Pub Date : 2018-10-01DOI: 10.1109/EECSI.2018.8752951
Andarining Palupi, A. A. Pramudita, D. Arseno, A. D. Setiawan
In several field such as structure health monitoring, landslide monitoring and medical measurement, small displacement is used as the indicator of any problem that may rise in such fields. High resolution radar system is required for small displacement detection in millimeter of centimeter scale. Continuous wave (CW) radar with its narrow bandwidth feature, has a simpler system comparing with other radar system. However, the modification is needed to present the ability of CW radar in detecting small displacement. In this paper, dual frequency CW radar was investigated and proposed for small displacement detection. Computer simulation has been conducted to study the capability of the proposed radar system. The result shows that the dual frequency CW radar at 10.525 GHz is capable to detect a small displacement in millimeter scale. The frequency difference of the radar signal needs to be adjusted to avoid the ambiguity in the detection result.
{"title":"Dual Frequency Continuous Wave Radar for Small Displacement Detection","authors":"Andarining Palupi, A. A. Pramudita, D. Arseno, A. D. Setiawan","doi":"10.1109/EECSI.2018.8752951","DOIUrl":"https://doi.org/10.1109/EECSI.2018.8752951","url":null,"abstract":"In several field such as structure health monitoring, landslide monitoring and medical measurement, small displacement is used as the indicator of any problem that may rise in such fields. High resolution radar system is required for small displacement detection in millimeter of centimeter scale. Continuous wave (CW) radar with its narrow bandwidth feature, has a simpler system comparing with other radar system. However, the modification is needed to present the ability of CW radar in detecting small displacement. In this paper, dual frequency CW radar was investigated and proposed for small displacement detection. Computer simulation has been conducted to study the capability of the proposed radar system. The result shows that the dual frequency CW radar at 10.525 GHz is capable to detect a small displacement in millimeter scale. The frequency difference of the radar signal needs to be adjusted to avoid the ambiguity in the detection result.","PeriodicalId":6543,"journal":{"name":"2018 5th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"1 1","pages":"576-579"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90412169","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 : 2018-10-01DOI: 10.1109/EECSI.2018.8752630
Arsyad Cahya Subrata, T. Sutikno, A. Z. Jidin, A. Jidin
Adjustable Speed Drive (ASD) fed Matrix Converter is an interesting topic and is widely discussed in several articles. ASD provides many advantages, especially in the industrial sector because it increases work efficiency so as to reduce production costs. The induction machines construction is sturdy and its relatively inexpensive maintenance makes it more desirable in industrial process applications. Whereas the Matrix Converter (MC) construction without dc-link capacitors makes it more compact compared to conventional converters. This article discussed the ASD control modulation technique by using MC on a three-phase induction motor.
{"title":"Review on Adjustable Speed Drive Techniques of Matrix Converter Fed Three-Phase Induction Machine","authors":"Arsyad Cahya Subrata, T. Sutikno, A. Z. Jidin, A. Jidin","doi":"10.1109/EECSI.2018.8752630","DOIUrl":"https://doi.org/10.1109/EECSI.2018.8752630","url":null,"abstract":"Adjustable Speed Drive (ASD) fed Matrix Converter is an interesting topic and is widely discussed in several articles. ASD provides many advantages, especially in the industrial sector because it increases work efficiency so as to reduce production costs. The induction machines construction is sturdy and its relatively inexpensive maintenance makes it more desirable in industrial process applications. Whereas the Matrix Converter (MC) construction without dc-link capacitors makes it more compact compared to conventional converters. This article discussed the ASD control modulation technique by using MC on a three-phase induction motor.","PeriodicalId":6543,"journal":{"name":"2018 5th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"13 1","pages":"350-355"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79678586","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}
One solution for interoperability issue in IoT is a middleware which is competent on resolving the problems of syntactical, semantic, and network interoperability. In previous study, a middleware capable of addressing semantic and syntactical interoperability challenges has been developed, yet has not responded to network interoperability matter. In this paper we continue our previous research by adding BLE and 6LoWPAN features to the middleware's communication media, so it may communicate with various devices. Interoperability test results show that the middleware is capable of responding to network interoperability challenges and able to receive data from multiple nodes simultaneously.
