VFAST Transactions on Software Engineering最新文献

Identifying Key Learning Algorithm Parameter of Forward Feature Selection to Integrate with Ensemble Learning for Customer Churn Prediction 识别前向特征选择的关键学习算法参数，与客户流失预测的集合学习相结合

VFAST Transactions on Software Engineering Pub Date : 2024-06-11 DOI: 10.21015/vtse.v12i2.1811

Sabahat Tasneem, Muhammad Younas, Qasim Shafiq

{"title":"Identifying Key Learning Algorithm Parameter of Forward Feature Selection to Integrate with Ensemble Learning for Customer Churn Prediction","authors":"Sabahat Tasneem, Muhammad Younas, Qasim Shafiq","doi":"10.21015/vtse.v12i2.1811","DOIUrl":"https://doi.org/10.21015/vtse.v12i2.1811","url":null,"abstract":"The Telecommunication has been facing fierce growth of customer data and competition in the market for a couple of decades. Due to this situation, an analytical strategy of proactive anticipation about customer churn and their profitable retention is inevitable for Telecommunication companies. To nip this problem in the bud, a lot of research work has been conducted in the past, but still the previously introduced churn prediction models possess their own limitations, such as high dimensional data with poor information and class imbalance, which turn into barriers while being implicated in real life to attain accurate and improved predictions. This study has been conducted, basically, to identify the key Learning Algorithm parameter of Forward Feature Selection (FFS) for dimensionality reduction which can be further integrated with class Imbalance Handling Technique and Ensemble Learning (EL) to attain improved accuracy. The core objective of this study is to turn an imbalanced dataset into a balanced one for Ensemble Learning (EL) Model of Customer Churn Prediction (CCP). This study concluded that Logistic Regression (LR) based Forward Feature Selection (FFS) can outperform with Oversampling Class Imbalance Handling Techniques and Ensemble Learning (EL) by scoring 0.96% accuracy, which is the highest accuracy against benchmark studies. The resulting methodology has been named as the Logistic Regression Learning based Forward Feature Selection for ensemble Learning (LRLFFSEL) and applied over Orange dataset with 20 features and 3333 instances. In future this methodology can be evaluated over a bigger dataset and combined with some data optimization techniques to improve its accuracy.","PeriodicalId":173416,"journal":{"name":"VFAST Transactions on Software Engineering","volume":"14 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141359334","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 Mobility Prediction Based Adaptive Task Migration in Mobile Edge Computing 移动边缘计算中基于移动性预测的自适应任务迁移

VFAST Transactions on Software Engineering Pub Date : 2024-06-03 DOI: 10.21015/vtse.v12i2.1768

Jawad Usman Arshed, Mehtab Afzal, Muhammad Hashim Ali Abbasi, Imtiaz Ahmad, Hasnat Ali, Ghulam Hussain

{"title":"A Mobility Prediction Based Adaptive Task Migration in Mobile Edge Computing","authors":"Jawad Usman Arshed, Mehtab Afzal, Muhammad Hashim Ali Abbasi, Imtiaz Ahmad, Hasnat Ali, Ghulam Hussain","doi":"10.21015/vtse.v12i2.1768","DOIUrl":"https://doi.org/10.21015/vtse.v12i2.1768","url":null,"abstract":"During the past few years, mobile data traffic has exponentially increased due to emerging applications, such as social media, online gaming, and augmented/virtual reality. Although the capabilities of mobile devices are significantly improved, they are unable to execute computationally intensive tasks. To extend the computing capabilities of resource-constrained mobile devices, computation offloading is performed on edge servers. Due to user mobility, offloaded tasks often need to be migrated from one edge server to another. Mobility-aware task migration faces different challenges due to varying mobility characteristics of end-users. These challenges include latency, server utilization, and energy consumption. Existing techniques of task and machine (VM) migration do not consider the user movement trajectories while making migration decisions. Consequently, the task or VM is migrated to the edge server that may be far away from the mobile users' location that increases the response time. In this paper we proposed Mobility Migration Algorithm based on Linear Regression (MALR). After outsourcing the task, a recurrent neural network (RNN) and linear regression are used to forecast the user's present location. Using the distance between the user and the server, it gets a list of nearby servers, and then moves the task there. The proposed approach eliminates the job migration time with improvement in forecast accuracy as compared to the logistic regression and K-mean.","PeriodicalId":173416,"journal":{"name":"VFAST Transactions on Software Engineering","volume":"67 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141388833","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

Exploring Long-Range Order in Diblock Copolymers through Cell Dynamic Simulations 通过细胞动态模拟探索二嵌段共聚物的长程有序性

