Fusion: Practice and Applications最新文献

{"title":"Enhancing Heart Disease Diagnosis Using Machine Learning Classifiers","authors":"Ahmed A. H. Alkurdi","doi":"10.54216/fpa.130101","DOIUrl":"https://doi.org/10.54216/fpa.130101","url":null,"abstract":"Heart diseases are the primary cause of death worldwide. The approximate mortality rate due to cardiovascular diseases is a staggering 18 million lives per year. many human lives could be saved with early and accurate diagnosis and prediction of such conditions. Thus, the automation of such a process is crucial and achievable with the rise of machine learning and deep learning capabilities. However, patient data is riddled with issues which must be resolved before they can be used for heart disease prediction. This research aims to improve the accuracy of heart disease diagnosis by utilizing data preprocessing techniques and classification algorithms. These techniques may provide an insight into predicting cardiovascular diseases from subtle clues before any major symptoms arise. The study employs the Heart Disease UCI dataset and follows a systematic approach to train machine learning models in the process of heart disease diagnosis. The approach utilizes a variety of data preprocessing techniques to prepare the data for model training such as MEAN missing value imputation, Normalization, Synthetic Minority Over-sampling Technique (SMOTE), and Correlation. Afterward, the preprocessed data is fed into four popular classification algorithms: Decision Tree, Random Forest, Support Vector Machine (SVM), and k-Nearest Neighbors (k-NN). These algorithms provide a broad evaluation of the dataset. The proposed methodology demonstrates promising results which clearly highlight the value and significance of data preprocessing. This is evident from the achieved accuracy, precision, recall, F1 score and ROC AUC results. In summary, the importance of preprocessing and feature selection is distinct when dealing with datasets containing various challenges. These crucial processes play a central role in building a trustworthy and precise model for heart disease prediction.","PeriodicalId":269527,"journal":{"name":"Fusion: Practice and Applications","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133252918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Improved Equilibrium Optimizer Algorithm for Tackling Global Optimization Problems","authors":"A. Admin, Ibrahim El-Henawy, K. Ahmed","doi":"10.54216/fpa.030101","DOIUrl":"https://doi.org/10.54216/fpa.030101","url":null,"abstract":"This paper introduces a new, metaheuristic optimization algorithm, named an Improved Metaheuristic Equilibrium Optimizer (IMEO). The algorithm Equilibrium Optimizer (EO), is inspired by its method of estimating both equilibrium and dynamics, based on mass balance models. Studying the EO closely, we find that EO does not have the potential to get closer to the optimal global solution when it solves certain problems. To improve EO efficiency, this paper suggests using an improvement, called an elite opposition learning-based, that increases the speed and accuracy of EO convergence, and helps the algorithm to get a better solution. Falling into local optima is a big problem, EO suffers from the fact that when we look deeply at the standard EO mathematical formula, we found that the algorithm is trying to get out of the local optima, but sometimes it can't, so we're introducing a new mathematical formula based on using cosine trigonometric function. To validate the proposed algorithm efficiency, The IMEO algorithm is evaluated on 23 benchmarks and compared with other common naturalistic heuristic algorithms. The statistical analysis shows that the results of IMEO achieve better performance compared to the standard EO and several well-known algorithms on several benchmark issues.","PeriodicalId":269527,"journal":{"name":"Fusion: Practice and Applications","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133144079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integration of Cultural Digital form and Material Carrier form of Traditional Handicraft Intangible Cultural Heritage","authors":"Ali Saadon Al-Ogaili","doi":"10.54216/fpa.050102","DOIUrl":"https://doi.org/10.54216/fpa.050102","url":null,"abstract":"Intangible cultural heritage is the continuous progress of human society. Intangible cultural heritage refers to various traditional cultural expressions that exist in intangible form and are closely related to the lives of the people and inherited from generation to generation. Intangible cultural heritage is a human-oriented living cultural heritage. It emphasizes human-centric skills, experience, and spirit, and is characterized by living changes. What stands out is the intangible attribute, and more emphasis on the quality that does not depend on the material form. The biggest feature of intangible cultural heritage is that it is not divorced from the special life and production methods of the nation, and it is the living of the nation's personality and national aesthetic habits. Appears. It exists on the basis of human beings, using voice, image and skills as means of expression, and passing from word to mouth as a cultural chain to continue. It is the most vulnerable part of living culture and its traditions. Therefore, for the process of inheriting intangible cultural heritage, the inheritance of people is particularly important. The traditional handicraft intangible cultural heritage is one of the best. However, with