{"title":"Middleware for Network Interoperability in IoT","authors":"Eko Sakti Pramukantoro, Fariz Andri Bakhtiar, Binariyanto Aji, Rasidy Pratama","doi":"10.1109/EECSI.2018.8752917","DOIUrl":"https://doi.org/10.1109/EECSI.2018.8752917","url":null,"abstract":"One solution for interoperability issue in IoT is a middleware which is competent on resolving the problems of syntactical, semantic, and network interoperability. In previous study, a middleware capable of addressing semantic and syntactical interoperability challenges has been developed, yet has not responded to network interoperability matter. In this paper we continue our previous research by adding BLE and 6LoWPAN features to the middleware's communication media, so it may communicate with various devices. Interoperability test results show that the middleware is capable of responding to network interoperability challenges and able to receive data from multiple nodes simultaneously.","PeriodicalId":6543,"journal":{"name":"2018 5th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"1 1","pages":"499-502"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89513204","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 : 2018-10-01DOI: 10.1109/EECSI.2018.8752637
Samuel Cahyawijaya, Bryan Wilie, W. Adiprawita
In crowd counting task, our goals are to estimate density map and count of people from the given crowd image. From our analysis, there are two major problems that need to be solved in the crowd counting task, which are scale invariant problem and inhomogeneous density problem. Many methods have been developed to tackle these problems by designing a dense aware model, scale adaptive model, etc. Our approach is derived from scale invariant problem and inhomogeneous density problem and we propose a dense aware inception based neural network in order to tackle both problems. We introduce our novel inception based crowd counting model called Inception Dense Estimator network (IDEnet). Our IDEnet is divided into 2 modules, which are Inception Dense Block (IDB) and Dense Evaluator Unit (DEU). Some variations of IDEnet are evaluated and analysed in order to find out the best model. We evaluate our best model on UCF50 and ShanghaiTech dataset. Our IDEnet outperforms the current state-of-the-art method in ShanghaiTech part B dataset. We conclude our work with 6 key conclusions based on our experiments and error analysis.
在人群计数任务中，我们的目标是从给定的人群图像中估计密度图和人数。从我们的分析来看，在人群计数任务中需要解决两个主要问题，即规模不变问题和非均匀密度问题。为了解决这些问题，人们开发了许多方法，如设计密集感知模型、比例自适应模型等。我们的方法来源于尺度不变问题和非均匀密度问题，我们提出了一个基于密集感知初始的神经网络来解决这两个问题。我们介绍了一种新的基于初始的人群计数模型，称为初始密集估计网络(ideet)。我们的idet分为2个模块，即Inception Dense Block (IDB)和Dense Evaluator Unit (DEU)。为了找出最好的模型，对不同的模型进行了评价和分析。我们在UCF50和ShanghaiTech数据集上评估了我们的最佳模型。我们的识别网络在上海科技B部分数据集中优于当前最先进的方法。基于实验和误差分析，我们得出了6个关键结论。
{"title":"IDEnet : Inception-Based Deep Convolutional Neural Network for Crowd Counting Estimation","authors":"Samuel Cahyawijaya, Bryan Wilie, W. Adiprawita","doi":"10.1109/EECSI.2018.8752637","DOIUrl":"https://doi.org/10.1109/EECSI.2018.8752637","url":null,"abstract":"In crowd counting task, our goals are to estimate density map and count of people from the given crowd image. From our analysis, there are two major problems that need to be solved in the crowd counting task, which are scale invariant problem and inhomogeneous density problem. Many methods have been developed to tackle these problems by designing a dense aware model, scale adaptive model, etc. Our approach is derived from scale invariant problem and inhomogeneous density problem and we propose a dense aware inception based neural network in order to tackle both problems. We introduce our novel inception based crowd counting model called Inception Dense Estimator network (IDEnet). Our IDEnet is divided into 2 modules, which are Inception Dense Block (IDB) and Dense Evaluator Unit (DEU). Some variations of IDEnet are evaluated and analysed in order to find out the best model. We evaluate our best model on UCF50 and ShanghaiTech dataset. Our IDEnet outperforms the current state-of-the-art method in ShanghaiTech part B dataset. We conclude our work with 6 key conclusions based on our experiments and error analysis.","PeriodicalId":6543,"journal":{"name":"2018 5th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"70 1","pages":"548-553"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89367043","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 : 2018-10-01DOI: 10.1109/EECSI.2018.8752625
Lailatul Husniah, R. Mahendra, Ali Sofyan Kholimi, E. Cahyono
The pathfinding algorithms have commonly used in video games. City 2.5 is an isometric grid-less game which already implements pathfinding algorithms. However, current pathfinding algorithm unable to produce optimal route when it comes to custom shape or concave collider. This research uses A* and a method to choose the start and end node to produce an optimal route. The virtual grid node is generated to make A* works on the grid-less environment. The test results show that A* be able to produce the shortest route in concave or custom obstacles scenarios, but not on the obstacle-less scenarios and tight gap obstacles scenarios.
