International Journal of Advanced Computer Science and Applications最新文献

{"title":"Histogram Gradient Boosting Classifier-Based UWSN Cyber Attack Detection Incorporating Environmental Factors (HGBoostUCAD)","authors":"Hamid Ouidir, Amine Berqia, Siham Aouad","doi":"10.14569/ijacsa.2025.0161217","DOIUrl":"https://doi.org/10.14569/ijacsa.2025.0161217","url":null,"abstract":"Underwater Wireless Sensor Networks (UWSNs) are commonly employed for exploring and exploiting aquatic areas, and its role is very important and more beneficial precisely in hostile and constrained marine environments. However, their security is more critical than terrestrial wireless sensor networks (TWSNs) due to the space in which they are deployed, the wireless communication medium, and the cost of damage repair, and their protection is a problematic issue that needs to be continuously resolved. Consequently, it is highly recommended see required to take procedure to protect UWSNs against attacks and intrusion and maintain service quality. In general, existing works on machine learning-based intrusion detection system (IDS) and cyber-attack detection approaches for (UWSNs) utilize dedicated datasets designed for (WSNs) without adapting them to the aquatic environment. Furthermore, these studies analyze the enhancement of UWSN performance based on network metrics separately from machine learning model metrics, and vice versa. In this way, this paper proposes a novel cybersecurity detection approach-based model learning Histogram Gradient Bosting (HGB) classifier called (HGBoostUCAD). It classifies four types of DoS attacks (Blackhole, Grayhole, Flooding, and Scheduling), employing an adjusted dataset for (IDS) in wireless sensor networks (WSN-DS) taking into account simulate realistic environmental factors: salinity, temperature, deep through Mackenzie’s equation and node movement in training data. The insight of simulation results obtained, shows that our method reached 97% as accuracy and 96% as precision also outperformed both Deep Neural Network (DNN) as well as the recent study Hyper_RNN_SVM eventually referenced in this research, in terms of machine learning model metrics. In addition to machine learning model metrics, our approach provides network measurements by DoS attack type.","PeriodicalId":13824,"journal":{"name":"International Journal of Advanced Computer Science and Applications","volume":"16 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://thesai.org/Downloads/Volume16No12/Paper_17-Histogram_Gradient_Boosting_Classifier_Based_UWSN_Cyber_Attack_Detection.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147914143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Utilizing the Metaverse in Astrosociology: Examine Students' Perspectives of Space Science Education","authors":"Yahya Almurtadha","doi":"10.14569/ijacsa.2024.0150373","DOIUrl":"https://doi.org/10.14569/ijacsa.2024.0150373","url":null,"abstract":"Big economic countries must invest in space skills to create a favorable business environment, particularly in KSA considering the present mindset in outer space. KSA's vast landmass is a tremendous asset that makes it the perfect position to provide space services throughout the Middle East and the world. Space science education is becoming increasingly important, requiring advanced technology and computational skills to benefit early-career scientists. The Ministry of Education in KSA has declared that students will take Earth and Space Sciences to prepare them for global competition. Traditional learning experiences seem to have little to no impact on students' conceptual understandings of the space science courses. The sociological interests of Generation Z serve as the foundation for modern Metaverse approaches. Students' comprehension and interest in studying space and the galaxy are increased by provided a simulation of space travel using metaverse technology. The major goal of this study is to underline the significance and usefulness of employing metaverse technology while creating a new space science curriculum to advance knowledge in the field of space scientific education. Another goal is to introduce the value of astrosociology in understanding how people might interact with one another in space. A voluntary survey was completed by 39 students prior to their training in the metaverse space simulation as part of this study. They then used the space simulation with careful observation. After that, they reply to a follow-up survey. The findings supported the suggestion that the metaverse should be included in space science curricula. A number of comments and interests also arise on the viability of space travel, social interaction, and the advantages of using the metaverse to research these issues.","PeriodicalId":13824,"journal":{"name":"International Journal of Advanced Computer Science and Applications","volume":"15 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"http://thesai.org/Downloads/Volume15No3/Paper_73-Utilizing_the_Metaverse_in_Astrosociology.