Journal of Intelligent & Fuzzy Systems - Volume 43, issue 2

Authors: Balas, Valentina Emilia

Article Type: Editorial

DOI: 10.3233/JIFS-219269

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 2, pp. 1681-1681, 2022

Authors: Abineza, Claudia | Balas, Valentina E. | Nsengiyumva, Philibert

Article Type: Research Article

Abstract: Chronic Obstructive Pulmonary Disease (COPD) is a progressive, obstructive lung disease that restricts airflow from the lungs. COPD patients are at risk of sudden and acute worsening of symptoms called exacerbations. Early identification and classification of COPD exacerbation can reduce COPD risks and improve patient’s healthcare and management. Pulse oximetry is a non-invasive technique used to assess patients with acutely worsening symptoms. As part of manual diagnosis based on pulse oximetry, clinicians examine three warning signs to classify COPD patients. This may lack high sensitivity and specificity which requires a blood test. However, laboratory tests require time, further delayed treatment …and additional costs. This research proposes a prediction method for COPD patients’ classification based on pulse oximetry three manual warning signs and the resulting derived few key features that can be obtained in a short time. The model was developed on a robust physician labeled dataset with clinically diverse patient cases. Five classification algorithms were applied on the mentioned dataset and the results showed that the best algorithm is XGBoost with the accuracy of 91.04%, precision of 99.86%, recall of 82.19%, F1 measure value of 90.05% with an AUC value of 95.8%. Age, current and baseline heart rate, current and baseline pulse ox. (SPO2) were found the top most important predictors. These findings suggest the strength of XGBoost model together with the availability and the simplicity of input variables in classifying COPD daily living using a (wearable) pulse oximeter. Show more

Keywords: COPD, pulse oximetry, machine learning, easy, classification

DOI: 10.3233/JIFS-219270

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 2, pp. 1683-1695, 2022

Authors: Victor, Tiţa | Daniel, Nijloveanu | Popescu, Doru Anastasiu | Bold, Nicolae

Article Type: Research Article

Abstract: In modern agriculture, one of the most influential and debatable problems are related to the water management and soil pollution. The water management issue is obviously connected to the usage of the lowest quantity possible, due to the scarce nature of the water, but is also related to cost reasons and profit maximization. The soil is also considered one of the key resources which must be dealt very rationally, due to its structure and complex processes from its function. In this paper we present a model of soil water management system, comprising the irrigation process, that also takes into account …one of the main parameters of an irrigation system: the plastic material used for irrigation. The model optimally choses the best suited material and the optimal water content, also taking into account the geographical area of the soil. The main purpose of building the model is to create an optimization environment for the irrigation systems, with both financial and environmental implications. In this paper, we will present some results of the model of a drip irrigation management system. In this matter, we have used two methods based on genetic algorithms and System Dynamic principles that can achieve desired results for the problem proposed. The results of this paper are shown based on simulations of the System Dynamic model. Show more

Keywords: Optimality, genetic, irrigation, drip, plastic

DOI: 10.3233/JIFS-219271

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 2, pp. 1697-1705, 2022

Authors: Biswas, Amrita | Dey, Barnali | Poudyel, Bishal | Sarkar, Nandita | Olariu, Teodora

Article Type: Research Article

Abstract: Falls particularly among the older population has always been a matter of concern. With the steady rise of small families, the elderly is very often left alone at home. Dedicated nurses or caretakers are quite expensive. Thus, intelligent monitoring systems with automatic fall detection systems installed at home or nursing homes could be a game changer in such applications. In this paper, a simple yet effective fall detection system based on computer vision. Novelty of this paper is that it uses the Yolo v2 network on the depth videos for extracting the subject from cluttered background. The robust performance of …the YOLOv2 network ensures accurate subject detection and removes the need for any complicated fall detection algorithm. Fall detection is carried out using subject’s height to width ratio and fall velocity. These parameters are simple and easy to calculate and yet provide effective results. The input data is captured using the Orbbec Astra 3D camera. Show more

Keywords: Fall detection, depth image, convolutional neural network

DOI: 10.3233/JIFS-219272

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 2, pp. 1707-1715, 2022

Authors: Mahanty, Chandrakanta | Kumar, Raghvendra | Mishra, Brojo Kishore | Barna, Cornel

Article Type: Research Article

Abstract: Coronavirus is an infectious disease induced by extreme acute respiratory syndrome coronavirus 2. Novel coronaviruses can lead to mild to serious symptoms, like tiredness, nausea, fever, dry cough and breathlessness. Coronavirus symptoms are close to influenza, pneumonia and common cold. So Coronavirus can only be confirmed with a diagnostic test. 218 countries and territories worldwide have reported a total of 59.6 million active cases of the COVID-19 and 1.4 million deaths as of November 24, 2020. Rapid, accurate and early medical diagnosis of the disease is vital at this stage. Researchers analyzed the CT and X-ray findings from a large …number of patients with coronavirus pneumonia to draw their conclusions. In this paper, we applied Support Vector Machine (SVM) classifier. After that we moved on to deep transfer learning models such as VGG16 and Xception which are implemented using Keras and Tensor flow to detect positive coronavirus patient using X-ray images. VGG16 and Xception show better performances as compared to SVM. In our work, Xception gained an accuracy of 97.46% with 98% f-score. Show more

Keywords: COVID-19, pneumonia, transfer learning, coronavirus, SVM, VGG16, Xception

