Pub Date : 2020-08-03DOI: 10.24843/ijeet.2020.v05.i01.p09
M. Suarda, I. W. Kusuma, M. Sucipta, A. Ghurri
Four shaped models of delivery valve had been investigated and compared to improve performance of a hydraulic ram. Hydraulic ram pumps have been constructed and operated. Most of them built locally using steel pipe fittings that commercially accessible in the market rather than factory-made one. These have assisted inhabitants in rural or hilly area where water sources available for water supply services or irrigations. However, the major problem challenged by the public was on designing and repairing of the impulse and delivery valves of the pumps. Performance of the pumps are affected predominantly by the both valves. One characteristic of the valves is their shape. Considered on the characteristics of the fluid flow through surface of plate and sphere object are different on the pattern and losses. Therefore, investigation is necessitated to find a proper shape of the delivery valve for enhancing the performance of the pump. In this research four valve models were experimented to assess the hydraulic ram pump performance on varies delivery heads. The results show that the sphere model of the delivery valve offered the best efficiency, then followed by the membrane, the half-sphere and the flat delivery valve models. However, the rounded model: sphere and half-sphere delivery valve model were facing obstructions in implementation for a high delivery head.
{"title":"Preliminary Study on Various Shaped Models of Delivery valve in Hydraulic Ram Pump – Experimental Results","authors":"M. Suarda, I. W. Kusuma, M. Sucipta, A. Ghurri","doi":"10.24843/ijeet.2020.v05.i01.p09","DOIUrl":"https://doi.org/10.24843/ijeet.2020.v05.i01.p09","url":null,"abstract":"Four shaped models of delivery valve had been investigated and compared to improve performance of a hydraulic ram. Hydraulic ram pumps have been constructed and operated. Most of them built locally using steel pipe fittings that commercially accessible in the market rather than factory-made one. These have assisted inhabitants in rural or hilly area where water sources available for water supply services or irrigations. However, the major problem challenged by the public was on designing and repairing of the impulse and delivery valves of the pumps. Performance of the pumps are affected predominantly by the both valves. One characteristic of the valves is their shape. Considered on the characteristics of the fluid flow through surface of plate and sphere object are different on the pattern and losses. Therefore, investigation is necessitated to find a proper shape of the delivery valve for enhancing the performance of the pump. In this research four valve models were experimented to assess the hydraulic ram pump performance on varies delivery heads. The results show that the sphere model of the delivery valve offered the best efficiency, then followed by the membrane, the half-sphere and the flat delivery valve models. However, the rounded model: sphere and half-sphere delivery valve model were facing obstructions in implementation for a high delivery head.","PeriodicalId":365777,"journal":{"name":"International Journal of Engineering and Emerging Technology","volume":"16 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129502108","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}
Pub Date : 2020-07-27DOI: 10.24843/ijeet.2020.v05.i01.p04
I. Indriyani, M. I. A. Putera
A database can consist of numerical and non-numerical attributes. However, several data processing algorithms, such as K-means clustering, can be used only in a dataset with numerical attributes. Data generalization by using Naïve Bayes and K-means clustering methods is usually employed WEKA (Waikato environment for knowledge analysis) application. Although the strength of WEKA lies in increasingly complete and sophisticated algorithms, the success of data mining still lies in the knowledge factor of the human implementer. The task of collecting high-quality data and knowledge of modeling and the use of appropriate algorithms is needed to guarantee the accuracy of the expected formulations. In this paper, we propose a simple web-based application that can be used like WEKA. The methodology used in this study includes several stages. The first stage is the preparation of data, which is the tic-tac-toe game dataset that is converted to CSV (comma-separated values) format. The next stage is the process of modifying data from non-numeric to numeric, specifically for clustering with the K-means algorithm. Afterward, the calculation of the distance between data is conducted and followed by data clustering. The final stage is the summary of these processes and results. From the experimental results, it was found that clustering can be done on categorical attributes that are transformed first into the numerical form using web-based applications.
数据库可以由数值属性和非数值属性组成。然而，一些数据处理算法，如K-means聚类，只能用于具有数值属性的数据集。使用Naïve贝叶斯和K-means聚类方法进行数据泛化，通常采用WEKA (Waikato environment for knowledge analysis)应用。尽管WEKA的优势在于算法越来越完备和复杂，但数据挖掘的成功仍然取决于人类实现者的知识因素。需要收集高质量的数据和建模知识，并使用适当的算法，以保证预期公式的准确性。在本文中，我们提出了一个简单的基于web的应用程序，可以像WEKA一样使用。本研究中使用的方法包括几个阶段。第一个阶段是准备数据，即转换为CSV(逗号分隔值)格式的井字游戏数据集。下一阶段是将数据从非数值修改为数值的过程，特别是使用K-means算法进行聚类。然后计算数据之间的距离，然后进行数据聚类。最后一个阶段是对这些过程和结果的总结。实验结果表明，使用基于web的应用程序将分类属性转换为数值形式后，可以对分类属性进行聚类。
{"title":"Web-based Application for Classification Using Naïve Bayes and K-means Clustering (Case Study: Tic-tac-toe Game)","authors":"I. Indriyani, M. I. A. Putera","doi":"10.24843/ijeet.2020.v05.i01.p04","DOIUrl":"https://doi.org/10.24843/ijeet.2020.v05.i01.p04","url":null,"abstract":"A database can consist of numerical and non-numerical attributes. However, several data processing algorithms, such as K-means clustering, can be used only in a dataset with numerical attributes. Data generalization by using Naïve Bayes and K-means clustering methods is usually employed WEKA (Waikato environment for knowledge analysis) application. Although the strength of WEKA lies in increasingly complete and sophisticated algorithms, the success of data mining still lies in the knowledge factor of the human implementer. The task of collecting high-quality data and knowledge of modeling and the use of appropriate algorithms is needed to guarantee the accuracy of the expected formulations. In this paper, we propose a simple web-based application that can be used like WEKA. The methodology used in this study includes several stages. The first stage is the preparation of data, which is the tic-tac-toe game dataset that is converted to CSV (comma-separated values) format. The next stage is the process of modifying data from non-numeric to numeric, specifically for clustering with the K-means algorithm. Afterward, the calculation of the distance between data is conducted and followed by data clustering. The final stage is the summary of these processes and results. From the experimental results, it was found that clustering can be done on categorical attributes that are transformed first into the numerical form using web-based applications.","PeriodicalId":365777,"journal":{"name":"International Journal of Engineering and Emerging Technology","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125706678","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}
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