VFAST Transactions on Software Engineering Pub Date : 2024-06-02 DOI: 10.21015/vtse.v12i2.1795

Muhammad Javed Iqbal, Inayatullah Soomro, Mumtaz Hussain Mahar, Usama Gulzar

{"title":"Exploring Long-Range Order in Diblock Copolymers through Cell Dynamic Simulations","authors":"Muhammad Javed Iqbal, Inayatullah Soomro, Mumtaz Hussain Mahar, Usama Gulzar","doi":"10.21015/vtse.v12i2.1795","DOIUrl":"https://doi.org/10.21015/vtse.v12i2.1795","url":null,"abstract":"Soft materials have played an important role in the development of nanotechnology over the past decade. Diblock copolymer systems in these soft materials have opened up new avenues of research, introducing discoveries in experimental and theoretical research in the bulk and melt states. To this end, computer programming has advanced the simulation of soft materials through mathematical models that have enabled the prediction of novel ordered structures and morphologies from simulations on long-range order. Using this approach proved to be cost-effective and time-efficient. There are many mathematical models for predicting novel morphologies in diblock copolymer systems by computer simulation. Still, cell dynamic simulation (CDS) stands out for its efficiency and robustness in achieving long-range order. This paper presents a cell dynamic simulation model for predicting simulation results by examining flow, deformation and phase transitions within diblock copolymer systems in curvilinear coordinate systems. The paper insight into the interpretation, understanding, scope, and application of the partial differential equations involved in the model by presenting a block diagram of the CDS model with a modified algorithm. A numerically consistent CDS numerical scheme is developed. Laplacian is involved in the CDS model based on curvilinear geometries to solve regular and irregular system boundaries. Also, self-assembly, phase separation mechanism, predicted results and applications in diblock copolymer systems are highlighted. Finally, the results of the CDS model are also presented for comparison with other models.","PeriodicalId":173416,"journal":{"name":"VFAST Transactions on Software Engineering","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141388926","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

FlightForecast: A Comparative Analysis of Stack LSTM and Vanilla LSTM Models for Flight Prediction FlightForecast：用于飞行预测的 Stack LSTM 和 Vanilla LSTM 模型的比较分析

VFAST Transactions on Software Engineering Pub Date : 2024-03-08 DOI: 10.21015/vtse.v12i1.1740

Rohail Qamar, Raheela Asif, Laviza Falak Naz, Adeel Mannan, Afzal Hussain

引用次数: 0

A Study of Brain Tumor detection using MRI images 利用磁共振成像检测脑肿瘤的研究

VFAST Transactions on Software Engineering Pub Date : 2024-02-19 DOI: 10.21015/vtse.v12i1.1698

Asadullah Kehar, Mashooque Ali Mahar, Shahid Hussain Danwer, Sidra Parveen, Mariya Bhutto, Zoya Qutrio

引用次数: 0

A Modern Approaches for Modeling Time-Varying Database Models 时变数据库模型建模的一种现代方法

VFAST Transactions on Software Engineering Pub Date : 2019-04-08 DOI: 10.21015/VTSE.V14I2.552

Nashwan Alromema, F. Alotaibi

引用次数: 0

An Image-Based Multimedia Database and Efficient Detection though Features 基于图像的多媒体数据库及特征高效检测

VFAST Transactions on Software Engineering Pub Date : 2018-11-24 DOI: 10.21015/VTSE.V14I1.536

Khurram Ejaz, M. Rahim, A. Rehman, Farhan Ejaz

引用次数: 5

Design and Development of Secure Mobile Communication over GSM Network Using Open Source Operating System (OS) 基于开源操作系统的GSM网络安全移动通信设计与开发

VFAST Transactions on Software Engineering Pub Date : 2018-11-24 DOI: 10.21015/VTSE.V14I1.535