the rapid development of society, the living environment of intangible cultural heritage has changed, and the intangible cultural heritage of traditional handicraft industry is rapidly declining or even disappearing. In order to protect traditional handicraft intangible cultural heritage, this article studies the influence of the integration of traditional handcrafted intangible cultural heritage with the form of material carrier, reading and analyzing a large number of related documents using the literature survey method, and according to research needs, through the study of the content of the literature In summary, a questionnaire survey method was adopted to investigate traditional handicraft intangible cultural heritage visitors and inheritors. The results of the survey found that visitors’ satisfaction with the integration of digital forms and physical carrier forms of intangible cultural heritage projects was nearly 30% higher than that of unintegrated forms. Inheritors generally believe that integrated research has better publicity and education for traditional handicraft intangible heritage. The merged handmade intangible cultural heritage items are easy to store, retrieve and query, and at the same time help to preserve the related traditional handmade intangible cultural heritage items safely and for a long time, making the traditional handmade intangible cultural heritage items widely spread and shared around the world.","PeriodicalId":269527,"journal":{"name":"Fusion: Practice and Applications","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133465125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Augmenting security for electronic patient health record (ePHR) monitoring system using cryptographic key management schemes","authors":"Ahmed A. Elngar, K. Sagayam","doi":"10.54216/fpa.050201","DOIUrl":"https://doi.org/10.54216/fpa.050201","url":null,"abstract":"Security plays a major role in most of the fields including pharmaceutical field. Authorization and Authentication are the key concepts in supporting notable areas of the cyber-health world. HIPAA's (Health Insurance Portability and Accountability Act) ultimate focus is to preserve the privacy of the health records of an individual without disclosing it and preventing the data from unauthorized access. A complaint key management solution is applied over the patient's health records to reduce the risk factor while engaging with cryptographic mechanisms. Though there are many existing cryptographic algorithms such as Elliptic curve cryptography, Elgammal's key exchange algorithm which provides security to the access of patient's health records, the proposed key management solution will overlay the same variant of security to the Electronic Health Records (EHR). This paper provides the countermeasures for improving security and suggests a key recovery mechanism for the protection of keys used in the security mechanism.","PeriodicalId":269527,"journal":{"name":"Fusion: Practice and Applications","volume":"246 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133934397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"De-Noising and Segmentation of Medical Images using Neutrophilic Sets","authors":"C. S. Manigandaa, V. D. A. Kumar, G. Ragunath, R. Venkatesan, N. Kumar","doi":"10.54216/fpa.110208","DOIUrl":"https://doi.org/10.54216/fpa.110208","url":null,"abstract":"Medical diagnosis and prognosis are challenging tasks due to subjectivity and inherent uncertainty in medical images. Inconsistencies in expert opinions can result in incorrect diagnoses. Neutrosophic theory, a mathematical framework that deals with imprecise or incomplete data, has shown promise in addressing the challenges posed by medical image processing. A neutrosophic theory approach is explored in this paper for de-noising and segmenting medical images. Neutrosophic theory has been utilized to represent the different degrees of truth in each piece of information, resulting in better performance in de-noising and segmentation tasks. Neutosophic theory presents a promising avenue for future investigation in medical image processing as shown in this study.","PeriodicalId":269527,"journal":{"name":"Fusion: Practice and Applications","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122379243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detection and Classification of Alcoholics Using Electroencephalogram Signal and Support Vector Machine","authors":"Shaymaa Adnan .., R. A. Jaafar","doi":"10.54216/fpa.020103","DOIUrl":"https://doi.org/10.54216/fpa.020103","url":null,"abstract":"Alcoholism may be recognized with the use of (EEG) analyzing signals. None-the-less, the analysis of the multi-channel signals of EEG is a complicated issue that usually needs performing complex computation operations and takes quite a long time to execute. The presented research will propose 13 optimal channel to feature extraction. In this research, an innovative horizontal visibility graph entropy (HVGE) method has been proposed for evaluating signals of EEG from controlled drinkers and alcoholic subjects and comparing against an approach of sample entropy (SaE). Values of HVGE and SaE have been obtained from 1200 records of bio-medical signals. While in classification step using SVM as classifier.","PeriodicalId":269527,"journal":{"name":"Fusion: Practice and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123990866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design of Effective Lossless Data