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A Study on Autonomous Driving Simulation Using a Deep Learning Process Model 基于深度学习过程模型的自动驾驶仿真研究
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.293264
Symphorien Karl Yoki Donzia, Haeng-Kon Kim
{"title":"A Study on Autonomous Driving Simulation Using a Deep Learning Process Model","authors":"Symphorien Karl Yoki Donzia, Haeng-Kon Kim","doi":"10.4018/ijsi.293264","DOIUrl":"https://doi.org/10.4018/ijsi.293264","url":null,"abstract":"Along with artificial intelligence technologies, deep learning technology, which has recently received a great deal of attention, has been studied on the basis of developed artificial neural networks. This thesis deals with the detection, recognition, judgment, and control that are included in the basic technologies of the autonomous driving subsystems to achieve fully autonomous driving. And this work solves many problems in this area. The use of the CARLA simulation in this project is the development of a deep learning intelligent autonomous driving system in the road environment. Autonomous driving recognizes the situation by processing the data collected through images from multiple sensors or lidars and cameras in real-time. In the cloud server process using real data, explore various deep learning models for traffic flow prediction, return the model trained onboard, perform the prediction and solve the problem of fully autonomous driving, including a module of control, which is a CARLA simulation.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130896179","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
Adaptive Threshold and Directional Weighted Median Filter-Based Impulse Noise Removal Method for Images 基于自适应阈值和方向加权中值滤波的图像脉冲噪声去除方法
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.297983
Ashpreet, M. Biswas
{"title":"Adaptive Threshold and Directional Weighted Median Filter-Based Impulse Noise Removal Method for Images","authors":"Ashpreet, M. Biswas","doi":"10.4018/ijsi.297983","DOIUrl":"https://doi.org/10.4018/ijsi.297983","url":null,"abstract":"Elimination of impulse noise in image snap shots with side renovation is one of the complex duties in digital image processing. In this paper, the removal of random impulse noise is done in two important levels. In first level, the detection of the impulse noise is done on the premise of a double threshold selecting strategy after which in the another level, elimination of impulse noise is done by the usage of median filter and directional weighted median filter relying upon the noise map (Nmap) construction of corrupted pixels detected within the first level. The proposed method makes use of the statistical characteristics of noisy image graphs and the brink obtained is adaptable to one of a kind of snap shots and noise conditions. Comparative evaluation with different widespread de-noising techniques shows that the proposed method outperforms in terms of PSNR, SSIM, NMSE and Computation Time (CT) of the distinct trying out test images, with exclusive noise levels.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134238027","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
Clustering of Template-Generated Webpages Using DOM Tree Paths of URLs 使用url的DOM树路径聚类模板生成的网页
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.297994
T. I. Bagban, P. Kulkarni
{"title":"Clustering of Template-Generated Webpages Using DOM Tree Paths of URLs","authors":"T. I. Bagban, P. Kulkarni","doi":"10.4018/ijsi.297994","DOIUrl":"https://doi.org/10.4018/ijsi.297994","url":null,"abstract":"Web templates are layouts for webpages that enable rapid and easy access to web content. Web data integration solutions use template based wrapper tools to extract product information from e-commerce websites. Given a collection of webpages, wrapper tools are used to discover the template portion of a webpage and extract data from it. These wrapper based data extraction techniques require pages created with the same template belong to the same cluster. Clustering these webpages based on their template is a significant challenge. While there are algorithms for clustering webpages based on their template, they are computationally intensive to be applied at web scale. By examining the DOM tree paths of URLs on a webpage, the proposed work presents a highly scalable methodology for clustering template-generated webpages. Further, the locality sensitive hashing (LSH) technique is used to reduce the cost of clustering. The proposed technique is found to be more precise and cost effective than the existing baseline methods when tested on three separate real-time data sets.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130985280","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
Stereo Seam Coupling and Depth Distortion Score in 3D Image Retargeting Using DMA Algorithm 基于DMA算法的三维图像重定位中的立体接缝耦合和深度失真评分
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.297506
M. Jagtap, Dineshkumar Jawalkar
