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A Novel Approach to Organize Blood Donation Camp and Blood Unit Wastage Management 组织献血营和血液单位损耗管理的新方法
Int. J. Softw. Innov. Pub Date : 2023-11-15 DOI: 10.4018/ijsi.333517
P. Ghosh, Takaaki Goto, Leena Jana Ghosh, Giridhar Maji, Soumya Sen
{"title":"A Novel Approach to Organize Blood Donation Camp and Blood Unit Wastage Management","authors":"P. Ghosh, Takaaki Goto, Leena Jana Ghosh, Giridhar Maji, Soumya Sen","doi":"10.4018/ijsi.333517","DOIUrl":"https://doi.org/10.4018/ijsi.333517","url":null,"abstract":"In the countries or areas where the supply-demand ratio of blood is not maintained, the medication process is being deteriorated, and this may be as fatal as death of the patients. It is being observed in different areas in different seasons or may be at the time of festival scarcity of blood may happen. On the other hand, if the blood donation camp is organized frequently, there may be a surplus of blood as it has expiry dates. Along with these issues, due to the transportation or mismanagement, blood units are wasted. These problems are addressed in this research work, and methodologies are proposed to determine the most suitable blood bank with respect to the blood donation camp. Further, a demand forecasting algorithm is used both for predicting the blood unit demand of every blood bank and for transferring excess blood units to the blood bank where it is needed the most, and also, for the efficient transportation of the blood units, taxicab geometry-based paths are employed.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"20 4","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2023-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139272670","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
Road Rage and Aggressive Driving Behaviour Detection in Usage-Based Insurance Using Machine Learning 基于使用的保险中道路愤怒和攻击性驾驶行为检测的机器学习
Int. J. Softw. Innov. Pub Date : 2023-03-02 DOI: 10.4018/ijsi.319314
Subramanian Arumugam, R. Bhargavi
{"title":"Road Rage and Aggressive Driving Behaviour Detection in Usage-Based Insurance Using Machine Learning","authors":"Subramanian Arumugam, R. Bhargavi","doi":"10.4018/ijsi.319314","DOIUrl":"https://doi.org/10.4018/ijsi.319314","url":null,"abstract":"Driving behaviour is a critical issue in modern transportation systems due to the increasing concerns about the safety of drivers, passengers, and road users. Machine learning models are capable of learning driving patterns from sensor data and recognizing individuals by their driving behaviours. This paper presents a novel framework for aggressive driving detection and driver classification based on driving events identified from GPS data collected with smartphones and heart rate of the driver captured with a wearable device. The proposed system for road rage and aggressive driving detection (RAD) is realized with an integral framework with components for data acquisition, event detection, driver classification, and model interpretability. The system is implemented by generating a prediction model by training machine learning classifiers with a dataset collected in a cohort to classify drivers into good, unhealthy, road rage, and always bad. The proposed system is to improve road safety and to customize insurance premiums in the best interest of policy holders and insurance companies.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126416190","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
Breast Cancer Prediction and Control Using BiLSTM and Two-Dimensional Convolutional Neural Network 基于BiLSTM和二维卷积神经网络的乳腺癌预测与控制
Int. J. Softw. Innov. Pub Date : 2023-01-20 DOI: 10.4018/ijsi.316169
M. Agana, C. Agwu, Nsinem A. Ukpoho
{"title":"Breast Cancer Prediction and Control Using BiLSTM and Two-Dimensional Convolutional Neural Network","authors":"M. Agana, C. Agwu, Nsinem A. Ukpoho","doi":"10.4018/ijsi.316169","DOIUrl":"https://doi.org/10.4018/ijsi.316169","url":null,"abstract":"Breast cancer has a devastating effect on women. Different strategies of breast cancer classification exist with minimal work done on the prediction of the occurrence of the disease in potential carriers. In this study, a breast cancer predictive system has been developed using bidirectional long short-term memory (BiLSTM) for feature extraction and learning while the two-dimensional convolutional neural network (CNN) was used for breast cancer classification. Histopathological images were used for cancer prediction. Python was used as the programming language for implementing the system. The model was tested using datasets from The Cancer Imaging Archive (TCIA) repository. An accuracy level of 98.8% (higher than the most recent existing model) was achieved for the prediction of the future occurrence of breast cancer based on the tests on the dataset. The application of the model using live data from women can help in the prediction and control of the occurrence of breast cancer amongst women.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122076151","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
Effective Classification of Chronic Kidney Disease Using Extreme Gradient Boosting Algorithm 基于极端梯度增强算法的慢性肾脏疾病有效分类
Int. J. Softw. Innov. Pub Date : 2023-01-13 DOI: 10.4018/ijsi.315732
Ramya Asalatha Busi, M. J. Stephen