DOI: 10.3233/JIFS-219273

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 2, pp. 1717-1726, 2022

Authors: Rad, Dana | Rad, Gavril | Maier, Roxana | Demeter, Edgar | Dicu, Anca | Popa, Mihaela | Alexuta, Daniel | Floroian, Dan | Mărineanu, Vasile Doru

Article Type: Research Article

Abstract: Meeting basic psychological needs could be difficult to maintain in current pandemic times, mainly due to preventive measures involving social distancing or full quarantine, which seem to play a very important role in well-being. The theory of basic psychological needs is a sub-theory of human motivation theory known as the theory of self-determination. This theory argues that meeting the needs of autonomy, relatedness and competence is crucial for motivation, optimal development, efficient functioning and health. Several research, examining the effects of basic psychological needs on well-being, concluded that changes in meeting the three needs had a significant effect on well-being. …Because perceived stress plays a vital role in daily life, several coping strategies have been shown to effectively manage stress and reduce its negative consequences. In this study, coping mechanisms refer to both cognitive and behavioral efforts to alleviate or overcome stressful situations, especially when an automatic response is not readily available. The present study aims to examine a predictive model of competence need satisfaction based on adaptive coping mechanisms: active coping and positive reframing, on a convenience sampling of 403 Romanian respondents. Results show that 3% of the variance in competence need satisfaction is explained by active coping and positive reframing. In this work, we have used fuzzy logic modelling on our psychological data to deal with the imprecision and vagueness inherent in input data and build a more reliable model for estimating psychological variables relations. Implications and conclusions are discussed. Show more

Keywords: Fuzzy logic modeling, self-determination theory, satisfaction of basic psychological needs, competence need satisfaction, adaptative coping mechanisms, active coping, positive reframing

DOI: 10.3233/JIFS-219274

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 2, pp. 1727-1737, 2022

Authors: Ignat, Anca | Luca, Mihaela | Păvăloi, Ioan | Lazăr, Camelia

Article Type: Research Article

Abstract: A well-structured and indexed database alleviates the computing burden on large data. This paper describes groundwork for presenting the data in a compact, distinctive form, improving the procedures of applying keypoint detection algorithms to preprocess and reduce the relevant features of the images. Our method computes for an image a number of SURF keypoints in a given interval, by adapting the threshold related to the Hessian matrix blob detector. This type of approach allows selecting the level of detail to use in image description and gives us control over the computing time. We named this method DENOL (Descriptor Number On …Limits) and tested it on images from two datasets, UCID and an original image database which we propose, IIT_DB. Very good retrieval results and a significantly reduced computing time are achieved. Show more

Keywords: CBIR, keypoint detector, keypoint matching, image database, labeling, UCID, IIT_DB

DOI: 10.3233/JIFS-219275

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 2, pp. 1739-1749, 2022

Authors: Luca, Mihaela | Ciobanu, Adrian

Article Type: Research Article

Abstract: Video colonoscopy automatic processing is a challenge and further development of computer assisted diagnosis is very helpful in correctness assessment of the exam, in e-learning and training, for statistics on polyps’ malignity or in polyps’ survey. New devices and programming languages are emerging and deep learning begun already to furnish astonishing results, in the quest for high speed and optimal polyp detection software. This paper presents a successful attempt in detecting the intestinal polyps in real time video colonoscopy with deep learning, using Mobile Net.

Keywords: Video colonoscopy, polyp detection, deep learning, real time

DOI: 10.3233/JIFS-219276

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 2, pp. 1751-1759, 2022

Authors: Kiss, Gabor

Article Type: Research Article

Abstract: News concerning autonomous cars are becoming more and more common today. There are recordings of vehicles in self-driving mode having an accident as well as footages in which they operate properly, in an errorless way. What can cause this fundamental difference? Either a software problem or the inaccuracy of the data emitted by the sensors or an incorrect decision issued by the central unit. This article is going to show the various ways in which the decisions of the central unit can be influenced and so the passengers and the environment of the vehicle can be endangered. The aim is …not to affect the trade of the autonomous cars in a negative way but, on the contrary, to attract the attention of the manufacturers to make them get prepared for and protect their cars against these dangers. At the end of the article there are going to be some suggestions made on how to install a module that can recognize external manipulations in self-driving cars to make their operation more secure. Show more

Keywords: Self-driving, autonomous, external manipulation, influenced decision making, confuse the artificial intelligence

DOI: 10.3233/JIFS-219277

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 2, pp. 1761-1769, 2022

Authors: Tran, Thien Khai | Dinh, Hoa Minh | Phan, Tuoi Thi

Article Type: Research Article

Abstract: Sentiment classification is one of the major tasks of natural language processing (NLP) and has gained much attention by researchers and businesses in recent years. However, the semantics of the social networking language is becoming increasingly complex and unpredictable, affecting the accuracy of the associated NLP systems. In this paper, we propose a hybrid sentiment analysis (SA) framework that classifies the opinions of Vietnamese reviews into one of two types: positive or negative. The special feature of the proposed framework is that it is built on a combination of three different text representation models that focus on analyzing social media …network language characteristics. Our system achieved an accuracy score of 81.54% on the test set, which is better than other strategies. Based on the experimental results, this work proves that the choice of text representation model determines the performance of the system. Show more

Keywords: Sentiment analysis, sentiment classification, natural language processing, bag-of-words, word2vec, text representation

DOI: 10.3233/JIFS-219278

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 2, pp. 1771-1777, 2022