Arslan Asim, M. Ashraf

{"title":"Design and Development of Secure Mobile Communication over GSM Network Using Open Source Operating System (OS)","authors":"Arslan Asim, M. Ashraf","doi":"10.21015/VTSE.V14I1.535","DOIUrl":"https://doi.org/10.21015/VTSE.V14I1.535","url":null,"abstract":"With the rapidly advancing technology of today, exchange of information and data is a very pertinent matter. The world has just recently witnessed the effects of information leakage through the issue of WikiLeaks. There are huge amounts of data being shared over different platforms nowadays. Global System for Mobile Communication (GSM) is one of the most reliable platforms known to and used by almost all people in the world for text as well as voice communication. With the tools like Android Studio and NetBeans available, it is now possible to encrypt the text that has to be sent over the GSM, so that it can be decrypted at the other end of the communication path. However, the encryption and decryption of voice being transmitted over the GSM network still remains a question. In the domain of real time voice encryption, much of the work being carried out pertains to the voice being exchanged through the Internet Protocol. As compared to the Voice over Internet Protocol (VoIP), voice over the GSM network has not seen much research work related to its security aspects. The purpose of this paper is to document the results of a project aimed at developing a platform for mobile phones in order to communicate over the GSM network in a secure manner. The most suitable method for achieving the above mentioned objective is to use an open source Operating System (OS), so that the source code is easily accessible and usable. In this paper, the Android OS will be under discussion, which is compatible with all the Android mobile phones. In this way, the maximum number of mobile phone users can be benefitted because Android cell phones are being widely used nowadays. The use of cryptographic algorithms for securing the voice communication over the GSM network is also a part of this paper. The work revolves around the Java programming language since the Android application development has been carried out in Java through the use of Android Studio. Also, NetBeans has been employed for developing algorithms for voice encryption","PeriodicalId":173416,"journal":{"name":"VFAST Transactions on Software Engineering","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120956988","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

Extracting True Number of Clusters for Segmenting Image through Adaptive Finite Gaussian Mixture Model 基于自适应有限高斯混合模型的图像分割真簇数提取

VFAST Transactions on Software Engineering Pub Date : 2018-11-24 DOI: 10.21015/VTSE.V14I1.540

M. M. Ahmad, Sajid Naeem, Syed Muhammad Rehman Habib

{"title":"Extracting True Number of Clusters for Segmenting Image through Adaptive Finite Gaussian Mixture Model","authors":"M. M. Ahmad, Sajid Naeem, Syed Muhammad Rehman Habib","doi":"10.21015/VTSE.V14I1.540","DOIUrl":"https://doi.org/10.21015/VTSE.V14I1.540","url":null,"abstract":"Knowing exact number of clusters in a digital image significantly facilitates in precisely clustering an image. This paper proposes a new technique for extracting exact number of clusters from grey scale images. It analyzes the contents of the input image and adaptively reserves one distinct cluster for one distinct grey value. The total count of the grey values found in an image determines the exact number of clusters. Based on the contents of image, this number of clusters keeps on changing from image to image. After obtaining this number, it is given as an input to Gaussian Mixture Model (GMM) which clusters the image.GMM works with finite number of clusters and forms mixture of various spectral densities contained in that image. The proposed method facilitates GMM to adapt itself according to the changing number of clusters. Therefore, the proposed model along with the inclusion of GMM, is named as Adaptive Finite Gaussian Mixture Model (AFGMM). The clustering performance of AFGMM is evaluated through Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR). Both of these performance measuring methods confirmed that exact number of clusters is essentially important for reliably analyzing an image.","PeriodicalId":173416,"journal":{"name":"VFAST Transactions on Software Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129921874","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

Career and Skills Recommendations using Data Mining Technique: Matching Right People for Right Profession, in Pakistani Context 使用数据挖掘技术的职业和技能建议:在巴基斯坦背景下为合适的职业匹配合适的人

VFAST Transactions on Software Engineering Pub Date : 2018-11-01 DOI: 10.21015/VTSE.V13I3.510

M. Kiran, Hira Asim, Malik Tahir Hassan

{"title":"Career and Skills Recommendations using Data Mining Technique: Matching Right People for Right Profession, in Pakistani Context","authors":"M. Kiran, Hira Asim, Malik Tahir Hassan","doi":"10.21015/VTSE.V13I3.510","DOIUrl":"https://doi.org/10.21015/VTSE.V13I3.510","url":null,"abstract":"There are a number of recommendation systems available on the internet for the help of jobseekers. These systems only generate job recommendations for people on the basis of input entered by user. The problem observed in Pakistani people is they are not clear in which field they should start or switch working. Before searching and applying for a job, one should be clear about his/her profession and important skills regarding selected profession. Based on above issues, there is a need to design such a system that can overcome the problem of profession selection and skills suggestions so that it can be easy for a jobseeker to apply for a specific job. In this research, the problem which is discussed above is resolved by proposing a model by using Association Rules Mining, a data mining technique. In this model, professions are recommended to job seekers by matching the profile of applicant or job seeker with those persons who have same profile like educational background, professional skills and the type of jobs which they are doing. The data collected for this research itself is a major contribution as we collected it from different sources. We will make this data publically available for others so that they can use for further research.","PeriodicalId":173416,"journal":{"name":"VFAST Transactions on Software Engineering","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124077324","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