Evergreen最新文献_第4页

Geothermal Direct Use for Silkworm Cultivation as a CSR Program in Wayang Windu Geothermal Field: Thermal Energy Calculation Approach 大阳温都地热田直接利用地热养蚕作为企业社会责任项目:热能计算方法

Evergreen Pub Date : 2023-09-01 DOI: 10.5109/7151689

None Suyanto, Lina Agustina, Andri Subandriya, None Ifanda, Nuraida Tarigan

引用次数: 0

Development and Mechanical Properties Evaluation of Basalt-Glass Hybrid Composites 玄武岩-玻璃杂化复合材料的研究进展及力学性能评价

Evergreen Pub Date : 2023-09-01 DOI: 10.5109/7151681

Bindu. S, None M. Prasanna Kumar, None Vinay K M

引用次数: 0

Analysis of Circular Economy Enablers in Manufacturing Context for Indian Industries: A ELECTRE method Ranking Process 印度工业制造环境下循环经济驱动因素分析:基于ELECTRE方法的排名过程

Evergreen Pub Date : 2023-09-01 DOI: 10.5109/7148437

Manoj Sharma, None Narayan Lal Jain, None Jayant Kishor Purohit

{"title":"Analysis of Circular Economy Enablers in Manufacturing Context for Indian Industries: A ELECTRE method Ranking Process","authors":"Manoj Sharma, None Narayan Lal Jain, None Jayant Kishor Purohit","doi":"10.5109/7148437","DOIUrl":"https://doi.org/10.5109/7148437","url":null,"abstract":": In the era circular economy, a nation's ability to sustainably grow its manufacturing sector is crucial for overall economic development. Therefore, in order to make the industrial sector sustainable and competitive, technologies must be developed with the circular economy in mind. The bulk of manufacturing companies in India fall under the category of small and medium-sized enterprises, which are acknowledged as the foundation of the economy since they generate a sizable portion of the country's GDP. The foundation of modern civilization's economy is the manufacturing sector. This paper attempts to re-examine the idea of a manufacturing-based circular economy system through a review of the scientific literature. In the context of Indian industries, the study pinpointed enablers that support the implementation of the circular economy. These enablers were categorized into six clusters. A survey questionnaire was formulated and the collected data was scrutinized to confirm the validity of these supporting factors. The majority of the manufacturing industries in India fall under the category of small and medium enterprises. A survey questionnaire was sent to the respondents through email, and personal visits were made to nearby industries. Cronbach's alpha count is used to evaluate the validity of important enablers. An expert panel of manufacturing industry managers and technical personnel validates these enablers as affecting how developing countries adopt CE, assigns weights to the enablers, and uses the ELECTRE Method to determine the final ranking of the enablers. The findings imply that technical (ETE) and financial (EFI) enablers are the main enablers for adopting the circular economy within India's industrial sectors. Through this study, the industries are better equipped to comprehend the enablers to the circular economy and develop practical implementation plans.","PeriodicalId":12085,"journal":{"name":"Evergreen","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135690150","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

Cost-effective Synthesis of CeO_2-SiO_2 Based on Oil Palm Leaves for the Removal of Toxic Compounds 基于油棕叶高效合成CeO_2-SiO_2去除有毒化合物

Evergreen Pub Date : 2023-09-01 DOI: 10.5109/7151676

None Salprima Yudha S, Charles Banon, Reza Pertiwi, None Deni Agus Triawan, None Jeong In Han

引用次数: 0

Texture-Based Classification of Benign and Malignant Mammography Images using Weka Machine Learning: An Optimal Approach 使用Weka机器学习的基于纹理的良性和恶性乳房x线摄影图像分类:一种最佳方法

Evergreen Pub Date : 2023-09-01 DOI: 10.5109/7151705

Heni Sumarti, None Sheilla Rully Anggita, None Hartono, None Fachrizal Rian Pratama, None Alvania Nabila Tasyakuranti

