International Journal of Scientific Methods in Engineering and Management最新文献_第3页

Flexible Real-Time Operating System Co-Design Flow for Embedded Computing Systems 嵌入式计算系统柔性实时操作系统协同设计流程

International Journal of Scientific Methods in Engineering and Management Pub Date : 1900-01-01 DOI: 10.58599/ijsmem.2023.1604

Pilli.Lalitha Kumari, S. Reddy, Sasikala Devireddy

引用次数: 0

Smart Farming based on Machine Learning and IOT 基于机器学习和物联网的智能农业

International Journal of Scientific Methods in Engineering and Management Pub Date : 1900-01-01 DOI: 10.58599/ijsmem.2023.1601

Shamili Srimani Pendyala

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Technology based on the Internet of Things to Monitor Animals 基于物联网的动物监测技术

International Journal of Scientific Methods in Engineering and Management Pub Date : 1900-01-01 DOI: 10.58599/ijsmem.2023.1605

J. Boga, T.Sunitha, K.Manjula

{"title":"Technology based on the Internet of Things to Monitor Animals","authors":"J. Boga, T.Sunitha, K.Manjula","doi":"10.58599/ijsmem.2023.1605","DOIUrl":"https://doi.org/10.58599/ijsmem.2023.1605","url":null,"abstract":"Improving existing animal husbandry practices is essential before introducing grazing animals to vineyards. In order to provide this type of assistance, it is necessary to monitor and condition the animals’ whereabouts and actions, especially their feeding posture. Using this strategy, sheep could graze in agricultural areas (such vineyards and orchards) without fear of harming them. Based on these findings, we have created an IoT-based platform for tracking animal habits. To facilitate unattended shepherding of ovine within vineyard areas, the system integrates a local Internet of Things network for data collection from the animals with a cloud platform with data dispensationalso storage competences. As a result, the system can tend to ovine flocks. Easy analysis and interpretation of Internet of Things (IoT) data is made possible by the machine learning capabilities built into the cloud platform. Therefore, we shall not only outline the platform but also supply some machine learning platform-specific results. To be more specific, testing looked at how well this platform could identify and characterize disorders related to animal posture. This page offers a comparison of the tested approaches because multiple algorithms were used.","PeriodicalId":103282,"journal":{"name":"International Journal of Scientific Methods in Engineering and Management","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133582094","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 massive datasets using an Adaptive and efficient K-Means approach 使用自适应和高效K-Means方法的海量数据集聚类

International Journal of Scientific Methods in Engineering and Management Pub Date : 1900-01-01 DOI: 10.58599/ijsmem.2023.1204

S. Imran, Muthukumaran M, V.Tharakeswari

引用次数: 0

Internet of Things-Based Car Wiper and Accident Location Notification 基于物联网的雨刷器和事故位置通知

International Journal of Scientific Methods in Engineering and Management Pub Date : 1900-01-01 DOI: 10.58599/ijsmem.2023.1502

Gajendra Singh Rajawat, Kamal Singh Rao, M. Sisodia

引用次数: 0

Energy-Saving Smart-Home Automation System Based on the Internet of Things 基于物联网的节能智能家居自动化系统

International Journal of Scientific Methods in Engineering and Management Pub Date : 1900-01-01 DOI: 10.58599/ijsmem.2023.1602

P. Saleem, B. Reddy, K. Venkatesan

引用次数: 0

Implementation of low power N-bit hybrid parallel prefix adder using Xilinx-ISE 使用Xilinx-ISE实现低功耗n位混合并行前缀加法器

International Journal of Scientific Methods in Engineering and Management Pub Date : 1900-01-01 DOI: 10.58599/ijsmem.2023.1104

