Innovations in Systems and Software Engineering最新文献_第4页

Automated credit assessment framework using ETL process and machine learning. 使用 ETL 流程和机器学习的自动信用评估框架。

IF 1.2

Innovations in Systems and Software Engineering Pub Date : 2022-12-31 DOI: 10.1007/s11334-022-00522-x

Neepa Biswas, Anindita Sarkar Mondal, Ari Kusumastuti, Swati Saha, Kartick Chandra Mondal

{"title":"Automated credit assessment framework using ETL process and machine learning.","authors":"Neepa Biswas, Anindita Sarkar Mondal, Ari Kusumastuti, Swati Saha, Kartick Chandra Mondal","doi":"10.1007/s11334-022-00522-x","DOIUrl":"10.1007/s11334-022-00522-x","url":null,"abstract":"In the current business scenario, real-time analysis of enterprise data through Business Intelligence (BI) is crucial for supporting operational activities and taking any strategic decision. The automated ETL (extraction, transformation, and load) process ensures data ingestion into the data warehouse in near real-time, and insights are generated through the BI process based on real-time data. In this paper, we have concentrated on automated credit risk assessment in the financial domain based on the machine learning approach. The machine learning-based classification techniques can furnish a self-regulating process to categorize data. Establishing an automated credit decision-making system helps the lending institution to manage the risks, increase operational efficiency and comply with regulators. In this paper, an empirical approach is taken for credit risk assessment using logistic regression and neural network classification method in compliance with Basel II standards. Here, Basel II standards are adopted to calculate the expected loss. The required data integration for building machine learning models is done through an automated ETL process. We have concluded this research work by evaluating this new methodology for credit risk assessment.","PeriodicalId":44465,"journal":{"name":"Innovations in Systems and Software Engineering","volume":" ","pages":"1-14"},"PeriodicalIF":1.2,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9803598/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10508957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparative exploration of CNN model and transfer learning on fire image dataset 火灾图像数据集上CNN模型与迁移学习的比较研究

IF 1.2

Innovations in Systems and Software Engineering Pub Date : 2022-12-27 DOI: 10.1007/s11334-022-00521-y

Sudip Suklabaidya, Indrani Das

引用次数: 0

A low-cost hybrid handwritten Devanagari character classifier 一个低成本的混合手写德文字符分类器

IF 1.2

Innovations in Systems and Software Engineering Pub Date : 2022-12-23 DOI: 10.1007/s11334-022-00518-7

Jayati Mukherjee, Sneha Mishra, Arjit Tomar, Vikas Kumar

引用次数: 1

Emotion recognition from lyrical text of Hindi songs 从印地语歌曲抒情文本看情感识别

IF 1.2

Innovations in Systems and Software Engineering Pub Date : 2022-12-22 DOI: 10.1007/s11334-022-00520-z

Sourish Dhar, Vishal Gour, Arnab Paul

引用次数: 1

Smart automation in manufacturing process using industrial internet of things (IIoT) architecture 利用工业物联网（IIoT）架构实现制造过程的智能自动化

IF 1.2

Innovations in Systems and Software Engineering Pub Date : 2022-12-12 DOI: 10.1007/s11334-022-00504-z

Jasjeet Singh, C. Banerjee, S. Pandey

引用次数: 4

A hybrid cellular automata-based model for leakage detection in smart drip irrigation water pipeline structure using IoT sensors 基于混合元胞自动机的物联网传感器智能滴灌管道结构泄漏检测模型

IF 1.2

Innovations in Systems and Software Engineering Pub Date : 2022-12-12 DOI: 10.1007/s11334-022-00503-0

A. Banerjee, C. Banerjee

引用次数: 0

Mental health issues assessment using tools during COVID-19 pandemic. 在 COVID-19 大流行期间使用工具评估心理健康问题。

IF 1.1

Innovations in Systems and Software Engineering Pub Date : 2022-12-12 DOI: 10.1007/s11334-022-00510-1