{"title":"Texture-Based Classification of Benign and Malignant Mammography Images using Weka Machine Learning: An Optimal Approach","authors":"Heni Sumarti, None Sheilla Rully Anggita, None Hartono, None Fachrizal Rian Pratama, None Alvania Nabila Tasyakuranti","doi":"10.5109/7151705","DOIUrl":"https://doi.org/10.5109/7151705","url":null,"abstract":": Breast cancer is the most common cancer in Indonesia. One way to detect it early is by screening using mammography. Previous trials showed that mammography screening in women aged 40-49 years could reduce breast cancer mortality by 25%. However, misdiagnosis may occur abaout breast density and the patient’s physical size due to machines. In addition, human reader errors can occur concerning the reader's experience and perception. Therefore, diagnostic aids are needed to distinguish benign and malignant cases and receive appropriate treatment. The methodology in this research consists of three stages: preprocessing, texture feature extraction, and data classification. Preprocessing consists of filtering, contrast, cropping, and resizing, while texture feature extraction consist of Histogram and (Gray Level Co-occurrence Matrix) GLCM. Data classification using Support Vector Machines (SVM), Naive Bayes, Multi-Layer Perceptron (MLP), Multiclass classifier, and Random Forest methods with Weka Machine Learning software. It produces an accuracy of 62.00%, 62.00%, 88.00%, 82.00%, and 100.00%, respectively. The results of data classification using the Random Forest method show that the accuracy, specifications, and specificity reach 100%. Random forest can be used as the most optimal classification method to distinguish benign and malignant cases based on texture features in mammography images using Weka Machine Learning software. This can help radiologists and medical professionals to diagnose cases and take further steps, such as therapy.","PeriodicalId":12085,"journal":{"name":"Evergreen","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135690524","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

Assessing Toughness of Pressurized Fluid Channel: Experiment using CTOD in Spiral Submerged Arc Welded Pipes 加压流体通道韧性评估:螺旋埋弧焊管CTOD试验

Evergreen Pub Date : 2023-09-01 DOI: 10.5109/7151771

None Hermawan Agus Suhartono, Yana Heryana, None Gilang Cempaka Kusuma

引用次数: 0

Influence of Lubrication on Vibration Response and Surface Roughness in Milling of Aluminum 6061 润滑对6061铝合金铣削振动响应和表面粗糙度的影响

Evergreen Pub Date : 2023-09-01 DOI: 10.5109/7151725

Amiruddin Aziz, Muizuddin Azka, None Nur Cholis Majid, None Mahfudz Al Huda, Agus Susanto, Khairul Jauhari, None Achmad Zaki Rahman, Ratna Nurmayni

{"title":"Influence of Lubrication on Vibration Response and Surface Roughness in Milling of Aluminum 6061","authors":"Amiruddin Aziz, Muizuddin Azka, None Nur Cholis Majid, None Mahfudz Al Huda, Agus Susanto, Khairul Jauhari, None Achmad Zaki Rahman, Ratna Nurmayni","doi":"10.5109/7151725","DOIUrl":"https://doi.org/10.5109/7151725","url":null,"abstract":": Aluminum is used widely for components of renewable energy, such as wind and hydro turbines. Some of these components require a milling process to improve surface quality. This research presented the influence of lubrication on vibration and surface roughness in the milling process. The first step, the modal parameters data were obtained by the impulse response method using a hammering test with an impulse hammer, then the milling tests experiment were conducted in three different cutting conditions i.e. dry cutting, wet cutting with coolant and oil. The three-axis accelerometer was used to collect acceleration signals of milling test. The collected acceleration signals then were analyzed using Fast Fourier Transform (FFT) to first transform the signals into frequency domain and after that more phenomenon of the milling process in frequency domain were analyzed. Then, the surface roughness was measured using a surface roughness tester. The results showed that the amplitude of signal is lower in milling with lubricant than dry cutting. The cutting condition was stable in wet cutting for both types of lubricant while the chatter occurs in dry cutting. Then, the surface roughness for wet cutting is better than dry cutting and the best of roughness is wet cutting with lubricant of coolant in this experiment.","PeriodicalId":12085,"journal":{"name":"Evergreen","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135691587","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

Prediction of Tool Wear Using Machine Learning Approaches for Machining on Lathe Machine 用机器学习方法预测车床加工中的刀具磨损

