International Journal of Advances in Soft Computing and its Applications最新文献_第3页

Assessing and Achieving Intended Learning Outcomes against the NQF Case of CS Program at Jadara University 基于Jadara大学CS项目NQF案例的预期学习成果评估与实现

International Journal of Advances in Soft Computing and its Applications Pub Date : 2022-07-20 DOI: 10.15849/ijasca.220720.10

B. Zaqaibeh

引用次数: 0

Artificial Intelligence Scheme for Medical Images Classification and Prediction 医学图像分类与预测的人工智能方案

International Journal of Advances in Soft Computing and its Applications Pub Date : 2022-07-20 DOI: 10.15849/ijasca.220720.04

Basil Al-Kasasbeh

{"title":"Artificial Intelligence Scheme for Medical Images Classification and Prediction","authors":"Basil Al-Kasasbeh","doi":"10.15849/ijasca.220720.04","DOIUrl":"https://doi.org/10.15849/ijasca.220720.04","url":null,"abstract":"Medicine is the industry where smart technologies and artificial intelligence are most commonly used. Medical imaging is usually used for tumor diagnosis; this includes Computer Tomography and Magnetic Resonance Imaging. Early tumor detection in various organs based on such images is important. This study intended to present an Adaptive Convolution Neural Networks (ACNN) based method for tumor detection in the brain. The ACNN will utilize a modified stochastic gradient descent (MSGD) training algorithm with adaptive momentum and learning rates to speed up the convergence of the error, which will speed up the classification process and improve the accuracy. MSGD is implemented such as when the loss increases, the learning rate increase, and vice versa. The proposed modifications allow the network to increase the learning rate at the beginning of the training process and slow down as the network outcomes reach stabilized conditions. The proposed method results were compared against the performance of several conventional combinations of CNN with several machine learning classifiers. The test results show that the proposed method outperformed the performance of the CNN with all the above-said adaptations. Accordingly, the contributions of this study are (1) improving the ACNN training algorithm for the tumor classification problem and (2) proposing original CNN architectures specialized for tumor classification. Keywords: artificial intelligence; convolution neural network; medical images processing; tumor classification, tumor detection.","PeriodicalId":38638,"journal":{"name":"International Journal of Advances in Soft Computing and its Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41363303","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: 0

A bibliometric analysis of the International Journal of Advances in Soft Computing and its Applications: Research influence and Contributions 《国际软计算进展及其应用杂志:研究影响与贡献》的文献计量学分析

International Journal of Advances in Soft Computing and its Applications Pub Date : 2022-07-20 DOI: 10.15849/ijasca.220720.12

Yousef Jaradat, Mohammad Alia, M. Masoud, Ahmad M. Manasrah, Iqbal Jebreil, Alaa’ Garaibeh, Sarah Al-Arasi

{"title":"A bibliometric analysis of the International Journal of Advances in Soft Computing and its Applications: Research influence and Contributions","authors":"Yousef Jaradat, Mohammad Alia, M. Masoud, Ahmad M. Manasrah, Iqbal Jebreil, Alaa’ Garaibeh, Sarah Al-Arasi","doi":"10.15849/ijasca.220720.12","DOIUrl":"https://doi.org/10.15849/ijasca.220720.12","url":null,"abstract":"The International Journal of Advances in Soft Computing and its Applications (IJASCA) is a rapidly growing academic journal published by Al-Zaythoonah University of Jordan (ZUJ). IJASCA publishes original contributions on soft computing, machine learning and artificial intelligence, cloud computing, big data and other current science and technological trends. This study uses different bibliometric analysis tools to analyze the IJASCA published research papers between 2009 and 2021. The analysis includes annual publication growth, citation patterns, most prolific authors, institutions and countries, co-citation and co-occurrence networks analysis. A total of 317 published papers have been studied. The results show that IJASCA has grown in research contributions from 12 papers in 2009 to 40 papers in 2021, and citations have grown drastically to 2253. Universiti Teknologi Malaysia, Johor, is the institution that contributed the most to IJASCA publications with 109 papers. Malaysia is the country that was cited the most with 794 citations. Thematic analysis shows that the most important author keywords are soft computing, optimization, machine learning, big data and cloud computing. Overall, the findings are beneficial to the IJASCA editorial board. Its retrospective review will most likely encourage journal readers and assist the editorial team in developing research strategies that will allow research scientists to contribute high-quality research papers to the IJASCA. Keywords: IJASCA, Bibliometric analysis, co-citation analysis, co-occurrence analysis, thematic analysis, Scopus","PeriodicalId":38638,"journal":{"name":"International Journal of Advances in Soft Computing and its Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48277374","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

Candlestick Pattern Classification Using Feedforward Neural Network 基于前馈神经网络的蜡烛图案分类

International Journal of Advances in Soft Computing and its Applications Pub Date : 2022-07-20 DOI: 10.15849/ijasca.220720.06

