发布求助
文献互助 智能选刊 最新文献

Computer Science & Engineering: An International Journal最新文献

筛选
英文 中文
Design of Security Taxonomy in Requirement Engineering 需求工程中安全分类的设计
Computer Science & Engineering: An International Journal Pub Date : 2022-02-28 DOI: 10.5121/cseij.2022.12106
T. Shah
{"title":"Design of Security Taxonomy in Requirement Engineering","authors":"T. Shah","doi":"10.5121/cseij.2022.12106","DOIUrl":"https://doi.org/10.5121/cseij.2022.12106","url":null,"abstract":"Non Functional Requirements (NFR) are important in all phases of software development and results in quality of software to be built. It is observed that security requirements are incorporated and identified later in the software development life cycle. Security as non functional requirements imposes new challenges in managing confidential data and preserving its integrity. The security requirements and related artefacts must be considered from Requirement Engineering (RE) phase to implementation phase. This paper focuses on new design of taxonomy of security in Requirement Engineering. The design covers the major properties of security which are required in developing any web based, secured, confidential and integrity oriented system.","PeriodicalId":361871,"journal":{"name":"Computer Science & Engineering: An International Journal","volume":"279 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132981064","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
Context aware Secure Collaborative Business Intelligence 上下文感知的安全协作商业智能
Computer Science & Engineering: An International Journal Pub Date : 2022-02-28 DOI: 10.5121/cseij.2022.12107
Veena N. Jokhakar
{"title":"Context aware Secure Collaborative Business Intelligence","authors":"Veena N. Jokhakar","doi":"10.5121/cseij.2022.12107","DOIUrl":"https://doi.org/10.5121/cseij.2022.12107","url":null,"abstract":"To enable efficient decision making, professionals need to collaborate with individuals with data being a collected from various sources like distributed clouds for storage, very large databases and social media with authentication and validation is needed for access to relevant roles. Further application of machine learning to deal with unlawful actions. This paper proposes a Context Aware Secure Collaborative Business Intelligence Framework (CASCBF) to address the same. CASCBF is divided into three layers. Multiple sources of data provide different levels of abstraction and granularity of access control to different roles. To control different types of assemblage of data resources from distributed sources and provide right access to users to the edge of the network is a core challenge.","PeriodicalId":361871,"journal":{"name":"Computer Science & Engineering: An International Journal","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116427063","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
Context aware Secure Collaborative Business Intelligence 上下文感知的安全协作商业智能
Computer Science & Engineering: An International Journal Pub Date : 2022-02-28 DOI: 10.5121/cseij.2022.12108
Sk Ibrar Ahmed, Quazi Mohmmad Alfred
{"title":"Context aware Secure Collaborative Business Intelligence","authors":"Sk Ibrar Ahmed, Quazi Mohmmad Alfred","doi":"10.5121/cseij.2022.12108","DOIUrl":"https://doi.org/10.5121/cseij.2022.12108","url":null,"abstract":"India can face an shortage of potable and fresh water in the near future. Coherent, efficient, and low-cost methods to monitor water usage are crucial to prevent this alarming issue. Measurement of water usage accompanied with monitoring the purity of water can result in saving of water.In this paper an IoT based complete water flow monitoring system with some added features (Internet of Things) is proposed here. The entire setup is developed using Wi-Fi enabled microcontroller which consists of various sensors and actuators e.g hall effect sensor, pH. sensor, TDS sensor, solenoid valve, etc.Hall effect sensor is mainly used to measure the water flow whereas pH and the TDS sensors are used to measure the purity of water. The solenoid valve is used to control the water supply. To meet the need for fresh and drinkable water a novelsolution is proposed in this paper which is based upon cloud based IoT (Internet of Things)network.","PeriodicalId":361871,"journal":{"name":"Computer Science & Engineering: An International Journal","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131587428","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 Recurrent Neural Model for Temporal Information Extraction 时间信息提取的递归神经模型
Computer Science & Engineering: An International Journal Pub Date : 2022-02-28 DOI: 10.5121/cseij.2022.12103
Parul Patel
{"title":"A Recurrent Neural Model for Temporal Information Extraction","authors":"Parul Patel","doi":"10.5121/cseij.2022.12103","DOIUrl":"https://doi.org/10.5121/cseij.2022.12103","url":null,"abstract":"Temporal information extraction is an emerging area of information retrieval. Understanding temporal nature of a document is very important in application like answering time sensitive queries, doing temporal analysis of a document, document clustering etc. Lot of research is done in temporal reasoning using rule based or machine learning based approaches. In this paper, deep learning is used to extract temporal expressions from the text documents. Bi-directional Long Short term Memory Recurrent Neural Network (Bi-LSTM RNN) is used to extract temporal expression from the text. Gold standard datasets are used for training and evaluation. Performance of the proposed system is compared with existing system.","PeriodicalId":361871,"journal":{"name":"Computer Science & Engineering: An International Journal","volume":"35 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125548761","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