Compression Technique for Multiple Genomic DNA Sequences","authors":"Mahmud Alosta, A. Souri","doi":"10.54216/fpa.060103","DOIUrl":"https://doi.org/10.54216/fpa.060103","url":null,"abstract":"In recent years, a massive amount of genomic DNA sequences are being created which leads to the development of new storing and archiving methods. There is a major challenge to process, store or transmit the huge volume of DNA sequences data. To lessen the number of bits needed to store and transmit data, data compression (DC) techniques are proposed. Recently, DC becomes more popular, and large number of techniques is proposed with applications in several domains. In this paper, a lossless compression technique named Arithmetic coding is employed to compress DNA sequences. In order to validate the performance of the proposed model, the artificial genome dataset is used and the results are investigated interms of different evaluation parameters. Experiments were performed on artificial datasets and the compression performance of Arithmetic coding is compared to Huffman coding, LZW coding, and LZMA techniques. From simulation results, it is clear that the Arithmetic coding achieves significantly better compression with a compression ratio of 0.261 at the bit rate of 2.16 bpc.","PeriodicalId":269527,"journal":{"name":"Fusion: Practice and Applications","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124538103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Palmprint Recognition Using Fusion of Local Binary Pattern and Histogram of Oriented Gradients","authors":"Hardik Agarwal, Kanika Somani, Shivangi Sharma, Prerna Arora, Puneet Singh Lamba, Gopal Chaudhary","doi":"10.54216/fpa.010103","DOIUrl":"https://doi.org/10.54216/fpa.010103","url":null,"abstract":"In this paper, unique features of the segmented image samples are extracted by using two major feature extraction techniques: Local Binary Pattern (LBP) and Histogram of Oriented Gradients (HOG). After this, these features are fused to get more precise and productive outcomes. The average accuracy of the three distinct datasets that were generated using the LBP and HOG features are determined. To calculate the accuracy of the three distinct models, classification techniques like KNN and SVM, are adopted.","PeriodicalId":269527,"journal":{"name":"Fusion: Practice and Applications","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127657117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Novel Filter of DWT for Image Processing Applications","authors":"J. A. Eleiwy, Nagham Jaafar","doi":"10.54216/fpa.040205","DOIUrl":"https://doi.org/10.54216/fpa.040205","url":null,"abstract":"In this work, wavelets are used in the analysis of medical images, where the efficiency of mathematics in this field has been proven because the basis of the proposed wavelets in this work is newly constructed mathematical equations, and through the MATLAB program, many programs have been designed to be ready for use in the field of image analysis and study. Physical samples were selected that were compressed using the proposed wavelets, and good results were obtained that prove the efficiency of the method used.","PeriodicalId":269527,"journal":{"name":"Fusion: Practice and Applications","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121246974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Text and Social Analytics with Fusion Techniques Enhance Hospital Health Management","authors":"R. K. A. Ahmed, Ryham Ali Zubaid, Fay Fadhil, Israa Habeeb Naser","doi":"10.54216/fpa.100209","DOIUrl":"https://doi.org/10.54216/fpa.100209","url":null,"abstract":"the impact of social analytics on hospital health management: a multilevel fusion approach for data-driven decision-making and brand improvement. The hospital health management center should use feature extraction techniques to learn more about customers' feelings towards their services and optimize their business strategies and promotions accordingly. The proposed multi-levelhybrid level fusion system architectures can effectively integrate dataimages from multiple sources, including social networks, to collect and process essential data for score level and rank level decision-making. This approach leverages intelligent techniques, such as deep learning models, fuzzy logic, and optimization algorithms, to improve fusion scores and achieve optimal fusion performance. The proposed framework can also be extended to various applications, including multimedia data fusion, e-systems data fusion, and spatial data fusion, to enable intelligent systems for information fusion and decision-making in diverse domains. Therefore, this paper proposes Improved Customer Relation and Business Operations (ICR-BO) to enhance customer relationships in business development using text and social analytics. A case study is carried out to explore the online debate of computer brands operated in hospital environments and Twitter suppliers. The authors used text-mining strategies and social analytics to analyze business operations. Social Media uses data sets to view important observations and trends to identify consumer awareness after collecting critical tweets using Twitter search. The experimental results show that ICR-BO achieves the highest customer relation compared to other existing methods.","PeriodicalId":269527,"journal":{"name":"Fusion: Practice and Applications","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116034018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}