Province, Southern Vietnam

Multi-correlation between bio-indices of nematode communities and ecological parameters in mangrove-shrimp farming ponds in Tam Giang commune, Nam Can District, Ca Mau Province, Vietnam were investigated. In which, diversities of nematode communities and several environmental variables in eight ponds were considered to process. Our findings underlined the high diversity of nematode communities in mangrove-shrimp farming ponds compared to other mangrove habitats. Nematode diversities provided more oppotunity in natural food for shrimp. Single correlation analyses showed that the species richness index correlated significantly to three variables (salinity, total organic carbon, and total nitrogen), the Margalef diversity index correlated to two variables (salinity, total organic carbon), and the expected number of species for 50 individuals index correlated with one variable (salinity). Results of multi-correlation analyses between the nematode bio-indices and the environmental variables were completely different from those of single-correlation analyses. In multi-correlation analyses, the species richness and the Margalef diversity index correlated to two variables (salinity, total organic carbon), Pielou’s evenness index and Hill indices correlated with dissolved oxygen, also the Hurlbert index correlated to total organic carbon. Hence, it is necessary to pay attention to the impact of complex interactions between the multi-environmental variables and nematode communities. This research aims to explain the differences between single- and multi-correlation for evaluation of the effects of environmental factors on nematodes as well as aquatic organisms.

Detection of Luminescence Centers in Colloidal Cd0.3_{0.3}Zn0.7_{0.7}S Nanocrystals by Synchronous Luminescence Spectroscopy

With the advantages of selectivity, spectral resolution and reduction of interference on account of light scattering, synchronous luminescence spectroscopy (SLS) is successfully applied to analyze complex mixtures with overlapped emission and/or excitation spectra. In fact, it is difficult to clearly distinguish the contributions of various luminescence centers to low-energy band of semiconductor nanocrystals (NCs). Herein, we report the application of SLS method to detect luminescence centers in colloidal Cdsub0.3/subZnsub0.7/subS NCs. Their conventional luminescence and synchronous luminescence spectra were comparatively investigated. Differently from conventional luminescence spectrum, the emission peaks at 460 and 515 nm were found using SLS method. They are attributed to the emission transitions related to sulfur and zinc/cadmium vacancies. The obtained results are useful to clarify the nature of luminescence centers as well as relaxation mechanism in Cdsubx/subZnsub1-x/subS NCs

MirrorNet: Bio-Inspired Camouflaged Object Segmentation

Camouflaged objects are generally difficult to be detected in their natural environment even for human beings. In this paper, we propose a novel bio-inspired network, named the MirrorNet, that leverages both instance segmentation and mirror stream for the camouflaged object segmentation. Differently from existing networks for segmentation, our proposed network possesses two segmentation streams: the main stream and the mirror stream corresponding with the original image and its flipped image, respectively. The output from the mirror stream is then fused into the main stream's result for the final camouflage map to boost up the segmentation accuracy. Extensive experiments conducted on the public CAMO dataset demonstrate the effectiveness of our proposed network. Our proposed method achieves 89% in accuracy, outperforming the state-of-the-arts. Project Page: https://sites.google.com/view/ltnghia/research/camoComment: Under Revie