IF 2.8 4区生物学

3 Biotech Pub Date : 2024-05-22 DOI: 10.1007/s13205-024-04003-9

Asmaa I. El-Shazly, Marwa I. Wahba, Nayera A. M. Abdelwahed, Abeer N. Shehata

引用次数: 0

A Predictive Approach for Evaluating Thermo-Physical Properties of Nano fluids Using Artificial Intelligence Algorithms 基于人工智能算法的纳米流体热物性预测方法

IF 2.8 4区生物学

3 Biotech Pub Date : 2023-09-01 DOI: 10.46632/jdaai/2/3/10

Som veer, M. Kumari, A. Pramanik, B. Lakshmaiah, B. Godara, PL Parameswari

{"title":"A Predictive Approach for Evaluating Thermo-Physical Properties of Nano fluids Using Artificial Intelligence Algorithms","authors":"Som veer, M. Kumari, A. Pramanik, B. Lakshmaiah, B. Godara, PL Parameswari","doi":"10.46632/jdaai/2/3/10","DOIUrl":"https://doi.org/10.46632/jdaai/2/3/10","url":null,"abstract":"Artificial Intelligence (AI) algorithms are increasingly being employed as substitutes for conventional methods or as components within integrated systems. They have demonstrated effectiveness in addressing complex applied problems across various domains, gaining popularity in the present context. AI approaches exhibit the ability to learn from patterns, tolerate faults by handling noisy data, and manage non-linear problems. Once trained, they excel in generalization and fast estimation. This survey presents a comprehensive review of AI algorithms developed for investigating nanoﬂuid-related issues. In nanoﬂuid research, the most commonly used neural network model is Multilayer perceptron neural network (MLP), while the Radial Basis Function Neural Network (RBF-ANN) is the preferred training method. the Generalized Regression Neural Networks (GRNNs) exhibit a simple structure that reduces learning time, making them particularly suitable for nanoﬂuids modelling. Consequently, for nanoﬂuids with a large number of samples, the use of RBF-ANN is recommended. The findings demonstrate the substantial potential of ANN methods as predictive and optimization tools for nanoﬂuids. This paper highlights the recent researches done for evaluating thermo-physical properties of nanofluids using AI algorithms.","PeriodicalId":48765,"journal":{"name":"3 Biotech","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77870398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine Learning Techniques in Agriculture 农业中的机器学习技术

IF 2.8 4区生物学

3 Biotech Pub Date : 2023-09-01 DOI: 10.46632//jdaai/2/3/5

M. Menaha, J. Lavanya

引用次数: 0

Identification of Changing Personnel with Double-Layer Network Fusion and Bi-Level Monitoring Mechanism 基于双层网络融合和双层监控机制的人员变动识别

IF 2.8 4区生物学

3 Biotech Pub Date : 2023-09-01 DOI: 10.46632/jdaai/2/3/3

Meena S. Gomathi, S. Dharani, R. Manikandan, Jeshrak Sam. V.

{"title":"Identification of Changing Personnel with Double-Layer Network Fusion and Bi-Level Monitoring Mechanism","authors":"Meena S. Gomathi, S. Dharani, R. Manikandan, Jeshrak Sam. V.","doi":"10.46632/jdaai/2/3/3","DOIUrl":"https://doi.org/10.46632/jdaai/2/3/3","url":null,"abstract":"Person re-identification (Re-ID) is an essential part of visual surveillance that aims to identify and locate persons from multiple network cameras without conflicting viewpoints. Although significant advances have been made in recent years with the use of deep learning, there are still many challenges in vision such as occlusion, exposure, background clutter, misalignment, scale, perspective, low resolution and illumination, and cross-camera methods. Dressing redefinition is a hot topic in education right now. Most existing methods assume that people's clothes do not change in a short time, but they do not apply when people change clothes. Accordingly, this article introduces a double-layer garment changer re-identification network that integrates the secondary care process through clustering and fine-grained knowledge in space and training the garment classification branch to increase the sensitivity of the network to garment characteristics. In this method, auxiliary equipment such as human bone is not used and the complexity of the model is greatly reduced compared to other methods. This article runs experiments on the famous redefined PRCC data and large-scale long-term dataset (LaST). Experimental results show that the method in this article is superior to existing methods.","PeriodicalId":48765,"journal":{"name":"3 Biotech","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80327813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Assessment on The Manufacturing Environment Using the Grey Relational Analysis Method 基于灰色关联分析法的制造环境评价

IF 2.8 4区生物学

3 Biotech Pub Date : 2023-09-01 DOI: 10.46632/jemm/9/3/1

引用次数: 2

Computer Vision Driven Precision Dairy Farming for Efficient Cattle Management 计算机视觉驱动的精准奶牛养殖，实现高效的奶牛管理

