An Improved Internet of Thing-based Optimized SVM Approach for ECG-founded Cardiac Arrhythmia Classification

Yogendra Narayan; Beemkumar; Mary Christeena; Lovish; Rishabh; Aws Zuhair

doi:https://doi.org/10.54216/JISIoT.130106

Fusion: Practice and Applications | 2024

Fusion of Forensic Analysis of Mobile Devices: Integrating Multi-Criteria Decision Methods and Case Study Insights

This study employed a Multi-Criteria Decision Analysis (MCDM) approach, utilizing the DEMATEL and TOPSIS methodologies, to assess the effectiveness of forensic tools designed for mobile devices, with a specific emphasis on Android and iOS platforms. The investigation evaluated technologies used for collecting, retrieving, and validating data in the Cyber Forensic Field Triage paradigm, with a focus on rapidly identifying and interpreting digital evidence. The study incorporated several factors and expert preferences, concluding that the Android Triage and Andriller tools were the most efficient.

groups

Jorge B. Rubio Peñaherrera mail -

Kevin Mauricio T. Diaz mail -

Adam Marks mail

link https://doi.org/10.54216/FPA.160203

Volume & Issue

Vol. Volume 16 / Iss. Issue 2

Details open_in_new

International Journal of Neutrosophic Science | 2024

Numerical Solutions for Fractional Multi-Group Neutron Diffusion System of Equations

This paper addresses fractional-order versions of multi-group neutron diffusion systems of equations, focusing on two numerical solutions. First, it employs the Laplace transform method to solve the classical version of multi-group neutron diffusion equations. Subsequently, it transforms these equations into their corresponding fractional-order versions using the Caputo differentiator. To handle the resultant fractional-order system, a novel approach is introduced to reduce it from a system of 2α-order to a system of α-order. This converted system is then solved using the so-called Modified Fractional Euler Method (MFEM). As far as we know, this is the first time that such numerical schemes have been used to deal with the systems at hand. The paper covers the multi-group neutron diffusion equations in spherical, cylindrical, and slab reactors, all solved and converted for verification purposes.

groups

Mohammed Shqair mail -

Iqbal M. Batiha mail -

Mohammed H. E. Abu-Sei’leek mail -

Shameseddin Alshorm mail -

Amira Abdelnebi mail -

Iqbal H. Jebril mail -

S. A. Abd El-Azeem mail

link https://doi.org/10.54216/IJNS.240401

Volume & Issue

Vol. Volume 24 / Iss. Issue 4

Details open_in_new

International Journal of Neutrosophic Science | 2024

Harnessing Dimensionality Reduction with Neutrosophic Net-RBF Neural Networks for Financial Distress Prediction

Neutrosophy is the study of neutralities and extends the discussion of the truth of opinions. Neutrosophic logic may be employed in any domain, for providing the solution for the ambiguity problems. Several real-time data experience problems such as indeterminacy, incompleteness, and inconsistency. A fuzzy set provides an uncertain solution, and intuitionistic fuzzy set handles incomplete data, but both fail to manage uncertain data. Before bankruptcy, financial distress is the early stage. Bankruptcies caused by financial problems can be seen in the financial statement of the company. The capability to predict financial problems became a crucial area of research since it provides earlier warning for the company. Moreover, predicting financial problems is advantageous for creditors and investors. In this article, we develop a new Dimensionality Reduction with Neutrosophic Net-RBF Neural Networks (DR-NSRBFNN) technique for FCP process. The DR-NSRBFNN technique concentrates on the predictive modelling of financial distress. In the DR-NSRBFNN technique, two major stages are involved. In the preliminary phase, the high dimensionality features can be reduced by the use of arithmetic optimization algorithm (AOA). In the second phase, the DR-NSRBFNN technique applies the NSRBFNN model to predict financial distress. The performance evaluation of the DR-NSRBFNN technique can be examined using distinct aspects. The widespread study stated the improved performance of the DR-NSRBFNN technique compared to other systems

groups

Tawfiq Hasanin mail

link https://doi.org/10.54216/IJNS.240402

Volume & Issue

Vol. Volume 24 / Iss. Issue 4

Details open_in_new

International Journal of Neutrosophic Science | 2024

Enhancing Inventory Management through Advanced Technologies and Mathematical Methods: Utilizing Neutrosophic Fuzzy Logic

Optimal inventory management is one of the most critical components for companies to thrive in the competitive market while meeting their customers’ demands, reducing costs, and developing their operations. In this paper, the utilization of different technologies and instruments ranging from the most modern ones to mathematical ones was analyzed to demonstrate how the system can function successfully. It is expected that Neutrosophic fuzzy logic is one of the most complicated approaches that allow for proper uncertainty management, forecasting, and inventory control improvements. Fundamentally, the process could be that much more insightful due to the availability of mathematical modelling and on-the-go support systems. Through the use of dynamic programming with the help of Python tools to process these models, Full optimization under fuzzy demand is possible to achieve. Therefore, one could conclude that companies have many opportunities to develop their operations, reduce costs, and keep their customers happy even in a highly dynamic and uncertain business environment.