{"title":"Effective Classification of Chronic Kidney Disease Using Extreme Gradient Boosting Algorithm","authors":"Ramya Asalatha Busi, M. J. Stephen","doi":"10.4018/ijsi.315732","DOIUrl":"https://doi.org/10.4018/ijsi.315732","url":null,"abstract":"With a high rate of morbidity and mortality, chronic kidney disease is a global health issue that also causes other diseases. Patients frequently overlook the condition because there aren't any evident symptoms in the early stages of CKD. An efficient and effective Extreme gradient boosting method for the early diagnosis of kidney illness has been proposed in this paper to explore the capability of various machine learning algorithms. DenseNet can extract a variety of features such as vector features. After that feature extraction phase, the data are fed into the feature selection phase. The features are selected based upon the Improved Salp swarm Algorithm (ISSA). The proposed CKD classification method has been simulated in PYTHON. Utilizing the CKD dataset from the UCI machine learning resources, the dataset is then tested. Sensitivity, accuracy, and specificity are the performance metrics used for the proposed CKD classification approach. The results of the experiments demonstrate that the proposed approach outperforms the present state-of-the-art method in classifying CKD.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134430024","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
An Outlook Architecture: Protocols and Challenges in IoT and Future Trends 展望架构:物联网中的协议和挑战以及未来趋势
Int. J. Softw. Innov. Pub Date : 2023-01-06 DOI: 10.4018/ijsi.315744
Kajal S. Patel, M. Mehta
{"title":"An Outlook Architecture: Protocols and Challenges in IoT and Future Trends","authors":"Kajal S. Patel, M. Mehta","doi":"10.4018/ijsi.315744","DOIUrl":"https://doi.org/10.4018/ijsi.315744","url":null,"abstract":"The internet of things (IoT) has recently received much attention due to its revolutionary potential. The internet of things facilitates data interchange in a large number of possible applications, including smart transportation, smart health, smart buildings, and so on. As a result, these application domains can be grouped to form smart life. In response to the IoT's rapid growth, cybercriminals and security professionals are racing to keep up. Billions of connected devices can exchange sensitive information with each other. As a result, securing IoT and protecting users' privacy is a huge concern. A session for communication in a network is established by authenticating and validating the device's identity and checking whether it is a legal device. The IoT technology can be used for various applications only if challenges related to IoT security can be overcome.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133464815","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 Study on Prediction Performance Measurement of Automated Machine Learning: Focusing on WiseProphet, a Korean Auto ML Service 自动机器学习预测性能测量研究:以韩国自动机器学习服务公司WiseProphet为例
Int. J. Softw. Innov. Pub Date : 2023-01-01 DOI: 10.4018/ijsi.315656
E. Im, Jina Lee, Sungbyeong An, Gwang-Young Gim
{"title":"A Study on Prediction Performance Measurement of Automated Machine Learning: Focusing on WiseProphet, a Korean Auto ML Service","authors":"E. Im, Jina Lee, Sungbyeong An, Gwang-Young Gim","doi":"10.4018/ijsi.315656","DOIUrl":"https://doi.org/10.4018/ijsi.315656","url":null,"abstract":"In digital economics, where value creation using big data becomes important, the ability to analyze data using machine learning and deep learning technology is a key activity in corporate activities. Nevertheless, companies consider it difficult to introduce machine learning and artificial intelligence technologies because they need an understanding of the business as well as data and analysis algorithms. Accordingly, services such as automated machine learning have emerged for easy use of machine learning. In this study, the authors explored the automated machine learning service and compared the random forest and extreme gradient boosting analysis results using WiseProphet and Python. WiseProphet is used as a representative of automated machine learning solutions because it is a cloud-based service that anyone can easily access and can be used in various ways. It is contrasted with the model implemented by Python, which writes code with No coding. As a result of comparing the prediction performance, WiseProphet automatically outperformed the analysis result by parameter optimization.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126004068","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
Cyber-Physical Urban Mobility Systems: Opportunities and Challenges in Developing Countries 网络-实体城市交通系统:发展中国家的机遇与挑战
Int. J. Softw. Innov. Pub Date : 2023-01-01 DOI: 10.4018/ijsi.315662
Dénis Awé Samalna, J. M. Ngossaha, Ado Adamou Abba Ari, Kolyang
{"title":"Cyber-Physical Urban Mobility Systems: Opportunities and Challenges in Developing Countries","authors":"Dénis Awé Samalna, J. M. Ngossaha, Ado Adamou Abba Ari, Kolyang","doi":"10.4018/ijsi.315662","DOIUrl":"https://doi.org/10.4018/ijsi.315662","url":null,"abstract":"Rapid population growth and the number of vehicles in cities have complicated urban mobility management. Digitalization supported by the internet of things and wireless communication has allowed some cities to mitigate the problem by taking advantage of the multiple benefits offered. These are cyber-physical systems (CPS), which are systems where a number of devices collaborate for the control of physical entities. This recent technology finds its application in urban mobility. However, in the context of developing countries, there are many local specificities one needs to consider. How could the integration of cyber-physical systems help urban decision makers to design sustainable urban mobility systems that meet the needs of the population? The paper proposed not only a recent review of the literature, but also a framework of CPS of urban mobility to guide decision makers. The challenges, opportunities, and barriers to innovation of CPS in urban environments in developing countries have also been identified.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"87 2 Suppl 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128460399","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
