Jordanian Journal of Computers and Information Technology最新文献_第4页

AN IMPROVED FRACTIONAL TWO-DIMENSIONAL PRINCIPAL COMPONENT ANALYSIS FOR FACE RECOGNITION 一种改进的分数二维主成分分析用于人脸识别

IF 1.2

Jordanian Journal of Computers and Information Technology Pub Date : 2022-01-01 DOI: 10.5455/jjcit.71-1637874750

F. Alsaqre

引用次数: 0

CERVICAL CANCER DETECTION AND CLASSIFICATION USING MRIS 子宫颈癌的mri检测与分型

IF 1.2

Jordanian Journal of Computers and Information Technology Pub Date : 2022-01-01 DOI: 10.5455/jjcit.71-1640595124

Ichrak Khoulqi, N. Idrissi

引用次数: 2

Consensual based classification as emergent decisions in a complex system 基于共识的分类作为复杂系统中的紧急决策

IF 1.2

Jordanian Journal of Computers and Information Technology Pub Date : 2022-01-01 DOI: 10.5455/jjcit.71-1638972901

Rabah Mazouzi, M. Ndenga, Cyril de Runz, H. Akdag

引用次数: 0

RULE-BASED APPROACH FOR CONTEXT-AWARE COLLABORATIVE RECOMMENDER SYSTEM 基于规则的上下文感知协同推荐系统

IF 1.2

Jordanian Journal of Computers and Information Technology Pub Date : 2022-01-01 DOI: 10.5455/jjcit.71-1641418357

S. Benhamdi, A. Babouri, Raja Chiky, Jamal Nebhen

引用次数: 0

FEATURE LEVEL FUSION FRAMEWORK FOR BRAIN MR IMAGE CLASSIFICATION USING SUPERVISED DEEP LEARNING AND HAND CRAFTED FEATURES 基于监督深度学习和手工特征的脑磁共振图像分类特征融合框架

IF 1.2

Jordanian Journal of Computers and Information Technology Pub Date : 2022-01-01 DOI: 10.5455/jjcit.71-1655376900

P. N, Prashantha J

引用次数: 0

SENTIMENT ANALYSIS BASED ON PROBABILISTIC CLASSIFIER TECHNIQUES IN VARIOUS INDONESIAN REVIEW DATA 基于概率分类器技术的印尼语评论数据情感分析

IF 1.2

Jordanian Journal of Computers and Information Technology Pub Date : 2022-01-01 DOI: 10.5455/jjcit.71-1646912715

Nur Hayatin, Suraya Alias, L. Hung, M. Sainin

{"title":"SENTIMENT ANALYSIS BASED ON PROBABILISTIC CLASSIFIER TECHNIQUES IN VARIOUS INDONESIAN REVIEW DATA","authors":"Nur Hayatin, Suraya Alias, L. Hung, M. Sainin","doi":"10.5455/jjcit.71-1646912715","DOIUrl":"https://doi.org/10.5455/jjcit.71-1646912715","url":null,"abstract":"Sentiment analysis is the field in data science to achieve a broader holistic view of users’ needs and expectations. Indonesian user opinions have the potential to manage to be valuable information using sentiment analysis tasks. One of the most supervised learning techniques used in Indonesian sentiment analysis is the Naïve Bayes classifier. The classifier can be optimized and tuned in various models to increase the sentiment analysis model performance. This research aims to examine the performance of various Naïve Bayes models in sentiment analysis, especially when implemented in small datasets to handle overfitting problems. Four different Naïve Bayes models used are Gaussian, Multinomial, Complement, and Bernoulli. We also analyse the effect of various pre-processing techniques on the models’ performance. Moreover, we build the first fashion dataset from the Indonesian marketplace which has a unique character compared to the datasets from other domains. Finally, we also use the various dataset in the experiment to test the Naïve Bayes models' performance. From the experiment result, Complement Naïve Bayes is superior to other models, especially in handling overfitting with F1-score of approximately 0.82.","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70821291","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}

引用次数: 1

Hybridization of Arithmetic Optimization with Great Deluge Algorithms for Feature Selection Problems in Medical Diagnoses 医学诊断特征选择问题的算法优化与大洪水算法的杂交