groups

C. Balakrishna Moorthy mail -

D. Rajani mail -

A. P. Pushpalatha mail -

S. Ramya mail -

A. Selvaraj mail -

Mohit Tiwari mail

link https://doi.org/10.54216/IJNS.240403

Volume & Issue

Vol. Volume 24 / Iss. Issue 4

Details open_in_new

International Journal of Neutrosophic Science | 2024

Neutrosophic Delphi for evaluating sustainability models of native and non-native digital media.

Technological globalization has brought many changes in different fields, one of which is related to the media. In the case of traditional media, they are forced to find new ways to rethink practice, while digital media emerges in a digital context, albeit with limitations. Experience In both cases, sustainability is one of the factors to be rethought. Building on this, the overall objective is to use the Neutrosophic Delphi method to investigate the extent to which native and non-native digital media have durable patterns that allow them to be successful in their communication activities. To achieve this objective, we work with a mixed methodology, that is, qualitative and quantitative approaches: for qualitative, we use interview methods, for quantitative, we use survey methods. The population studied included both native and non-native digital media. Specifically, the survey and interviews were applied to a group of media owners. The article concludes with a series of Neutrosophic reflections on the conditions of media sustainability.

groups

Karla Valeria A. Sigcha mail -

Evelyn M. Lema Basantes mail -

Lourdes Y. Cabrera Martinez mail -

Tonguc Cagin mail

link https://doi.org/10.54216/IJNS.240404

Volume & Issue

Vol. Volume 24 / Iss. Issue 4

Details open_in_new

International Journal of Neutrosophic Science | 2024

Leveraging Bat Algorithm with Rough Neutrosophic Soft Set for Enhanced Oral Cancer Detection and Classification

Neutrosophic soft sets (NSS) are highly effective in representing neutral uncertain data. NSS model attracts several authors because it has huge range of applications in several areas such as decision-making, data analysis, smoothness of functions, probability theory, measurement theory, predicting, and operations research. Oral squamous cell carcinoma (OSCC) is the most general tumor around the world and its occurrence is on the increase in several populations. Early diagnosis plays vital role in improving diagnosis, treatment outcomes and survival rates. Although the new developments in understanding molecular mechanisms, late analysis and the implementation of precision medicine for OSCC patients continue to present problems. Early diagnosis and detection can support doctors in offering optimum patient care and effectual treatment. In recent years, the execution of several machine-learning (ML) approaches in cancer analysis has provided valuable insights, facilitating more effective and precise treatment decision-making. Oral Cancer screening can progress with the execution of artificial intelligence (AI) approaches. AI offers support to the oncology region by correctly examining a huge database in many imaging modalities. This article develops a Bat Algorithm with Rough Neutrosophic Soft Set for Oral Cancer Diagnosis (BARNSS-OCD) technique. The main intention of the BARNSS-OCD technique is to exploit deep learning (DL) model for enhanced identification of OC. In the BARNSS-OCD technique, median filtering (MF) is used for image pre-processing and the feature extraction takes place using deep convolutional neural network (DCNN) model. In addition, bat algorithm (BA) is used for the hyperparameter selection of the DCNN model. For OC detection process, the BARNSS-OCD technique applies RNSS model. To exhibit the improved performance of the BARNSS-OCD technique, a sequence of experiments is involved. The simulation outcomes indicate that the BARNSS-OCD technique gains better performance compared to other DL models

groups

Arwa Darwish Alzughaibi mail -

Ebtesam Al-Mansor mail

link https://doi.org/10.54216/IJNS.240405

Volume & Issue

Vol. Volume 24 / Iss. Issue 4

Details open_in_new

International Journal of Neutrosophic Science | 2024

Neutrosophic analysis of avocado oil extraction conditions by varieties

Avocado oil is defined by the composition of the fruit and its nutritional value, which according to previous studies suggests that it provides health benefits, reduces cardiovascular disease, and provides anti-inflammatory and antioxidant effects. However, the nutritional value is determined by the amount of acid. Monounsaturated and polyunsaturated fatty acids make this product useful in cooking. The quality of the oil is affected by the method and conditions of extraction, as these processes affect the preservation of nutrients and beneficial properties of avocado oil. This study aimed to conduct a Neutrosophic analysis of avocado oil extraction conditions depending on the cultivar, dehydration and cold pressing conditions. As a result, the physicochemical properties of the reaction variables were determined and the values of acidity, moisture, density, and impurities were obtained for the oil obtained from the Hass variety by dehydration and pressing.