Prediction of Customer Review's Helpfulness Based on Feature Engineering Driven Deep Learning Model 基于特征工程驱动深度学习模型的客户评论有用性预测
Int. J. Softw. Innov. Pub Date : 2023-01-01 DOI: 10.4018/ijsi.315734
Suryanarayan Sharma, Laxman Singh, Rajdev Tiwari
{"title":"Prediction of Customer Review's Helpfulness Based on Feature Engineering Driven Deep Learning Model","authors":"Suryanarayan Sharma, Laxman Singh, Rajdev Tiwari","doi":"10.4018/ijsi.315734","DOIUrl":"https://doi.org/10.4018/ijsi.315734","url":null,"abstract":"Online consumer reviews play a pivotal role in boosting online shopping. After Covid-19, the e-commerce industry has been grown exponentially. The e-commerce industry is greatly impacted by the online customer reviews, and a lot of work has been done in this regard to identify the usefulness of reviews for purchasing online products. In this proposed work, predicting helpfulness is taken as binary classification problem to identify the helpfulness of a review in context to structural, sentimental, and voting feature sets. In this study, the authors implemented various leading ML algorithms such as KNN, LR, GNB, LDA and CNN. In comparison to these algorithms and other existing state of art methods, CNN yielded better classification results, achieving highest accuracy of 95.27%. Besides, the performance of these models was also assessed in terms of precision, recall, F1 score, etc. The results shown in this paper demonstrate that proposed model will help the producers or service providers to improve and grow their business.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114918544","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
Sentiment Analysis of Tweets During the COVID-19 Pandemic Using Multinomial Logistic Regression 基于多项逻辑回归的COVID-19大流行期间推文情绪分析
Int. J. Softw. Innov. Pub Date : 2023-01-01 DOI: 10.4018/ijsi.315740
Supriya Raheja, Anjani Asthana
{"title":"Sentiment Analysis of Tweets During the COVID-19 Pandemic Using Multinomial Logistic Regression","authors":"Supriya Raheja, Anjani Asthana","doi":"10.4018/ijsi.315740","DOIUrl":"https://doi.org/10.4018/ijsi.315740","url":null,"abstract":"Recently, the research on sentimental analysis has been growing rapidly. The tweets of social media are extracted to analyze the user sentiments. Many of the studies prefer to apply machine learning algorithms for performing sentiment analysis. In the current pandemic, there is an utmost importance to analyze the sentiments or behavior of a person to make the decisions as the whole world is facing lockdowns in multiple phases. The lockdown is psychologically affecting the human behavior. This study performs a sentimental analysis of Twitter tweets during lockdown using multinomial logistic regression algorithm. The proposed system framework follows the pre-processing, polarity and scoring, and feature extracting before applying the machine learning model. For validating the performance of proposed framework, other three majorly used machine learning based models-- namely decision tree, naïve Bayes, and K-nearest neighbors-- are implemented. Experimental results prove that the proposed framework provides improved accuracy over other models.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127912300","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
PageRank and HodgeRank on Ethereum Transactions: A Measure for Social Credit 以太坊交易中的PageRank和HodgeRank:一种衡量社会信用的方法
Int. J. Softw. Innov. Pub Date : 2023-01-01 DOI: 10.4018/ijsi.315737
Huu-Dung Do, Thuat Do
{"title":"PageRank and HodgeRank on Ethereum Transactions: A Measure for Social Credit","authors":"Huu-Dung Do, Thuat Do","doi":"10.4018/ijsi.315737","DOIUrl":"https://doi.org/10.4018/ijsi.315737","url":null,"abstract":"Mathematical ranking plays a critical role in the era of the internet and bigdata. Google's PageRank is well-known as a trillion-dollar algorithm. Definitely, algorithmic ranking frameworks are found on every search engine. In this paper, the article shall investigate how PageRank can be applied in the blockchain space to build up reliable and verifiable social credit and reputation systems. It is expected to provide a measure of credibility complementary and parallel with FICO, which is not applicable for individuals lacking credit information in financial institutions. Moreover, the approach proposes an unbiased method of interpreting and measuring real social interaction and reputation ranking on a blockchain network. The authors envision a future of payment based on cryptocurrencies (especially stable coins) and digital fiats; thus the proposed credit scoring framework shall be helpful for P2P credit and lending networks, possibly for decentralized finance (Defi) applications.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133949363","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
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