IF 1.2

Jordanian Journal of Computers and Information Technology Pub Date : 2022-01-01 DOI: 10.5455/jjcit.71-1639410312

Mohammed Alweshah

{"title":"Hybridization of Arithmetic Optimization with Great Deluge Algorithms for Feature Selection Problems in Medical Diagnoses","authors":"Mohammed Alweshah","doi":"10.5455/jjcit.71-1639410312","DOIUrl":"https://doi.org/10.5455/jjcit.71-1639410312","url":null,"abstract":"In the field of medicine, there is a need to filter data to find information that is relevant for specific research problems. However, in the realm of scientific study, the process of selecting the appropriate data or features is a substantial and challenging problem. Therefore, in this paper, two wrapper feature selection (FS) methods based on novel metaheuristic algorithms named the arithmetic optimization algorithm (AOA) and the great deluge algorithm (GDA) were used to attempt to tackle the medical diagnostics challenge. Two methods, AOA and AOA-GD were tested on 23 medical benchmark datasets. According to all of the experimental data, the hybridization of the GDA with the AOA considerably increased the AOA’s search capability. The AOA-GD method was then compared with two previous wrapper FS approaches;namely, the coronavirus herd immunity optimizer with greedy crossover operator (CHIO-GC) and the binary moth flame optimization with Lévy flight (LBMFO_V3). When applied to the 23 medical benchmark datasets, the AOA-GD achieved an accuracy rate of 0.80, thereby surpassing both the CHIO-GC and LBMFO V3.","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70820707","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}

引用次数: 5

An Early Detection Model for KerberoastingAttacks and Dataset Labeling kerberos攻击的早期检测模型及数据集标注

IF 1.2

Jordanian Journal of Computers and Information Technology Pub Date : 2022-01-01 DOI: 10.5455/jjcit.71-1661423262

Remah Younisse, Mouhammd Alkasassbeh, Mohammad Almseidin, Hamza Abdi

{"title":"An Early Detection Model for Kerberoasting\u0000Attacks and Dataset Labeling","authors":"Remah Younisse, Mouhammd Alkasassbeh, Mohammad Almseidin, Hamza Abdi","doi":"10.5455/jjcit.71-1661423262","DOIUrl":"https://doi.org/10.5455/jjcit.71-1661423262","url":null,"abstract":"The wild nature of humans has become civilized, and the weapons they use to attack each other are now digitized. Security over the Internet usually takes a defensive shape, aiming to fight against attacks created for malicious reasons. Invaders’ actions over the internet can take patterns by going through specific steps every time they attack. These patterns can be used to predict, mitigate and stop these attacks. This study proposes a method to label datasets related to multi-stage attacks according to attack stages rather than the attack type. These datasets can be used later in machine learning models to build intelligent defensive models. On the other hand, we propose a method to predict and early kill attacks in an active directory environment, such as Kerberoasting attacks. In this study, we have collected the data related to a suggested Kerberoasting attack scenario in pcap files. Every pcap file contains the data related to a particular stage of the attack lifecycle, the extracted information from the pcap files was used to highlight the features and specific activities during every stage. The information was used to draw an efficient defensive plan against the attack. Here we propose a methodology to draw equivalent defensive plans for other similar attacks as the Kerberoasting attack covered in this study.","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70821062","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}

引用次数: 2

DES22: DES BASED ALGORITHM WITH IMPROVED SECURITY Des22:基于des的算法，提高了安全性

IF 1.2

Jordanian Journal of Computers and Information Technology Pub Date : 2022-01-01 DOI: 10.5455/jjcit.71-1632868199

Malek Barhoush, Bilal Alguni, Rafat Hammad, Mohammad Fawareh, Rana Hassan

引用次数: 1

FULLY OPTIMIZED ULTRA WIDEBAND RF RECEIVER FRONT END 全面优化的超宽带射频接收机前端

IF 1.2

Jordanian Journal of Computers and Information Technology Pub Date : 2022-01-01 DOI: 10.5455/jjcit.71-1644147942

R. Khatri, D. Mishra

引用次数: 0