Hamnah Rao, Meenu Gupta, Parul Agarwal, Surbhi Bhatia, Rajat Bhardwaj

{"title":"Mental health issues assessment using tools during COVID-19 pandemic.","authors":"Hamnah Rao, Meenu Gupta, Parul Agarwal, Surbhi Bhatia, Rajat Bhardwaj","doi":"10.1007/s11334-022-00510-1","DOIUrl":"10.1007/s11334-022-00510-1","url":null,"abstract":"COVID-19 has brought distress among people as pandemic has impacted the globe not only economically or physically, but also psychologically by degrading their mental health. Several research were done in the past which tried to capture these issues but post-covid situation needs to be critically handled and analyzed so that corrective measures for cure and support can be taken. The current work is an attempt to observe the mental health issues (anxiety and depression) that occurred during the lockdown by combining a few pre-designed questionnaires. The online survey included 244 respondents (females = 126, males = 118) and when we thoroughly examined gender, age group, and occupational activity as three main factors, the results showed that female students aged 21-35 were affected more than male students of the same age group. In this study, we used a 4-item Geriatric Depression Scale (GDS-4) as a depression screening instrument and discovered that 225 out of total respondents were depressed. Using the Generalized Anxiety Disorder (GAD-7), a self-administered anxiety tool, we found 103 responders with mild, 87 with moderate, 12 with severe, and 42 with no anxiety symptoms. Patient Health Questionnaire (PHQ-9) showed the symptoms of mental disorders where 68 individuals had mild, 85 had moderate, 37 had moderately severe, 12 had severe, and 42 had no symptoms. With the help of multiple linear regression analysis, demographic data were evaluated, and later results were compared between GDS-4, GAD-7, and PHQ-9 using correlation coefficients. This will help practitioners and individuals to focus on their physiological health and adopt diagnostic measures.","PeriodicalId":44465,"journal":{"name":"Innovations in Systems and Software Engineering","volume":" ","pages":"1-12"},"PeriodicalIF":1.1,"publicationDate":"2022-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9742669/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10460744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

LowEST: a low resource semantic text summarization method for big data LowEST：一种低资源的大数据语义文本摘要方法

IF 1.2

Innovations in Systems and Software Engineering Pub Date : 2022-12-09 DOI: 10.1007/s11334-022-00514-x

Sufal Das

引用次数: 0

Opinion classification at subtopic level from COVID vaccination-related tweets. 根据 COVID 疫苗接种相关推文进行子话题层面的意见分类。

IF 1.1

Innovations in Systems and Software Engineering Pub Date : 2022-12-09 DOI: 10.1007/s11334-022-00516-9

Mrinmoy Sadhukhan, Pramita Bhattacherjee, Tamal Mondal, Sudakshina Dasgupta, Indrajit Bhattacharya

{"title":"Opinion classification at subtopic level from COVID vaccination-related tweets.","authors":"Mrinmoy Sadhukhan, Pramita Bhattacherjee, Tamal Mondal, Sudakshina Dasgupta, Indrajit Bhattacharya","doi":"10.1007/s11334-022-00516-9","DOIUrl":"10.1007/s11334-022-00516-9","url":null,"abstract":"Coronavirus disease 2019 (Covid-19) is a contiguous disease which affected a large volume of population with a high mortality rate across the globe. For dealing with the recent spread of COVID-19, one of the prime measures was to vaccinate people in full extent. People across the globe have diverse opinion regarding the vaccination process, its side effect and effectiveness. Such opinions get located into different micro-blogging sites including twitter. Opinion mining through analyzing public sentiments of such micro-blogs is a common method for detection of public responses. This paper focuses on classifying the public opinions expressed related to COVID-19 vaccination at sub topic level. The procedure tries to find out different keywords regarding positive, negative and neutral sentences. From those keywords, different related query set was constructed using Rocchio query expansion algorithm for positive, negative and neutral sentiments. Later Extended query set is used to form subtopic using LDA algorithm to identify the nature of the tweets. The proposed LDA model came across with 0.56 coherence score with twenty subtopics, which is fair enough to classify the tweets in different classes. This trained model is finally used to classify the tweets in real time with Apache Kafka framework regarding different subtopic based on positive, negative or neutral sentiment.","PeriodicalId":44465,"journal":{"name":"Innovations in Systems and Software Engineering","volume":" ","pages":"1-12"},"PeriodicalIF":1.1,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9734573/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10749763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A novel hybrid multi-resource load balancing approach using ant colony optimization with Tabu search for cloud computing 一种基于蚁群优化和禁忌搜索的云计算混合多资源负载平衡方法

IF 1.2

Innovations in Systems and Software Engineering Pub Date : 2022-12-08 DOI: 10.1007/s11334-022-00508-9

Jyotsna P. Gabhane, Sunil Pathak, N. Thakare

引用次数: 4