Evergreen Pub Date : 2023-09-01 DOI: 10.5109/7151683

None Ashish Kumar Srivastava, None Bipin Kumar Singh, Supriya Gupta

{"title":"Prediction of Tool Wear Using Machine Learning Approaches for Machining on Lathe Machine","authors":"None Ashish Kumar Srivastava, None Bipin Kumar Singh, Supriya Gupta","doi":"10.5109/7151683","DOIUrl":"https://doi.org/10.5109/7151683","url":null,"abstract":": In manufacturing industries, removal of material from the workpiece is the prime processes that convert raw material into finished product. During removal processes the cutting tool are incessantly deteriorated in health, which can be stated as perks and drawbacks of process. The precision and roughness of the material are directly related to the condition of the tools during the machining process. Machining analysis depends on numerous of cutting conditions when it is being performed. The likelihood of wearing increases with repeated use. So, by implementing the proposed approach for tool wear prediction can improve the quality as well as reduce the machining time. However, to maintain the healthy tool's conditions for prolong time is a major challenge for the scientific community. Hence, as a component of industry 4.0, this study explored the possibilities to monitor the tool condition using the machine learning techniques. So, an endeavor has been made to present a solution of this problem without hampering the productivity losses in terms of time, material, and tool, consequences in high productivity. For the proposed work, machine learning techniques such as k-NN, Random forest, Adaboost, k-Star, and Decision Tree are implemented and there accuracy of prediction is demonstrated. Furthermore, WEKA, open source software has been used to employ several tool learning algorithms for better understanding. The investigation noticed that the random forest algorithm has a higher accuracy of 97.30% and a root mean square error value of 0.144 among all other algorithm.","PeriodicalId":12085,"journal":{"name":"Evergreen","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135690299","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

Multi Objective Scheduling of CHP based Microgrid Using Manta Ray Optimization Technique 基于蝠鲼优化技术的热电联产微网多目标调度

Evergreen Pub Date : 2023-09-01 DOI: 10.5109/7151691

Surmadhur Pant, Gaurav Bhandari

{"title":"Multi Objective Scheduling of CHP based Microgrid Using Manta Ray Optimization Technique","authors":"Surmadhur Pant, Gaurav Bhandari","doi":"10.5109/7151691","DOIUrl":"https://doi.org/10.5109/7151691","url":null,"abstract":": With the introduction of concept of sustainable development for different applications, combined heat and power system became very important due to reliability, economical aspects, saving in energy and saving of environment. Here a model is taken for economic load scheduling, CHP system with a micro grid fuel cell, wind energy, solar energy, heat boiler (waste heat), and loads which includes thermal and electrical. An optimal model with nonlinearity is taken which deals with the economical operating condition of all the power sources used and formulate the heat demand along with the electrical demand for one day (24 hours) forecasted values of all the types of power generating sources is taken in to consideration. Manta Ray foraging optimization technique is suggested for the optimization and compared with other techniques also. This Model is tested without peak valley pricing for different type of optimization algorithm. After comparing the results of different optimization method, it is clear that the result produced by MRFO are better than other method and the costing of the system is improved. From convergence graph, it can be seen that the MRFO technique demonstrates a faster convergence rate towards reaching the minimum cost of the objective function compared to other optimization techniques. As it iteratively progresses through the optimization process, MRFO efficiently approaches the optimal solution, which is the desired minimum cost. This efficiency translates to the technique requiring fewer iterations to achieve the desired outcome. Since MRFO achieves the desired outcome with fewer iterations, it reduces the overall computational workload and resource requirements compared to slower converging optimization methods.","PeriodicalId":12085,"journal":{"name":"Evergreen","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135690301","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

Design and Development of Novel Solar Concentrating Spittoon to Control the Spread of COVID-19 Virus at Public Places 新型太阳能聚光痰盂的设计与研制控制新型冠状病毒在公共场所的传播

Evergreen Pub Date : 2023-09-01 DOI: 10.5109/7151692

Abhimannyu Sharma, None Deepak Kumar Raj, Dheeraj Kumar, Amit Kumar, Anup Kumar, None Mithilesh Kumar Sahu

引用次数: 0