Meilona Karmelia, Moeljono Widjaja, S. Hansun

{"title":"Candlestick Pattern Classification Using Feedforward Neural Network","authors":"Meilona Karmelia, Moeljono Widjaja, S. Hansun","doi":"10.15849/ijasca.220720.06","DOIUrl":"https://doi.org/10.15849/ijasca.220720.06","url":null,"abstract":"Investment in the capital market can help boost a country’s economic growth. Without a doubt, in investing, a technical analysis of the condition of the stock is needed at that time. One of the technical analyses that can be done is to look at the historical data of stocks. Candlestick charts can summarize historical data that contain price value for Open, High, Low, and Close (OHLC) in the form of a chart. A group of candlesticks will form a pattern that can help investors to see whether the stock is trending up or down. The number of candlestick patterns and the manual determination of candlestick patterns may take time and effort. Feedforward Neural Network (FNN) is one of the algorithms that can help map the input and output of a given dataset. This study aims to implement FNN to classify candlestick patterns found in historical stock data. The test results show that the accuracy for each model scenario does not guarantee whether all patterns can be properly recognized. This is mainly caused by an imbalanced dataset and the classification process cannot be done properly. Testing with the original data has an accuracy of above 85% on each stock, but the average F1-score is below 45%. Further experiments using random under-sampling and Synthetic Minority Oversampling Technique (SMOTE) result in decreased accuracy value, where the lowest is 59% in PT Bukit Asam Tbk share, and an increased average F1-score, but less than 15%. Keywords: Candlestick patterns, feedforward neural network, investment, historical data, OHLC, SMOTE, stocks.","PeriodicalId":38638,"journal":{"name":"International Journal of Advances in Soft Computing and its Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45271094","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

Financial Technology as a Basis for Financial Inclusion and its Impact on Profitability: Evidence from Commercial Banks 金融科技作为普惠金融的基础及其对盈利能力的影响:来自商业银行的证据

International Journal of Advances in Soft Computing and its Applications Pub Date : 2022-07-20 DOI: 10.15849/ijasca.220720.09

A. Alshehadeh, Haneen A. Al-Khawaja

{"title":"Financial Technology as a Basis for Financial Inclusion and its Impact on Profitability: Evidence from Commercial Banks","authors":"A. Alshehadeh, Haneen A. Al-Khawaja","doi":"10.15849/ijasca.220720.09","DOIUrl":"https://doi.org/10.15849/ijasca.220720.09","url":null,"abstract":"The purpose of this study was to show how financial technology tools can be used to reinforce financial inclusion indicators on the profitability indicators of a Jordanian commercial bank listed on the Amman stock exchange. Between 2010 and 2020, a quantitative and qualitative panel data set was used. The study population is represented by all the banks listed on the Amman stock exchange (n = 16). The study found that financial technology through its multitools changed the structure of the overall financial services, besides the diversity and style of financial services for the commercial banks' clients, thus reinforcing and increasing the availability for a wider social group that did not have access to that service. Further, it was found that there is a significant effect of the financial technology tools to reinforce the financial inclusion indicators over the studies' profitability indicators that include return on assets, return on equity, and earnings per share (JD). It is recommended to adopt effective and modern financial and technological strategies that provide marginalized social groups and small and medium enterprises reasonable access to the financial services and products that meet their needs, including transactions, payments, savings, credit, and insurance. Thus, getting the added value of the data and investing it to increase the financial inclusion indicators improves the profitability indicators and income for commercial banks. Keywords: Financial Technology, Profitability, Financial Inclusion, Commercial Banks.","PeriodicalId":38638,"journal":{"name":"International Journal of Advances in Soft Computing and its Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44166643","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: 7

Novel Approach for Augmented Reality using Convolutional Neural Networks 基于卷积神经网络的增强现实新方法

International Journal of Advances in Soft Computing and its Applications Pub Date : 2022-07-20 DOI: 10.15849/ijasca.220720.05

Zainab Oufqir, A. El Abderrahmani, K. Satori

{"title":"Novel Approach for Augmented Reality using Convolutional Neural Networks","authors":"Zainab Oufqir, A. El Abderrahmani, K. Satori","doi":"10.15849/ijasca.220720.05","DOIUrl":"https://doi.org/10.15849/ijasca.220720.05","url":null,"abstract":"In this paper, we will exploit the potential of convolutional neural networks (CNN) in augmented reality. Our work combines existing approaches and produces a new method for aligning a virtual object in the real world and in real time. Our method consists in detecting 2D objects of one or more classes present in the real world with CNN algorithms, then using the output of the network to calculate the position of the camera with the PnP algorithm in order to augment the detected object with additional information. The lightness of the MobileNet convolutional neural network combined with the speed of the Single Shot multibox Detector (SSD) framework allows to analyze the acquired images in real time and to use devices with limited resources and performance. We use a trained model that detects 20 different classes, the network receives as input an image sequence acquired in real time. The output of the network provides the set of detected classes as well as the coordinates of the corners of the surrounded rectangle on the object of this class. The coplanar coordinates of this rectangle are used to calculate the camera position and to align a 3D virtual object in the middle of the bounding box surrounding the detected object. The results obtained in the experimental part show the importance and the robustness of the method. Keywords: augmented reality; camera pose estimation; convolution neural network; MobileNet-SSD","PeriodicalId":38638,"journal":{"name":"International Journal of Advances in Soft Computing and its Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47766431","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: 0