{"title":"Comparison Between A* And Obstacle Tracing Pathfinding In Gridless Isometric Game","authors":"Lailatul Husniah, R. Mahendra, Ali Sofyan Kholimi, E. Cahyono","doi":"10.1109/EECSI.2018.8752625","DOIUrl":"https://doi.org/10.1109/EECSI.2018.8752625","url":null,"abstract":"The pathfinding algorithms have commonly used in video games. City 2.5 is an isometric grid-less game which already implements pathfinding algorithms. However, current pathfinding algorithm unable to produce optimal route when it comes to custom shape or concave collider. This research uses A* and a method to choose the start and end node to produce an optimal route. The virtual grid node is generated to make A* works on the grid-less environment. The test results show that A* be able to produce the shortest route in concave or custom obstacles scenarios, but not on the obstacle-less scenarios and tight gap obstacles scenarios.","PeriodicalId":6543,"journal":{"name":"2018 5th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"67 1","pages":"489-494"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76518577","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 : 2018-10-01DOI: 10.1109/EECSI.2018.8752898
Luh Putu Ayu Prapitasari, Parth Rawal, R. Grigat
The concept of building 3D models, known as 3D reconstruction, already exists since the last few decades. However, by manually aligning the objects during acquisition phase does not guarantee that the output, the 3D models, will be perfectly aligned with the computer’s world coordinate system. It mainly happens because in real world it is quite challenging to get perfect measurements, especially for the irregular objects. In this paper we address this problem by proposing a method to be used on the post processing phase of the 3D reconstruction process. The method is based on the variance and symmetricity of the object’s point cloud which is acquired during acquisition. For the evaluation, we applied and evaluated the proposed method to both synthetic and reconstructed 3D models. The results are significant and show that the method capable of aligning the models to a fine resolution of 1' (one minute) angle.
{"title":"Variance and Symmetrical-based Approach for Optimal Alignment of 3D Model","authors":"Luh Putu Ayu Prapitasari, Parth Rawal, R. Grigat","doi":"10.1109/EECSI.2018.8752898","DOIUrl":"https://doi.org/10.1109/EECSI.2018.8752898","url":null,"abstract":"The concept of building 3D models, known as 3D reconstruction, already exists since the last few decades. However, by manually aligning the objects during acquisition phase does not guarantee that the output, the 3D models, will be perfectly aligned with the computer’s world coordinate system. It mainly happens because in real world it is quite challenging to get perfect measurements, especially for the irregular objects. In this paper we address this problem by proposing a method to be used on the post processing phase of the 3D reconstruction process. The method is based on the variance and symmetricity of the object’s point cloud which is acquired during acquisition. For the evaluation, we applied and evaluated the proposed method to both synthetic and reconstructed 3D models. The results are significant and show that the method capable of aligning the models to a fine resolution of 1' (one minute) angle.","PeriodicalId":6543,"journal":{"name":"2018 5th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"20 1","pages":"753-758"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73089890","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 : 2018-10-01DOI: 10.1109/EECSI.2018.8752726
Ahmad Zoebad Foeady, D. C. R. Novitasari, Ahmad Hanif Asyhar, Muhammad Firmansjah
Diabetic Retinopathy (DR) is the cause of blindness. Early identification needed for prevent the DR. However, High hospital cost for eye examination makes many patients allow the DR to spread and lead to blindness. This study identifies DR patients by using color fundus image with SVM classification method. The purpose of this study is to minimize the funds spent or can also be a breakthrough for people with DR who lack the funds for diagnosis in the hospital. Pre-processing process have a several steps such as green channel extraction, histogram equalization, filtering, optic disk removal with structuring elements on morphological operation, and contrast enhancement. Feature extraction of preprocessing result using GLCM and the data taken consists of contrast, correlation, energy, and homogeneity. The detected components in this study are blood vessels, microaneurysms, and hemorrhages. This study results what the accuracy of classification using SVM and feature from GLCM method is 82.35% for normal eye and DR, 100% for NPDR and PDR. So, this program can be used for diagnosing DR accurately.