groups

María M. Morales Padilla mail -

Cristian I. Cuchipe Chacha mail -

Vicente A. Guerrón Troya mail -

Kholmuminov Shayzak Rakhmatovich mail

link https://doi.org/10.54216/IJNS.240406

Volume & Issue

Vol. Volume 24 / Iss. Issue 4

Details open_in_new

International Journal of Neutrosophic Science | 2024

Enhancing Guinea Pig Farming: A Neutrosophic Approach with Interval-Valued and Bipolar Sets in Decision-Making Methods

The study emphasizes the need of implementing several ways to promote guinea pig farming in small family units. It highlights the relevance of enhanced nutrition, effective health management, genetic enhancement, and acceptable habitat conditions as essential factors for enhancing productivity and profitability. Suggestions encompass the adoption of advanced breeding methods, offering training and technical support, and expanding the range of goods and markets to ensure the long-term economic viability of guinea pig farming. The utilization of neutrosophic sets provided a strong framework for assessing these techniques, enabling a thorough study that considers the inherent uncertainties in decision-making processes. To enhance future study, it is recommended to improve and broaden neutrosophic approaches to comprehend the intricacies of guinea pig farming systems more effectively. It will be beneficial to create more advanced models that include a broader set of factors and extensive data, as well as to undertake longitudinal studies to evaluate the long-term effects. It is essential to work together with local communities to customize tactics that are suitable for specific geographical conditions and socioeconomic contexts. This is necessary to ensure that these interventions are practical and successful.

groups

Patricia M. Andrade-Aulestia mail -

Luis A. Chicaiza-Sánchez mail -

César R. Delgado-Acurio mail -

Rafael A. Garzón-Jarrín mail -

Tonguc Cagin mail

link https://doi.org/10.54216/IJNS.240407

Volume & Issue

Vol. Volume 24 / Iss. Issue 4

Details open_in_new

International Journal of Neutrosophic Science | 2024

Possibility Fermatean Neutrosophic Soft Set

In this paper, we introduce the concept of Possibility Fermatean Neutrosophic Soft Set and define some related concepts such as Possibility Fermatean Neutrosophic Soft subset, Possibility Fermatean Neutrosophic Soft null set, and Possibility Fermatean Neutrosophic Soft universal set. Then, we define set-theoretical operations of Possibility Fermatean Neutrosophic Soft Sets such as union, intersection, and complement, and investigate some properties of these operations. We also introduce AND-product and OR-product operations between two Possibility Fermatean Neutrosophic Soft Sets. We propose a decision-making method called the Possibility Fermatean Neutrosophic Soft decision-making method (PFNS-decision-making method) which can be applied to decision-making problems involving uncertainty based on AND-product operation. We finally give a numerical example to display the application of the method that can be successfully applied to the problems.

groups

Shawkat Alkhazaleh mail -

Belal Batiha mail -

Areen Al-khateeb mail -

Hamzeh Zureigat mail -

Abedallah Al-shboul mail -

Khaldoun Batiha mail

link https://doi.org/10.54216/IJNS.240408

Volume & Issue

Vol. Volume 24 / Iss. Issue 4

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2024

An Improved Internet of Thing-based Optimized SVM Approach for ECG-founded Cardiac Arrhythmia Classification

Cardiovascular diseases (CVD) stand as the leading cause of global mortality, claiming millions of lives annually. An electrocardiogram (ECG) records the heart's electrical activity based on the Internet of Things (IoT), crucial in detecting cardiac arrhythmias (CA), characterized by irregular heart rates and rhythms. Signals from the MIT-BIH Arrhythmia Physio net database are analyzed. This chapter aims to propose a hybrid approach merging Genetic Algorithm-Support Vector Machine (GSVM) and Particle Swarm Optimization-Support Vector Machine (PSVM) for CA classification. The study introduces an algorithm for categorizing ECG beats into six groups using Independent Component Analysis (ICA)-derived features. Optimal SVM settings are determined using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) on ICA features computed via non-parametric power spectral estimation. The research delves into the origins and methodologies of GA and PSO. Simulation results comparing GSVM and PSVM are presented, emphasizing PSVM's superior performance in accuracy, sensitivity, specificity, and positive predictivity. Detailed performance metrics, including Sensitivity, Specificity, Positive Predictivity, and Accuracy percentages, are scrutinized and compared against the top classifier. The findings endorse PSVM's superiority over GSVM, indicating enhanced performance across multiple evaluation criteria.

groups

Yogendra Narayan Prajapati mail -

Beemkumar N. mail -

Mary Christeena Thomas mail -

Lovish Dhingra mail -

Rishabh Bhardwaj mail -

Aws Zuhair Sameen mail

link https://doi.org/10.54216/JISIoT.130106

Volume & Issue

Vol. Volume 13 / Iss. Issue 1

Details open_in_new