PDIS: A Service Layer for Privacy and Detecting Intrusions in Cloud Computing PDIS:一种用于云计算中隐私和入侵检测的服务层

International Journal of Advances in Soft Computing and its Applications Pub Date : 2022-07-20 DOI: 10.15849/ijasca.220720.02

Rusul Mumtaz, V. Samawi, Aysh Alhroob, Wael Alzyadat, I. Almukahel

{"title":"PDIS: A Service Layer for Privacy and Detecting Intrusions in Cloud Computing","authors":"Rusul Mumtaz, V. Samawi, Aysh Alhroob, Wael Alzyadat, I. Almukahel","doi":"10.15849/ijasca.220720.02","DOIUrl":"https://doi.org/10.15849/ijasca.220720.02","url":null,"abstract":"Cloud computing faces numerous challenges in many areas including security and privacy issues. In this work, a developed approach is suggested to tackle three security and privacy issues: network intrusion detection (NID), privacy, and internal attacks. A decision tree (J48) has been used to generate a set of rules based on the CICIDS2017 dataset to solve the NID problem. The accuracy of the generated rules approaches 99.8%. A set of policies are attached to the data file on the bases of a sticky policy to preserve privacy. A new approach is suggested based on blockchain to detect internal attacks in real-time, in which a set of trustees-chain are identified by the data owner. Any data modification conducted by a trusted member will be reported to all members of the trust group including the owner. The developed approach suggests adding a Privacy and Detecting Intrusions Service (PDIS) layer as part of the cloud computing main service model. PDIS includes the three suggested approaches above (NID, sticky policy, and trustees-chain). Finally, a web-based application is implemented to act as casework to validate PDIS and evaluate its reliability. Keywords: Cloud computing, Privacy, Machine learning, Internal Intrusion Detection, Network Intrusion Detection, Real Time Auditing","PeriodicalId":38638,"journal":{"name":"International Journal of Advances in Soft Computing and its Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48153057","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

Applications of Conformable Fractional Pareto Probability Distribution 符合分数帕累托概率分布的应用

International Journal of Advances in Soft Computing and its Applications Pub Date : 2022-07-20 DOI: 10.15849/ijasca.220720.08

Duha Abu Judeh

引用次数: 7

Image SPAM Detection Using ML and DL Techniques 使用ML和DL技术的图像垃圾检测

International Journal of Advances in Soft Computing and its Applications Pub Date : 2022-03-28 DOI: 10.15849/ijasca.220328.15

Nawal Abuzaid

引用次数: 2

Efficient Task Scheduling of Virtual Machines using Novel Spectral Partitioning and Differential Evaluation Algorithm 基于谱划分和差分评估算法的虚拟机高效任务调度

International Journal of Advances in Soft Computing and its Applications Pub Date : 2022-03-28 DOI: 10.15849/ijasca.220328.11

Anwar Shaheen, Sundar Kumar

{"title":"Efficient Task Scheduling of Virtual Machines using Novel Spectral Partitioning and Differential Evaluation Algorithm","authors":"Anwar Shaheen, Sundar Kumar","doi":"10.15849/ijasca.220328.11","DOIUrl":"https://doi.org/10.15849/ijasca.220328.11","url":null,"abstract":"Abstract Task-scheduling is a major challenge in cloud computing environment that degrades the performance of the system. To enhance the performance of the system, an effective task-scheduling algorithm is needed. Hence an effective task-partitioning and taskscheduling algorithm is introduced for enhancing the system performance. To create resources (datacentre, broker, Virtual Machine - VM and cloudlet) in a dynamic way through the use of CloudSim. In addition, this study intended to perform taskpartitioning and task-scheduling in an effective manner by utilizing the novel spectral partitioning - (SP) and differential evaluation algorithm - (DEA). At first, the task and datacentre is initialized. Subsequently, task-partitioning is performed using the novel SP. It includes a series of steps in which a Laplacian matrix is computed initially. Then based on the Eigen-values and Eigen-vectors of the Laplacian matrix the tasks are partitioned. Followed by this, taskscheduling is performed with the employment of proposed novel DEA. The process comprise the following series of steps such as threshold calculation, mutation, crossover, selection and knee solution for achieving efficient task-partitioning and scheduling. The performance of the proposed system is evaluated by comparing it with other traditional methods. And validated in terms of service cost, load balancing, makespan and energy consumption. The results proved the efficacy of the introduced system. The overall results obtained from comparative analysis also reveal that proposed method outperformed other traditional techniques thereby accomplishing effective task scheduling of VMs in cloud computing environment. Keywords: Cloud computing environment, Virtual Machines, Task Scheduling, Novel Spectral Partitioning and Differential Evaluation Algorithm.","PeriodicalId":38638,"journal":{"name":"International Journal of Advances in Soft Computing and its Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47216284","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: 0