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147890165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of K-Nearest Neighbor, Naive Bayes Classifier, Decision Tree, and Logistic Regression in Classification of Non-Performing Financing","authors":"R. Putra, Iis Dewi Ratih","doi":"10.47679/ijasca.v2i2.35","DOIUrl":"https://doi.org/10.47679/ijasca.v2i2.35","url":null,"abstract":"The Non-Performing Financing (NPF) indicator of one of the Islamic Banks in Indonesia in the 1st to 3rd quarter of 2021 in a row of 9.69%; 9.97%; 9.46%. The NPF movement tends to improve slightly from time to time but still exceeds the maximum limit stipulated in Bank Indonesia’s Regulation Number 23/2/PBI/2021, which is no more than 5%. This shows that the Islamic bank has a financing performance that can be said to be less good. Preventive steps that can be taken to reduce the NPF ratio in order to improve the health of the bank is to classify prospective financing customers. This research was conducted using the K-Nearest Neighbor (KNN), Naive Bayes Classifier (NBC), Decision Tree, and Logistics Regression classification methods to predict potential financing customers. The dataset is divided into 80% training and 20% testing. It was found that the best classification result was the Naive Bayes Classifier in the proportion of distribution of 80% training data and 20% testing data with an accuracy value of 84.69%, sensitivity of 58.25%, and specificity of 90.16%.","PeriodicalId":13824,"journal":{"name":"International Journal of Advanced Computer Science and Applications","volume":"34 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75002115","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":"Simulation of fire exposure behavior to building structural elements using LISA FEA V.8.","authors":"Aco Wahyudi Efendi","doi":"10.47679/ijasca.v2i2.31","DOIUrl":"https://doi.org/10.47679/ijasca.v2i2.31","url":null,"abstract":"The purpose of this work is to evaluate the most generally used techniques for measuring the thermal conductivity of concrete, as well as to consider the variables influencing the thermal conductivity of cement-based materials. Based on previous research indicating that the pattern of heat flow can be modeled in a numerical analysis program and provide a hue of coverage and differences in indoor temperature conditions, as well as the impact that occurs on several elements in the room, a heat simulation analysis was performed in this study due to a fire. \u0000The researchers in this study simulated the flow pattern from the temperature that occurred due to fire in a room measuring 4000x4000 mm with a wall thickness of 200 mm with Hebel/light brick material, floor plate thickness was 120 mm, and the size of the building column structural elements was 400x400 mm with the material reinforced concrete. \u0000According to the simulation results of a fire that occurred in the middle of the room with two conditions for installing hebel walls, namely covering the building structure columns and those behind the building structure columns, there is an increase in the temperature of the column with a ratio of 1.062 in the two conditions where the temperature of the wall lining the column is 6.28% lower than the temperature of the wall behind the column, while the heat flux magnitude that occurs is lower.","PeriodicalId":13824,"journal":{"name":"International Journal of Advanced Computer Science and Applications","volume":"31 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75355248","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 Exploration into Hybrid Agile Development Approach","authors":"Siti Sarah Maidin, Norzariyah Yahya","doi":"10.47679/ijasca.v2i2.32","DOIUrl":"https://doi.org/10.47679/ijasca.v2i2.32","url":null,"abstract":"The aim of this paper is to provide a review of the different hybrid agile models. This study raised the question “what are the types of hybrid agile models and their features”? The systematic review was done using Preferred Reporting Items for Systematic Reviews and Meta-Analyses Model for comprehensive searching. Scopus is used as the database for searching articles. A total of 131 papers related to agile and hybrid agile models were retrieved and finally after screening and filtering, only 26 papers were included in the study. This paper probes into the features of agile and hybrid agile models and thus recommends hybrid agile models as one of the best-suited models in software development due to several reasons. Some of the reasons are due to its comprehensiveness in managing a large-scale project with good documentation and developing better methods for business analysis. This paper concludes by providing insight into the different types of hybrid agile models