A rapid increase in heart disease has occurred recent years, which might be the result of unhealthy food, mental stress, genetic issues, and a sedentary lifestyle. There are many advanced automated diagnosis systems for prediction proposed studies, but most them focus only on feature preprocessing, some selection, improving predictive accuracy. In this study, we every aspect that may have an influence final performance system, i.e., to avoid overfitting underfitting problems or solve network...

The Knowledge graph, a multi-relational graph that represents rich factual information among entities of diverse classifications, has gradually become one the critical tools for knowledge management. However, existing still some problems which form hot research topics in recent years. Numerous methods have been proposed based on various representation techniques. Graph Neural Network, framework uses deep learning to process graph-structured data directly, significantly advanced...

The features are considered the cornerstone of text summarization. most important issue is what feature to be in a summarization process. Including all process may not as an optimal solution. Therefore, other methods need deployed. In this paper, random five used and investigated using (pseudo) Genetic concept optimized trainable selection mechanism. Document Understanding Conference (DUC2002) train our proposed model; hence objective paper learn weight (importance) each feature. For input...

Abstract Choosing descriptors is a crucial aspect of improving QSAR (Quantitative Structure-Activity Relationship) models, especially when it comes to precisely forecasting chemical biodegradability. As cheminformatics advances, the handling large molecular datasets introduces challenges due high dimensionality created by numerous descriptors. This study presents Chaotic Adaptive Somersault Factor Binary Manta Ray Foraging Optimization (CASF-BMRFO) algorithm, designed optimize descriptor...

Different CNNs models do not perform well in deepfake detection cross datasets. This paper proposes a model called DeepfakeNet, which consists of 20 network layers. It refers to the stacking idea ResNet and split-transform-merge Inception design block structure, That is, structure ResNeXt. The study uses some data FaceForensics++, Kaggle TIMIT datasets, enhancement technology is used expand datasets for training testing models. experimental results show that, compared with current mainstream...

Nowadays, many documents are available on the internet and easy to access. Due this wide availability, users can easily create a new document by copying pasting. Plagiarism occurs when content is copied without permission or citation. This paper introduces plagiarism detection technique based Semantic Role Labeling (SRL). The analyses compares text semantic allocation for each term inside sentence. SRL superior in generating arguments sentence semantically. In addition, experimental results...

Weeds are very annoying for farmers and also not good the crops. Its existence might damage growth of Therefore, weed control is important farmers. Farmers need to ensure their agricultural fields free from weeds at least once a week, whether they spray herbicides plantation or remove it using tools manually. The aim this research build an automated robot Lego Mindstorm EV3 which connected computer. consists motors, servo motors camera we use capture image crops weeds. An classification...

In today's digital era, it becomes a challenge for netizens to find specific information on the internet. Many web-based documents are retrieved and is not easy digest all information. Automatic text summarization process that identifies important points from related produce concise summary. this paper, we propose model based classification using neuro-fuzzy approach. The can be trained filter high-quality summary sentences. We then compare performance of our proposed with existing...

The aim of automatic multi-document abstractive summarization is to create a compressed version the source text and preserves salient information. Existing graph based methods treat sentence as bag words, rely on content similarity measure did not consider semantic relationships between sentences. These may fail in determining redundant sentences that are semantically equivalent. This paper introduces genetic approach for summarization. Semantic from document set constructed such way nodes...

Left ventricular segmentation is a vital and necessary procedure for assessing cardiac systolic diastolic function, while echocardiography an indispensable diagnostic technique that enables functionality assessment. However, manually labeling the left region on images time consuming leads to observer bias. Recent research has demonstrated deep learning capability employ process automatically. downside, it still ignores contribution of all semantic information through process. This study...

News articles which are available through online search often provide readers with large collection of texts. Especially in the case news story, different sources reporting on same event usually returns multiple response to a reader's search. In this work, we first identify cross-document relations from un-annotated texts using Genetic-CBR approach. Following that, develop new sentence scoring model based voting technique over identified relations. Our experiments show that incorporating...

In Malaysia, a new regulation of traffic offences demerit points has been over debate. Therefore, blockchain model is formulated to solve this issue. It serves purpose be Proof Work (PoW) system. This contains application layer and with smart contract inside. The contracts act as conditional filter which follows the rules. three starting from declaration each offence’s fines until penalties when certain amount collected, including revocation driver license. will automatically executed such...