Early Detection of Breast Cancer Tumors using Linear Discriminant Analysis Feature Selection with Different Machine Learning Classification Methods 基于线性判别分析的乳腺癌肿瘤早期检测与不同机器学习分类方法的特征选择
Computer Science & Engineering: An International Journal Pub Date : 2022-02-28 DOI: 10.5121/cseij.2022.12117
M. Abbas, Hamid Ghous
{"title":"Early Detection of Breast Cancer Tumors using Linear Discriminant Analysis Feature Selection with Different Machine Learning Classification Methods","authors":"M. Abbas, Hamid Ghous","doi":"10.5121/cseij.2022.12117","DOIUrl":"https://doi.org/10.5121/cseij.2022.12117","url":null,"abstract":"Globally, the frequency of breast cancer and its morality speak to a critical and developing risk for the developing countries. In Asia, Pakistan has the biggest rate of breast cancer. It is evaluated that every year 83,000 cases were reported in Pakistan and over 40,000 deaths are caused by breast cancer. Patients suffering from this malignancy have a better chance of surviving if they are diagnosed early. Many Early identification of breast cancer can be achieved using data mining techniques, allowing preventative treatments to be done. In this research Wisconsin Breast Cancer Dataset (WBCD) and Duke Breast cancer dataset (DBDS) are used with Linear Discriminant Analysis (LDA) feature selection with Support Vector Machine (SVM), Decision Tree (DT), Neural Network and Random Forest (RF) machine learning classifiers to predict breast cancer tumors. The finding of the proposed model is that feature selections through LDA improve the accuracy of detecting tumors and also reduce time duration of executing model. The best machine learning model with LDA feature selection is Neural Network Model with highest accuracy 1.00 among all classification models and also consume less time.","PeriodicalId":361871,"journal":{"name":"Computer Science & Engineering: An International Journal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125794502","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
Resume Screening and Recommendation System using Machine Learning Approaches 使用机器学习方法的简历筛选和推荐系统
Computer Science & Engineering: An International Journal Pub Date : 2022-02-28 DOI: 10.5121/cseij.2022.12101
Lokesh. S, Mano Balaje. S, Prathish. E, B. Bharathi
{"title":"Resume Screening and Recommendation System using Machine Learning Approaches","authors":"Lokesh. S, Mano Balaje. S, Prathish. E, B. Bharathi","doi":"10.5121/cseij.2022.12101","DOIUrl":"https://doi.org/10.5121/cseij.2022.12101","url":null,"abstract":"Candidates apply in large numbers for jobs on web portals by uploading their resumes, due to the rapid growth of online-based recruitment systems. On the other hand, the resume has its formatting style, data blocks, and segments, as well as a variety of data formatting options such as text alignment, color, font type, and font size, making it an excellent example of unstructured data. As a result, filtering applicants for the appropriate position in an organization becomes a difficult task for recruiters. We can use Natural Language Processing (NLP) techniques to extract the relevant information from the resume to save time and effort. Also, a Machine Learning (ML) model is trained to check whether a candidate’s skills, experiences, and other aspects are suitable for that particular role. In addition to that, our system will also recommend the other available job roles based on the candidate’s skillset.","PeriodicalId":361871,"journal":{"name":"Computer Science & Engineering: An International Journal","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122037038","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
Plant Disease Detection Techniques based on Deep Learning Models: A Review 基于深度学习模型的植物病害检测技术综述
Computer Science & Engineering: An International Journal Pub Date : 2022-02-28 DOI: 10.5121/cseij.2022.12115
Onkar Saxena, Shikha Agrawal, S. Silakari
{"title":"Plant Disease Detection Techniques based on Deep Learning Models: A Review","authors":"Onkar Saxena, Shikha Agrawal, S. Silakari","doi":"10.5121/cseij.2022.12115","DOIUrl":"https://doi.org/10.5121/cseij.2022.12115","url":null,"abstract":"Plants must be checked at an early stage of their life cycle in order to avoid illnesses. Visual observation, which takes longer, and costly expertise are the conventional approach utilised for this monitoring. Therefore, illness detection systems need to be automated in order to speed up this procedure. This study analyses the possibility of technologies for the identification of pest leaf diseases in plants to support agricultural growth. It covers many processes, such as image retrieval, image segmentation, extraction of features and classification. Two key phases comprise plant disease detection technology: segmentation of an open input to detect the ill portion and an extraction approach to extract the image feature and classify the functionality that is removed using different classifiers. The technology consists of two important steps. In this study, segmentation, characteristic removal, and classification approaches are examined and clarified from the perspective of different parameters.","PeriodicalId":361871,"journal":{"name":"Computer Science & Engineering: An International Journal","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123429802","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