in software development. This paper starts with an Introduction section, followed by a Materials and Method section, continued with a Results and Discussion section, and finally concludes the research in the Conclusion section. \u0000 ","PeriodicalId":13824,"journal":{"name":"International Journal of Advanced Computer Science and Applications","volume":"58 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83434945","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":"A Study on Sentiment Analysis Techniques of Twitter Data","authors":"A. Alsaeedi, M. Zubair","doi":"10.14569/IJACSA.2019.0100248","DOIUrl":"https://doi.org/10.14569/IJACSA.2019.0100248","url":null,"abstract":"The entire world is transforming quickly under the present innovations. The Internet has become a basic requirement for everybody with the Web being utilized in every field. With the rapid increase in social network applications, people are using these platforms to voice them their opinions with regard to daily issues. Gathering and analyzing peoples’ reactions toward buying a product, public services, and so on are vital. Sentiment analysis (or opinion mining) is a common dialogue preparing task that aims to discover the sentiments behind opinions in texts on varying subjects. In recent years, researchers in the field of sentiment analysis have been concerned with analyzing opinions on different topics such as movies, commercial products, and daily societal issues. Twitter is an enormously popular microblog on which clients may voice their opinions. Opinion investigation of Twitter data is a field that has been given much attention over the last decade and involves dissecting “tweets” (comments) and the content of these expressions. As such, this paper explores the various sentiment analysis applied to Twitter data and their outcomes.","PeriodicalId":13824,"journal":{"name":"International Journal of Advanced Computer Science and Applications","volume":"9 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91137688","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":"Handwriting Recognition using Artificial Intelligence Neural Network and Image Processing","authors":"Sara Aqab, Muhammad Tariq","doi":"10.14569/ijacsa.2020.0110719","DOIUrl":"https://doi.org/10.14569/ijacsa.2020.0110719","url":null,"abstract":"Due to increased usage of digital technologies in all sectors and in almost all day to day activities to store and pass information, Handwriting character recognition has become a popular subject of research. Handwriting remains relevant, but people still want to have Handwriting copies converted into electronic copies that can be communicated and stored electronically. Handwriting character recognition refers to the computer's ability to detect and interpret intelligible Handwriting input from Handwriting sources such as touch screens, photographs, paper documents, and other sources. Handwriting characters remain complex since different individuals have different handwriting styles. This paper aims to report the development of a Handwriting character recognition system that will be used to read students and lectures Handwriting notes. The development is based on an artificial neural network, which is a field of study in artificial intelligence. Different techniques and methods are used to develop a Handwriting character recognition system. However, few of them focus on neural networks. The use of neural networks for recognizing Handwriting characters is more efficient and robust compared with other computing techniques. The paper also outlines the methodology, design, and architecture of the Handwriting character recognition system and testing and results of the system development. The aim is to demonstrate the effectiveness of neural networks for Handwriting character recognition.","PeriodicalId":13824,"journal":{"name":"International Journal of Advanced Computer Science and Applications","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79943082","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":"Global and Local Characterization of Rock Classification by Gabor and DCT Filters with a Color Texture Descriptor","authors":"J. W. Vangah, S. Ouattara, G. Ouattara, A. Clément","doi":"10.14569/ijacsa.2019.0100401","DOIUrl":"https://doi.org/10.14569/ijacsa.2019.0100401","url":null,"abstract":"In the automatic classification of colored natural textures, the idea of proposing methods that reflect human perception arouses the enthusiasm of researchers in the field of image processing and computer vision. Therefore, the color space and the methods of analysis of color and texture, must be discriminating to correspond to the human vision. Rock images are a typical example of natural images and their analysis is of major importance in the rock industry. In this paper, we combine the statistical (Local Binary Pattern (LBP) with Hue Saturation Value (HSV) and Red Green Blue (RGB) color spaces fusion) and frequency (Gabor filter and Discrete Cosine Transform (DCT)) descriptors named respectively Gabor Adjacent Local Binary Pattern Color Space Fusion (G-ALBPCSF) and DCT Adjacent Local Binary Pattern Color Space Fusion (D-ALBPCSF) for the extraction of visual textural and colorimetric features from direct view images of rocks. The textural images from the two G-ALBPCSF and D-ALBPCSF approaches are evaluated through similarity metrics such as Chi2 and the intersection of histograms that we have adapted to color histograms. The results obtained allowed us to highlight the discrimination of the rock classes. The proposed extraction method provides better classification results for various direct view rock texture images. Then it is validated by a confusion matrix giving a low error rate of 0.8% of classification.","PeriodicalId":13824,"journal":{"name":"International Journal of Advanced Computer Science and Applications","volume":"43 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86643526","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":"A New Strategy for the Morphological and Colorimetric Recognition of Erythrocytes for the Diagnosis of Forms of Anemia based on Microscopic Color Images of Blood Smears","authors":"Jerome Nango, J. N. Alico, S. Ouattara, A. Clément","doi":"10.14569/ijacsa.2020.0110762","DOIUrl":"https://doi.org/10.14569/ijacsa.2020.0110762","url":null,"abstract":"The detection of red blood cells based on morphology and colorimetric appearance is very important in improving hematology diagnostics. There are automatons capable of detecting certain forms, but these have limitations with regard to the formal identification of red blood cells because they consider certain cells to be red blood cells when they are not and vice versa. Other automata have limitations in their operation because they do not cover a sufficient area of the blood smear. In spite of their performance, biologists have very often resorted to the manual analysis of blood smears under an optical microscope for a morphological and colorimetric study. In this paper, we present a new strategy for semi-automatic identification of red blood cells based on their isolation, their automatic color segmentation using Otsu's algorithm and their morphology. The algorithms of our method have been implemented in the programming environment of the scientific software MATLAB resulting in an artificial intelligence application. The application, once launched, allows the biologist to select a region of interest containing the erythrocyte to be characterized, then a set of attributes are computed extracted from this target red blood cell. These attributes include compactness, perimeter, area, morphology, white and red proportions of the erythrocyte, etc. The types of anemia treated in this work concern the iron-deficiency, sickle-cell or falciform, thalassemia, hemolytic, etc. forms. The results obtained are excellent because they highlight different forms of anemia contracted in a patient.","PeriodicalId":13824,"journal":{"name":"International Journal of Advanced Computer Science and Applications","volume":"269 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90252768","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":"Cardiorespiratory Mortality Prediction Based on Air Pollution Using Tree-Based Ensemble Models","authors":"Akibu Mahmoud Abdullahi","doi":"10.47679/ijasca.v2i2.30","DOIUrl":"https://doi.org/10.47679/ijasca.v2i2.30","url":null,"abstract":"Air pollution has a substantial negative impact on human wellbeing and health. Cardiorespiratory mortality is one of the primary effects of air pollution. In this study, we provide analysis of air pollution, cardiorespiratory mortality and the cardiorespiratory mortality is predicted based on air pollution using tree-based ensemble models. The tree-based ensemble models utilized in this study are Voting Regressor (VR), Random Forest (RF), Gradient Tree Boosting (GB), and Extreme Gradient Boosting (XGBoost). The used dataset contains data for five research locations: Shah Alam (SA), Klang (KLN), Putrajaya (PUJ), Cheras, Kuala Lumpur (CKL), and Petaling Jaya (PJ) from January 2006 to December 2016. The results show that XGBoost and VR models outperformed the rest of the models with the best evaluation metric scores in the Klang study area, XGBoost(MAE:0.005, RMSE:0.010, MAPE:0.70%) and VR (MAE:0.005, RMSE:0.011, MAPE:0.70%). The results reveal that the utilized models provided an excellent and accurate prediction of cardiorespiratory mortality based on air pollution and can follow the trend of cardiorespiratory mortality.","PeriodicalId":13824,"journal":{"name":"International Journal of Advanced Computer Science and Applications","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76472797","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}