2022 IEEE 7th International conference for Convergence in Technology (I2CT)最新文献

Application of the Refactoring to the Understandability and the Cognitive Complexity of a Software 重构在软件可理解性和认知复杂性中的应用

2022 IEEE 7th International conference for Convergence in Technology (I2CT) Pub Date : 2022-04-07 DOI: 10.1109/i2ct54291.2022.9824082

D. Wijendra, K. Hewagamage

引用次数: 0

Decision-Making Platform for SMART Plantation Agriculture Using Machine Learning and Image Processing 基于机器学习和图像处理的智能种植农业决策平台

2022 IEEE 7th International conference for Convergence in Technology (I2CT) Pub Date : 2022-04-07 DOI: 10.1109/i2ct54291.2022.9825063

Supunya Swarnakantha, Bhagyani Chathurika, K. V. Weragoda, W. M. I. K. Bowatte, E.V Thalawala, M. Bandara

{"title":"Decision-Making Platform for SMART Plantation Agriculture Using Machine Learning and Image Processing","authors":"Supunya Swarnakantha, Bhagyani Chathurika, K. V. Weragoda, W. M. I. K. Bowatte, E.V Thalawala, M. Bandara","doi":"10.1109/i2ct54291.2022.9825063","DOIUrl":"https://doi.org/10.1109/i2ct54291.2022.9825063","url":null,"abstract":"Plantation agriculture plays a crucial role in the Sri Lankan economy in terms of both values of production and employment, even though the relative contribution has declined in recent years. Climate variability and volatile commodity prices influence agricultural production and revenue. Production and marketing decisions are frequently based on insufficient knowledge of the specific outcome of that decision. Therefore, most planters are having difficulty with the decision-making process since they are not using high-level technologies and are relying on conventional approaches. As a result, Sri Lankan agriculture and plantation industries are operating at a lower production capacity. The objective of this study is to analyze and propose appropriate solutions to the challenges that the planters face daily based on their environmental characteristics, previous data, and using their mobile phone cameras, planters will be able to make the most precise decisions using high-level technologies. This system presents a software-enabled platform for predicting future yields, forecasting the future market and intermediate buying selling prices, recognizing pests, and providing appropriate treatments, forecasting a fertilizer plan and water delivery according to soil type, and selecting the most suitable crops for cultivation. Aside from that, introducing a platform where planters can sell their crop to local and international customers and planters can communicate with experts and other planters through an agricultural forum. Machine learning, deep learning, and image processing techniques are employed to develop this system.","PeriodicalId":185360,"journal":{"name":"2022 IEEE 7th International conference for Convergence in Technology (I2CT)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115626886","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

Performance Analysis of Standalone DC Microgrid for Different Converter Topologies 不同变流器拓扑下独立直流微电网性能分析

2022 IEEE 7th International conference for Convergence in Technology (I2CT) Pub Date : 2022-04-07 DOI: 10.1109/i2ct54291.2022.9824152

Aishwarya B Kallanagoudar, Anupama R. Itagi, S. Karajgi, M. Kappali

引用次数: 0

Parallelizing Sequential Algorithms using MPICH Programming with Case Studies 并行顺序算法使用MPICH编程与案例研究

2022 IEEE 7th International conference for Convergence in Technology (I2CT) Pub Date : 2022-04-07 DOI: 10.1109/i2ct54291.2022.9825354

D. K. Reddy

引用次数: 0

IFVSNet : Intermediate Features Fusion based CNN for Video Subtitles Identification 基于中间特征融合的CNN视频字幕识别

2022 IEEE 7th International conference for Convergence in Technology (I2CT) Pub Date : 2022-04-07 DOI: 10.1109/i2ct54291.2022.9825167

Veronica Naosekpam, Nilkanta Sahu

{"title":"IFVSNet : Intermediate Features Fusion based CNN for Video Subtitles Identification","authors":"Veronica Naosekpam, Nilkanta Sahu","doi":"10.1109/i2ct54291.2022.9825167","DOIUrl":"https://doi.org/10.1109/i2ct54291.2022.9825167","url":null,"abstract":"This paper presents a method to determine the presence of subtitle in a video frame through intermediate features fusion-based Convolutional Neural Network (CNN) called the IFVSNet via partial transfer learning process on pre-trained VGG13. The intermediate features from all the convolutional blocks of the CNN are fused by concatenation after each max-pooling layer. The features to be fused are of the same dimension. They are then flattened and passed as an input to the subsequent fully connected layers, ending with the sigmoid layer. Binary cross-entropy is used as the objective function. The model is evaluated on the Film Videos Dataset (FiViD) [21], which is composed of video frames with and without subtitles in Arabic languages. We obtained an average accuracy of 98.83% which can be taken as an effective result. We have also conducted other experiments by fine-tuning the VGG13 model, another by using VGG13 as the features extractor and Long Short Term Memory (LSTM) as the classifier, and lastly, with a 3-layers CNN trained from scratch. It is observed that the performances of these three models are lower than the proposed methodology. The class-wise analysis of the proposed method has also demonstrated that the model is quite strong in distinguishing the classes present in the dataset and achieved a precision, recall, and F-score of above 98%.","PeriodicalId":185360,"journal":{"name":"2022 IEEE 7th International conference for Convergence in Technology (I2CT)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117190489","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