{"title":"Automated Diagnosis System of Diabetic Retinopathy Using GLCM Method and SVM Classifier","authors":"Ahmad Zoebad Foeady, D. C. R. Novitasari, Ahmad Hanif Asyhar, Muhammad Firmansjah","doi":"10.1109/EECSI.2018.8752726","DOIUrl":"https://doi.org/10.1109/EECSI.2018.8752726","url":null,"abstract":"Diabetic Retinopathy (DR) is the cause of blindness. Early identification needed for prevent the DR. However, High hospital cost for eye examination makes many patients allow the DR to spread and lead to blindness. This study identifies DR patients by using color fundus image with SVM classification method. The purpose of this study is to minimize the funds spent or can also be a breakthrough for people with DR who lack the funds for diagnosis in the hospital. Pre-processing process have a several steps such as green channel extraction, histogram equalization, filtering, optic disk removal with structuring elements on morphological operation, and contrast enhancement. Feature extraction of preprocessing result using GLCM and the data taken consists of contrast, correlation, energy, and homogeneity. The detected components in this study are blood vessels, microaneurysms, and hemorrhages. This study results what the accuracy of classification using SVM and feature from GLCM method is 82.35% for normal eye and DR, 100% for NPDR and PDR. So, this program can be used for diagnosing DR accurately.","PeriodicalId":6543,"journal":{"name":"2018 5th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"12 1","pages":"154-160"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74366186","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 : 2018-10-01DOI: 10.1109/EECSI.2018.8752769
M. O. Pratama, W. Satyawan, Bagus Fajar, Rusnandi Fikri, Haris Hamzah
Indonesian ID Card can be used to recognize citizen of Indonesia identity in several requirements like for sales and purchasing recording, admission and other transaction processing systems (TPS). Current TPS system used citizen ID Card by entering the data manually that means time consuming, prone to error and not efficient. In this research, we propose a model of citizen id card detection using state-of-the-art Deep Learning models: Convolutional Neural Networks (CNN). The result, we can obtain possitive accuracy citizen id card recognition using deep learning. We also compare the result of CNN with traditional computer vision techniques.
{"title":"Indonesian ID Card Recognition using Convolutional Neural Networks","authors":"M. O. Pratama, W. Satyawan, Bagus Fajar, Rusnandi Fikri, Haris Hamzah","doi":"10.1109/EECSI.2018.8752769","DOIUrl":"https://doi.org/10.1109/EECSI.2018.8752769","url":null,"abstract":"Indonesian ID Card can be used to recognize citizen of Indonesia identity in several requirements like for sales and purchasing recording, admission and other transaction processing systems (TPS). Current TPS system used citizen ID Card by entering the data manually that means time consuming, prone to error and not efficient. In this research, we propose a model of citizen id card detection using state-of-the-art Deep Learning models: Convolutional Neural Networks (CNN). The result, we can obtain possitive accuracy citizen id card recognition using deep learning. We also compare the result of CNN with traditional computer vision techniques.","PeriodicalId":6543,"journal":{"name":"2018 5th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"140 1","pages":"178-181"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76693921","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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