Critical Success Factor for Effective Utilization of Mobile AR in the Real Estate Industry 房地产行业有效利用移动增强现实的关键成功因素
Computer Science & Engineering: An International Journal Pub Date : 2022-02-28 DOI: 10.5121/cseij.2022.12116
Yashraj Jain, Jyoti H. Trivedi, Amarnath Cb
{"title":"Critical Success Factor for Effective Utilization of Mobile AR in the Real Estate Industry","authors":"Yashraj Jain, Jyoti H. Trivedi, Amarnath Cb","doi":"10.5121/cseij.2022.12116","DOIUrl":"https://doi.org/10.5121/cseij.2022.12116","url":null,"abstract":"Digitalization has become a new normal. The mobile augmented reality technology adds another dimension like visualization of ongoing or unfurnished property, space measurement, exploring multiple design options among the variety of applications in the real estate sector. The success of any technology will depend on the users’ acceptance of the technology and their intention to use it for a project. Here the researcher tries to explore those pre-usage critical factors with the help of the technology acceptance model followed by verifying it with post-usage perception by using the expectation confirmation model. These theories are tested for confirmatory factor analysis in which these research models were tested for data reliability and discriminant validity. Later the factors were statistically interpreted using the correlation test to conclude the significance of pre and post-usage behavior in technology continuance.","PeriodicalId":361871,"journal":{"name":"Computer Science & Engineering: An International Journal","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131275508","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
Simplex based Social Spider Optimization Method for Improving Medical Data Analysis 基于单纯形的社会蜘蛛优化方法改进医疗数据分析
Computer Science & Engineering: An International Journal Pub Date : 2022-02-28 DOI: 10.5121/cseij.2022.12111
Monalisa Nayak, Soumya Das, U. Bhanja, Manas Ranjan Senapati
{"title":"Simplex based Social Spider Optimization Method for Improving Medical Data Analysis","authors":"Monalisa Nayak, Soumya Das, U. Bhanja, Manas Ranjan Senapati","doi":"10.5121/cseij.2022.12111","DOIUrl":"https://doi.org/10.5121/cseij.2022.12111","url":null,"abstract":"Accurate and reliable prediction is the only way to prevent the disease transmission. Many machine learning models have been developed for prediction of large scale medical datasets. In this paper, Simplex based Social Spider Optimization method is used for classification of three types of medical datasets like heart disease, echocardiogram and hepatitis. The performance of the model is obtained by using Root Mean Square Error (RMSE) and time.","PeriodicalId":361871,"journal":{"name":"Computer Science & Engineering: An International Journal","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122388451","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
Applications of Finite Element Method in Computer Tomography for Cancer and Tumors: A Review 有限元法在癌症和肿瘤计算机断层扫描中的应用综述
Computer Science & Engineering: An International Journal Pub Date : 2022-02-28 DOI: 10.5121/cseij.2022.12114
T. V. Smitha, Raunak Kumar Singh, Naresh Santosh Shet
{"title":"Applications of Finite Element Method in Computer Tomography for Cancer and Tumors: A Review","authors":"T. V. Smitha, Raunak Kumar Singh, Naresh Santosh Shet","doi":"10.5121/cseij.2022.12114","DOIUrl":"https://doi.org/10.5121/cseij.2022.12114","url":null,"abstract":"Computer Tomography (CT) is one of the widely used methods in the field of medical imaging. We can obtain images of any parts of the body including Bones, Muscles, Fat, and Organs from CT. The CT scans of internal organs, bone, soft tissue, and blood vessels provide greater clarity and reveal more details than compared to regular X-rays. One of the best numerical methods to study the behavior of cancerous cells or tumors from CT scan images is the Finite Element (FE) method. The FE mesh consists of three steps. Those are mainly Pre mesh, Mesh, Post mesh. It is efficient to create a 3D Model of these tumors by using Tetrahedral elements. FE method acquires the application such as Data acquisition, Tomographic reconstruction and segmentation, and surface extraction. It is one of the effective tools to understand the mechanical and geometrical characteristics of cancers and predict elastography parameters under different testing conditions. For these applications, high-level meshes are generated using which the analysis of the patient's anatomy is carried out. This technique has the potential to reveal the distribution of Tumor Treating Fields and to acquire the correlation between field strength and survival, which helps to improve the efficiency in the results. This paper thus reviews the study of CT scans using the FE method for cancer and tumors.","PeriodicalId":361871,"journal":{"name":"Computer Science & Engineering: An International Journal","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134265908","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
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信