A year into the COVID-19 pandemic and one of longest recorded lockdowns in world, Philippines received its first delivery vaccines on 1 March 2021 through WHO’s COVAX initiative. month inoculation all frontline health professionals other priority groups, authors this study gathered data sentiment Filipinos regarding Philippine government’s efforts using social networking site Twitter. Natural language processing techniques were applied to understand general sentiment, which can help...

Early diagnosis is crucial to prevent the development of a disease that may cause danger human lives. COVID-19, which contagious has mutated into several variants, become global pandemic demands be diagnosed as soon possible. With use technology, available information concerning COVID-19 increases each day, and extracting useful from massive data can done through mining. In this study, authors utilized supervised machine learning algorithms in building model analyze predict presence using...

With the increasing popularity of Twitter as both a social media platform and data source for companies, decision makers, advertisers, even researchers alike, have been so massive that manual labeling is no longer feasible. This research uses semi-supervised approach to sentiment analysis English Tagalog tweets using base classifier. In this study involving Philippines, where played central role in campaign candidates, during widely contested race between son Philippines’ former President...

As is well known in statistics, the resulting linear regressors by using rank-based Wilcoxon approach to regression problems are usually robust against (or insensitive to) outliers. This motivates us introduce this paper area of machine learning. Specifically, we investigate four new learning machines, namely neural network (WNN), generalized radial basis function (WGRBFN), fuzzy (WFNN), and kernel-based regressor (KWR). These provide alternative machines when faced with general nonlinear...

In this paper, a new similarity measure for fractal image compression (FIC) is introduced. the proposed Huber (HFIC), linear regression technique from robust statistics embedded into encoding procedure of compression. When original corrupted by noises, we argue that scheme should be insensitive to those noises presented in image. This leads concept The HFIC one our attempts toward design main disadvantage high computational cost. To overcome drawback, particle swarm optimization (PSO)...

In this paper, a fast encoding algorithm is developed for fractal image compression. At each search entry in the domain pool, mean square error (MSE) calculations of given range block and eight dihedral symmetries are obtained simultaneously frequency domain, which redundant computations all eliminated new algorithm. It shown software simulation that time about six times faster than baseline method with almost same PSNR retrieved image. The performed to deal at entry. Therefore, it can be...

Detecting the presence of a disease requires laboratory tests, testing kits, and devices; however, these were not always available on hand. This study proposes new approach in detection using machine learning algorithms by analyzing symptoms experienced person without requiring tests. Six supervised such as J48 decision tree, random forest, support vector machine, k-nearest neighbors, naïve Bayes algorithms, artificial neural networks applied "COVID-19 Symptoms Presence Dataset" from Kaggle....

The central problem in the implementation of a Reed-Solomon code is finding roots error locator polynomial. In 1967, Berlekamp et al. found an algorithm for affine polynomial GF(2/sup m/) that can be used to solve this problem. paper, it shown Berlekamp-Rumsey-Solomon (1967) algorithm, together with Chien (1964) search method, makes possible fast decoding standard-basis representation naturally suitable software implementation. Finally, simulation results are given.

In a previous article by Truong et al. (see ibid., vol.46, p.973-76, 1998), it was shown that an inverse-free Berlekamp-Massey (1968, 1969) algorithm can be generalized to find the error locator polynomial in Reed-Solomon (RS) decoder for correcting errors as well erasures. The basic idea of this procedure is replacement initial condition BM Forney (1965) syndromes. It errata obtained directly initializing with erasure and An important ingredient new modified computing polynomial. As...

One of the fundamental advancements in deployment object detectors real-time applications is to improve recognition against obstruction, obscurity, and noises images. In addition, detection a challenging task since it needs correct objects from Semantic segmentation localization are an important module recognizing image. The method (Grad-CAM++) mostly used by researchers for localization, which uses gradient with convolution layer build map regions on This paper proposes called Combined...

Efforts have been made to improve the risk stratification model for patients with diffuse large B-cell lymphoma (DLBCL). This study aimed evaluate disease prognosis using machine learning models iterated cross validation (CV) method. A total of 122 pathologically confirmed DLBCL and receiving rituximab-containing chemotherapy were enrolled. Contributions clinical, laboratory, metabolic imaging parameters from fluorine-18 fluorodeoxyglucose (FDG) positron emission tomography/computed...

In this paper, we investigate the robust single-label multi-class classification problems in machine learning using proposed linearly scored categorical cross-entropy for training data with wrong class labels. Deep neural networks are constructed and trained different loss functions various noise levels. CIFAR10 CIFAR100 image datasets used to calculate estimated accuracy performances via 10-fold cross validation. From simulation results, function may actually provide a promising alternative...

Early risk tagging is crucial in maternal health, especially because it threatens both the mother and long-term development of baby. By high-risk pregnancies, mothers would be given extra care before, during, after thus reducing complications. In Philippines, where fertility rate high, among youth, awareness risks can significantly contribute to overall outcome pregnancy and, an extent, Maternal mortality rate. Although supervised machine learning models have ubiquity as predictors, there a...

Object detection has received a lot of research attention in recent years because its close association with video analysis and image interpretation. Detecting objects images videos is fundamental task considered as one the most difficult problems computer vision. Many machine learning deep models have been proposed past to solve this issue. In current scenario, algorithm must calculate from beginning end shortest amount time possible. This paper proposes method called GradCAM-MLRCNN that...

Principal component analysis (PCA), a statistical processing technique, transforms the data set into lower dimensional feature space, yet retain most of intrinsic information content original data. In this paper, we apply PCA for image compression. computation, adopt neural network architecture in which synaptic weights, served as principal components, are trained through generalized Hebbian algorithm (GHA). Moreover, partition training clusters using K-means method order to obtain better...