{"title":"Stereo Seam Coupling and Depth Distortion Score in 3D Image Retargeting Using DMA Algorithm","authors":"M. Jagtap, Dineshkumar Jawalkar","doi":"10.4018/ijsi.297506","DOIUrl":"https://doi.org/10.4018/ijsi.297506","url":null,"abstract":"Preserving the highlighted contents in left and right stereo images by using seam carving technique is the challenging job in current digital era. The seam carving technique facilitates to minimise the trouble by eliminating unwanted seam patches from the stereo images by using saliency detection method. These images are popularly known as stereoscopic images. This paper addresses the issues in 2-D planer images and emphasised on 3-D stereoscopic images. We method enforces on the foreground pixels which are highly considerable by calculating the high energy pixels. The depth distortion estimation is performed by adjusting the aspect ratio. The viewpoints of left and right stereo images are somewhat different. Disparity Map Acquisition (DMA) algorithm maps the pixel points from the left stereo image to its corresponding right image pixels. The fusion of the left and right images is incorporating to minimise the depth distortion score.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128415891","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
Class Imbalance Learning to Heterogeneous Cross-Software Projects Defect Prediction 类不平衡学习在异构跨软件项目缺陷预测中的应用
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.292021
Rohit Vashisht, S. Rizvi
{"title":"Class Imbalance Learning to Heterogeneous Cross-Software Projects Defect Prediction","authors":"Rohit Vashisht, S. Rizvi","doi":"10.4018/ijsi.292021","DOIUrl":"https://doi.org/10.4018/ijsi.292021","url":null,"abstract":"Heterogeneous CPDP (HCPDP) attempts to forecast defects in a software application having insufficient previous defect data. Nonetheless, with a Class Imbalance Problem (CIP) perspective, one should have a clear view of data distribution in the training dataset otherwise the trained model would lead to biased classification results. Class Imbalance Learning (CIL) is the method of achieving an equilibrium ratio between two classes in imbalanced datasets. There are a range of effective solutions to manage CIP such as resampling techniques like Over-Sampling (OS) & Under-Sampling (US) methods. The proposed research work employs Synthetic Minority Oversampling TEchnique (SMOTE) and Random Under Sampling (RUS) technique to handle CIP. In addition to this, the paper proposes a novel four-phase HCPDP model and contrasts the efficiency of basic HCPDP model with CIP and after handling CIP using SMOTE & RUS with three prediction pairs. Results show that training performance with SMOTE is substantially improved but RUS displays variations in relation to HCPDP for all three prediction pairs.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133921145","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
A 3D Chaotic Dynamics-Assisted Color Image Authentication Technique in Multicore Milieu: Multicore Implementation of 3D RGB Steganography 多核环境下三维混沌动态辅助彩色图像认证技术:三维RGB隐写的多核实现
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.303581
Gaurav Gambhir, Monika Gambhir, J. K. Mandal
{"title":"A 3D Chaotic Dynamics-Assisted Color Image Authentication Technique in Multicore Milieu: Multicore Implementation of 3D RGB Steganography","authors":"Gaurav Gambhir, Monika Gambhir, J. K. Mandal","doi":"10.4018/ijsi.303581","DOIUrl":"https://doi.org/10.4018/ijsi.303581","url":null,"abstract":"The paper presents a novel, 3D Chaotic Dynamics assisted secured and imperceptible, LSB steganography technique for hiding secret information, into the RGB color components of a cover image. Random numbers generated with three dimensional chaotic function assist in embedding and extracting the secret data in the payload, enhancing the transmission security. The quality of the pseudorandom number sequences has been tested with the standard NIST test suite as a pre-embedding operation. The proposed steganography technique is highly secure, robust and fast in execution as it utilizes multicore processors available today with most of the desktop and laptop computers. Statistical analysis of the technique validates the security and robustness while scalability and speed-up analysis validate the efficiency of the proposed parallel steganography technique. Significant performance has been observed even when a large amount of data is processed.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116593102","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
Depression Detection Model in Social Network Content: A Survey 社交网络内容中的抑郁检测模型研究
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.309112
E. M. Rabie, Atef F. Hashem, Fahad Kamal Alsheref
{"title":"Depression Detection Model in Social Network Content: A Survey","authors":"E. M. Rabie, Atef F. Hashem, Fahad Kamal Alsheref","doi":"10.4018/ijsi.309112","DOIUrl":"https://doi.org/10.4018/ijsi.309112","url":null,"abstract":"Social media (SM) is a platform that generates a massive quantity of data every day and allows individuals to engage with one another. For many people, social media has evolved into a way of life and the fifth component of daily living. Among the most popular social media platforms are Facebook, Instagram, Twitter, WhatsApp, and Snapchat. Depression is a frequent and dangerous medical condition that has a negative impact on how you feel, think, and act. A therapist's ability to swiftly detect depression in persons is limited since they cannot observe a person's mood throughout the day. Researchers can assess a person's sentiments via social media by looking at the user's posts and comments to discover if he or she has a mental issue. This survey study mirrors prior research on detecting depression using user-generated material from social media platforms, which introduce different techniques and compare between it to obtain accuracy.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116660927","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