Kiran Kumar Gopathoti, Naguri Divya Sruthi

{"title":"Implementation of low power N-bit hybrid parallel prefix adder using Xilinx-ISE","authors":"Kiran Kumar Gopathoti, Naguri Divya Sruthi","doi":"10.58599/ijsmem.2023.1104","DOIUrl":"https://doi.org/10.58599/ijsmem.2023.1104","url":null,"abstract":"Recently, digital circuitry has demanded a decrease in space and power by decreasing time while simultaneously improving performance in speed. This has resulted in a need for more efficient use of the available space. Adders are fundamental components that are used in the construction of digital circuits. As a consequence of this, the performance of adders has to be improved in order to enhance the performance of integrated circuits that are used in the real world. The creation of a novel parallel prefix adder (PPA) architecture known as Hybrid PPA is the primary topic of this article. Hybrid PPA makes use of full carrier generation (FCG), full sum generation (FSG), half carry generation (HCG), and half sum generation (HSG) blocks. In addition to this, the N-bit Hybrid-PPA is constructed with features that may be reconfigured, and these features utilise square root additions through modified sum carry selection (MSCS). In addition, the implementation of multiplexer switching logic, which selects the whole sum bits and carry bits in a high-speed manner, reduces the amount of propagation time necessary for the generation of the sum and carry output. The results of the simulation show that using the proposed Hybrid PPA results in a reduction in area, latency, and power consumption when compared to using basic adders or approaches that are considered to be state of the art.","PeriodicalId":103282,"journal":{"name":"International Journal of Scientific Methods in Engineering and Management","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124299712","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

Automatic Portrait Image Cropping using Machine Learning Models 使用机器学习模型的自动肖像图像裁剪

International Journal of Scientific Methods in Engineering and Management Pub Date : 1900-01-01 DOI: 10.58599/ijsmem.2023.1107

Naguri Sobha Rani, Naguri Divya Sruthi

引用次数: 0

An exposition on the prediction of load on a Smart Grid 对智能电网负荷预测的探讨

International Journal of Scientific Methods in Engineering and Management Pub Date : 1900-01-01 DOI: 10.58599/ijsmem.2023.1202

Vijendra Pratap Singh, Praveen Kumar Reddy K, Nagarjuna Reddy Gujjula

{"title":"An exposition on the prediction of load on a Smart Grid","authors":"Vijendra Pratap Singh, Praveen Kumar Reddy K, Nagarjuna Reddy Gujjula","doi":"10.58599/ijsmem.2023.1202","DOIUrl":"https://doi.org/10.58599/ijsmem.2023.1202","url":null,"abstract":"Smart grids depend on AI-based load forecasting to estimate future power demand (AI). Deep learning is especially important in smart grid load forecasting with neural networks (ANN). Processing time and data are needed to count smart grid deep learning. Combining data would speed load projections. The bottleneck strategy has been abandoned to attain this precision. Keeping the lights on requires short-term electricity demand prediction. But, the load’s intricacy and volatility make it fun to predict. EEMD breaks the load into many frequency-dependent components of different strengths. MLR predicts low-frequency regularities, while LSTM neural networks predict high-frequency components. Computational extent is unchanged. Despite its varied aggregation scope, the electric grid’s large data can be used to create the most effective deep learning models for Short-term Load Forecasting (STLF) in electrical networks. Hence, a suitable forecasting strategy uses deep learning with a Micro-clustering (MC) job that mixes unsupervised and supervised clustering tasks utilizingKmeans and Gaussian Support Vector Machine. To guarantee accuracy. B-bidirectional LSTMs can store feed-forward and future hidden-layer data. Feedback and feed-forward loops do this. The DaviesBouldering index determined cluster production per hour. MC with B-LSTM networks improves prediction,especially around spike locations. Forecasting RE generation and grid load is difficult. Prosumer microgrids (PMGs) sell electricity to aggregators. A hybrid machine learning-based load and weather data transmission method provides the biggest benefit. ANFIS, MLP, and radial basis function artificial neural networks (ANNs) would be used in this technique (RBF). Machine learning-based hybrid forecasting can improve accuracy.","PeriodicalId":103282,"journal":{"name":"International Journal of Scientific Methods in Engineering and Management","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124075294","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

Detecting Fake Faces with AI: A Deep Neural Network Improvement Project 用AI检测假脸:一个深度神经网络改进项目

International Journal of Scientific Methods in Engineering and Management Pub Date : 1900-01-01 DOI: 10.58599/ijsmem.2023.1405

L.Ravi Kumar, Ram Kumar Yadav, S.Yuvaraj

引用次数: 0