Transfer Learning: A way for Ear Biometric Recognition 迁移学习:耳朵生物特征识别的一种方法

2022 IEEE 7th International conference for Convergence in Technology (I2CT) Pub Date : 2022-04-07 DOI: 10.1109/i2ct54291.2022.9824374

Swapnil Singh, Snehi Suman

引用次数: 2

Effective Prediction of Heart Disease: Data Mining in Healthcare Domain 心脏病的有效预测:医疗保健领域的数据挖掘

2022 IEEE 7th International conference for Convergence in Technology (I2CT) Pub Date : 2022-04-07 DOI: 10.1109/i2ct54291.2022.9825110

Swapna Bhavsar, Anil Badarla, R. Phursule

{"title":"Effective Prediction of Heart Disease: Data Mining in Healthcare Domain","authors":"Swapna Bhavsar, Anil Badarla, R. Phursule","doi":"10.1109/i2ct54291.2022.9825110","DOIUrl":"https://doi.org/10.1109/i2ct54291.2022.9825110","url":null,"abstract":"For extracting concealed patterns, mining of Data, applying clubbed schemes of Database technology, machine learning and statistical analysis, is being implemented in Big Databases. In addition to this, due to their applications in enhancing various uses in outstanding areas of Medical systems, health care data mining became an ever growing important subject for research and study. While scanning fatalities world over, cardiac ailment seems to be main reasons. Sensing people’s probability in getting into diseases related to heart is quite complicated task for cardiologists, involving a good deal of years into their expertise and extensive medical testing. Businesses dealing into medical fields accumulated huge chunk of information pertaining to particular data that is found to be essential in better decision making for health care expert. For taking Good decisions and provide adequate results on data Particular developed data mining schemes are implemented. Concerning this research, 3 groups for data mining schemes such as Naïve Bayes, Decision tree and K-NN, were taken for discussion, and implemented in enhancing diseases of heart disease for casting systems in prediction and analysis. Main aim of such research lies in establishing optimal methods of grouping in maximizing accurate classification of abnormal and normal population. In avoiding precious life loss before time, hence is became possible. Testing setup was developed in measuring behavior of algorithms by UCI machine learning Repository’s dataset on cardiac ailments. In comparison with remaining prevention of heart disease algorithms, it was seen that Naïve Bayes algorithm is best by providing precision of up to 98%.","PeriodicalId":185360,"journal":{"name":"2022 IEEE 7th International conference for Convergence in Technology (I2CT)","volume":"159 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121052372","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

Motion Anomaly Detection in Surveillance Videos Using Spatial and Temporal Features 基于时空特征的监控视频运动异常检测

2022 IEEE 7th International conference for Convergence in Technology (I2CT) Pub Date : 2022-04-07 DOI: 10.1109/i2ct54291.2022.9825295

Raahat Gupta, S. Raghuvanshi, Vinal Patel

引用次数: 1

Small-Scale Hybrid Solar and Wind Power Generation System 小型太阳能和风能混合发电系统

2022 IEEE 7th International conference for Convergence in Technology (I2CT) Pub Date : 2022-04-07 DOI: 10.1109/i2ct54291.2022.9824271

N. Karthikeyan, Aakash S Jamadagni, N. R., Chanakya S Arkasali, Gousia Sultana

引用次数: 0

A Systematic Survey on Computational agents for Mental Health Aid 心理健康援助计算代理的系统调查

2022 IEEE 7th International conference for Convergence in Technology (I2CT) Pub Date : 2022-04-07 DOI: 10.1109/i2ct54291.2022.9824269

Madiha Mansoori, Hrishil Maliwal, Sharvil Kotian, Hersh Kenkre, Ishani Saha, Payal Mishra

{"title":"A Systematic Survey on Computational agents for Mental Health Aid","authors":"Madiha Mansoori, Hrishil Maliwal, Sharvil Kotian, Hersh Kenkre, Ishani Saha, Payal Mishra","doi":"10.1109/i2ct54291.2022.9824269","DOIUrl":"https://doi.org/10.1109/i2ct54291.2022.9824269","url":null,"abstract":"In recent times the rate of mental health disorders among the youth has spiked due to increased competitiveness which affects the mental well-being of students. An unhealthy mental state not only affects the daily life of an individual but is also the reason for increased self-harm and suicide rates. In developing nations, the ratio of mental care professionals to mental health patients is far too less for all to receive care. A solution to this problem is internet-delivered cognitive therapy (iCBT). The objective of this paper is to shed light on various techniques that can deliver iCBT to a patient in a comfortable manner. Since iCBT can be delivered from home, it tackles the challenge of societal stigma. Different existing approaches and solutions being implemented like various types of chatbots(SERMO, EMMA) and social robots(Ryan Bot)are analyzed and compared in this paper. We also analyze different types of existing datasets(NHS Mental Health Dataset, CounselChat Dataset, ISEAR Dataset) used to train various models(Convolutional Neural Networks, Recursive Neural Networks, Hierarchical Attention Network, Transformers). Word Count Per Session, Sentiment Analysis and Emotion Analysis were some of the evaluation metrics analyzed.","PeriodicalId":185360,"journal":{"name":"2022 IEEE 7th International conference for Convergence in Technology (I2CT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125740311","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