Androscanreg 2.0: Enhancement of Android Applications Analysis in a Flexible Blockchain Environment Androscanreg 2.0:在灵活的区块链环境中增强Android应用程序分析
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.309724
Abdellah Ouaguid, F. Fathi, Mouad Zouina, M. Ouzzif, N. Abghour
{"title":"Androscanreg 2.0: Enhancement of Android Applications Analysis in a Flexible Blockchain Environment","authors":"Abdellah Ouaguid, F. Fathi, Mouad Zouina, M. Ouzzif, N. Abghour","doi":"10.4018/ijsi.309724","DOIUrl":"https://doi.org/10.4018/ijsi.309724","url":null,"abstract":"In this article, the authors propose a new innovative method based on blockchain technology providing an analysis of Android applications in a decentralized, flexible, and reliable way. The proposed approach improves the typical operation of the blockchain technology that considers invalid (or “fraudulent”) any outcome different from other results found by the majority of network nodes. However, ignoring any result different from the majority without starting additional verification can cause losses in terms of data, time, computing power, or even system reliability and the integrity of its data. The purpose of the presented approach is to confirm or deny the legitimacy of any outcome different from the majority. This new concept will facilitate the detection of polymorphic programs by allowing nodes to adopt specific environments at any time to reduce the rejection of results deemed, wrongly, to be fraudulent. A proof of concept has been designed and implemented showing the feasibility of the proposed approach with a real case study.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"212 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121092346","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
A Hybrid System for Heart Disease Diagnosis Based on HPCBE Method 基于HPCBE方法的混合心脏病诊断系统
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.303582
P. Rani, Rajneesh Kumar, Anurag Jain
{"title":"A Hybrid System for Heart Disease Diagnosis Based on HPCBE Method","authors":"P. Rani, Rajneesh Kumar, Anurag Jain","doi":"10.4018/ijsi.303582","DOIUrl":"https://doi.org/10.4018/ijsi.303582","url":null,"abstract":"Heart disease is a type of chronic disease that can lead to death if not diagnosed in time. A clinical decision support system developed using machine learning technology can be used in the diagnosis of disease. Proper utilization of feature selection increases classification accuracy by reducing the computational cost. The purpose of this research work is to purpose a new Hybrid Pearson Correlation with Backward Elimination (HPCBE) feature selection method. Proposed HPCBE method is further used to develop a hybrid system for heart disease diagnosis (HSHDD).HPCBE is proposed by combining pearson correlation (PC) and backward elimination (BE) methods. Reduced feature subset selected by HPCBE method is used along with decision tree (DT), k-nearest neighbor (KNN), extreme gradient boosting (XGBoost) and adaptive boosting (AdaBoost) classifiers to develop HSHDD. The feature reduction ratio of 53.84% is achieved by the proposed HPCBE Feature Selection method. HSHDD achieved a maximum accuracy of 86.49% in heart disease classification with AdaBoost classifier.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115456546","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
A Performance Improvement Model for Cloud Computing Using Simulated Annealing Algorithm 基于模拟退火算法的云计算性能改进模型
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.301222
Geeta Singh, Santosh Kumar, S. Prakash
{"title":"A Performance Improvement Model for Cloud Computing Using Simulated Annealing Algorithm","authors":"Geeta Singh, Santosh Kumar, S. Prakash","doi":"10.4018/ijsi.301222","DOIUrl":"https://doi.org/10.4018/ijsi.301222","url":null,"abstract":"Cloud system has emerged as a fast computing technology wherein it delivers its services to users with minimum cost and time. The number of cloud users are also increasing too fast. With this increased number of users, there is a need of efficient algorithms which would be able to maximize the resource utilization, scheduling jobs in optimal manner leading to maximum profit and improved overall cloud performance. Research trends show that meta-heuristic optimization algorithms have been successfully applied to enhance the performance of cloud system. In this research, a simulated annealing based concept has been applied for job scheduling with the aim of minimizing the overall execution time of a job schedule selected from the job pool and balancing the loads in the available virtual machines. The algorithm has been simulated in CloudSim environment and it has been seen that it provides non-dominance optimal solution and is able to achieve reduced execution time of job schedule in comparison to other existing algorithms like FCFS, min-min algorithm and RR and Iterative Improvement.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131948220","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
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