IF 2.8 4区生物学

3 Biotech Pub Date : 2023-09-01 DOI: 10.46632/jdaai/2/3/9

M. Kumari, Som veer, RR Deshmukh, RV Vinchurkar, PL Parameswari

{"title":"Computer Vision Driven Precision Dairy Farming for Efficient Cattle Management","authors":"M. Kumari, Som veer, RR Deshmukh, RV Vinchurkar, PL Parameswari","doi":"10.46632/jdaai/2/3/9","DOIUrl":"https://doi.org/10.46632/jdaai/2/3/9","url":null,"abstract":"Precision Dairy Farming (PDF)” or “The Per Animal Approach” can be enhanced through the implementation of three-dimensional computer vision, which offers improved cattle identification, disease monitoring, and growth assessment. The integration of 3D vision systems is particularly vital for advancing dairy farming practices in the next generation. These systems facilitate the automation of various animal husbandry tasks, including monitoring, herding, feeding, milking, and bedding of animals. The applications of 3D computer vision in PLF encompass diverse platforms, such as 3D camera installations for monitoring cow walking postures, and intelligent systems that interact safely with animals, capable of identifying dairy cattle and detecting health indicators like animal identification, recognition, body condition score, and lameness. To be effective, systems must be adaptable to unconstrained environments, varying herd characteristics, weather conditions, farmyard layouts, and animal-machine interaction scenarios. Considering these requirements, this paper proposes the application of emerging computer vision and artificial intelligence techniques in dairy farming. This review encourages future research in three-dimensional computer vision for cattle growth management and its potential extension to other livestock and wild animals","PeriodicalId":48765,"journal":{"name":"3 Biotech","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87342615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Promoting Green Supply Chain Management With Optimal Selection Of Packaging Materials Using Integrated Fuzzy MCDM and Rl Model 基于模糊MCDM和Rl模型的包装材料优化选择促进绿色供应链管理

IF 2.8 4区生物学

3 Biotech Pub Date : 2023-09-01 DOI: 10.46632/ese/2/3/1

{"title":"Promoting Green Supply Chain Management With Optimal Selection Of Packaging Materials Using Integrated Fuzzy MCDM and Rl Model","authors":"","doi":"10.46632/ese/2/3/1","DOIUrl":"https://doi.org/10.46632/ese/2/3/1","url":null,"abstract":"Green supply chain management is highly significant to maintain environmental sustainability. The agglomeration of green components enhances and supports the business activities to practice green supply chain more effectively. Utilizing sustainable packaging materials in logistics is a step towards promoting business eco sustainability. This research work attempts to develop a hybrid decision making model by integrating techniques of fuzzy multi criteria decision making (MCDM) and Reinforcement Learning (RL). This research work proposes a decision-making method of IDOCRIW (Integrated Determination of Objective Criteria Weights) under fuzzy environment with linguistic representations to determine the criterion weights of material selection and applies the RL method of Q learning in ranking the packaging materials for promoting green sustainability. The proposed fuzzy based MCDM method resolves the problems of conflict of uncertainty. The ranking results obtained using this method are compared with the non-integrated MCDM method. The proposed combined model shall be discussed under various other extended fuzzy representations. The decision-making problem on optimal selection of packaging materials addressed in this research work benefits the business decision makers to make right choices. This hybrid model will certainly make the logistic environment more robust and also it will upscale the smart framework of supply chain management.","PeriodicalId":48765,"journal":{"name":"3 Biotech","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89621586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Smart Neuro-Centric Approach to Predict Heart Attacks for Child Using IOT 使用物联网预测儿童心脏病发作的智能神经中心方法

IF 2.8 4区生物学

3 Biotech Pub Date : 2023-09-01 DOI: 10.46632/jdaai/2/3/4

K. Sai

引用次数: 0

A Survey of Bigdata Analysis, Extracting Data and Mapping the Data 大数据分析、数据提取与数据映射研究综述

IF 2.8 4区生物学

3 Biotech Pub Date : 2023-09-01 DOI: 10.46632/jdaai/2/3/6

P. Hemalatha, J. Lavanya

{"title":"A Survey of Bigdata Analysis, Extracting Data and Mapping the Data","authors":"P. Hemalatha, J. Lavanya","doi":"10.46632/jdaai/2/3/6","DOIUrl":"https://doi.org/10.46632/jdaai/2/3/6","url":null,"abstract":"Data mapping is one of the simplest terms is to map source data fields and their related target data fields. Mapping can have a varying degree of complexity, depending on the number, data types, schema, primary keys, and foreign keys of the data sources. Nowadays, Archaeological research is based on an interdisciplinary approach which makes use of a wide range of technologies allowing for the collection of data and information about sites and archaeological findings. The purpose of archaeology is to learn more about past societies and the development of the human race. An essential part of the archaeological data is related to spatial information that links historical contents to the metric reconstruction of monuments and artifacts, and show their mutual relations in a map. A critical a part of the archaeological records is associated with spatial data that links ancient contents to the metric reconstruction. By processing a steady stream of all real-time data, organizations can make time-sensitive decisions faster than ever before, monitor emerging trends, course-correct rapidly and jump on new business opportunities. To design a data mapping framework process, the data from various sources uses a new proposed technique. To secure the high profile raw and analyzed data using the combination of hardware and software any key generation for data extraction and mapping. The information can be accessed only through the authenticated source of the framework and hence duplication and data theft is extremely difficult. This paper follows the various data mapping techniques handled in previous work and also shows the limitations of existing techniques.","PeriodicalId":48765,"journal":{"name":"3 Biotech","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88440791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Review on Material Selection for Small Wind Turbine Blades Using the WASPAS Method 基于WASPAS方法的小型风力发电机叶片材料选择研究进展

IF 2.8 4区生物学

3 Biotech Pub Date : 2023-09-01 DOI: 10.46632/jame/2/3/1

引用次数: 0

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