2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC)最新文献

Performance Improvement on 64-QAM Multicarrier with Closed-Loop Rotate Modulation 64-QAM多载波闭环旋转调制性能改进

2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC) Pub Date : 2018-12-01 DOI: 10.1109/ICCEREC.2018.8711996

Budi Prasetya, A. Kurniawan, Iskandar, Arfianto Fahmi

{"title":"Performance Improvement on 64-QAM Multicarrier with Closed-Loop Rotate Modulation","authors":"Budi Prasetya, A. Kurniawan, Iskandar, Arfianto Fahmi","doi":"10.1109/ICCEREC.2018.8711996","DOIUrl":"https://doi.org/10.1109/ICCEREC.2018.8711996","url":null,"abstract":"To improve performance in the 64-QAM multicarrier communication system, we propose a new method, closed-loop rotate modulation. The closed-loop process requires feedback channel information in the form of complex quantities that contain information on the gain and delay of the channel. Based on the purpose of distortionless transmission, we can get the equation in the closed-loop rotate modulation method on the multi-carrier system at the transmitter side. From the simulation results, with the application of closed-loop rotate modulation, the output signal of the multicarrier demodulator is exactly the same as the transmission signal. On the probability of error curve generated, the application of closed-loop rotate modulation can coincide with the system performance if only disturbed by the AWGN channel. Terms so that the algorithm can work optimally, the speed of updating feedback must be faster than changes in channel fluctuations and channel feedback works perfectly. The simulation results also show that although channel information feedback is not perfect, but still can produce a good performance, the more accurate channel feedback will result in a better probability of error. Another advantage of the scheme that we propose is that the transmission process of a multi-carrier system does not use guard intervals, so the efficiency of the data is maximized.","PeriodicalId":250054,"journal":{"name":"2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116911628","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

Apllication of Optimization Heavy Traffic Path with Floyd-Warshall Algorithm Floyd-Warshall算法在大流量路径优化中的应用

2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC) Pub Date : 2018-12-01 DOI: 10.1109/ICCEREC.2018.8712110

I. K. Laga Dwi Pandika, Budhi Irawan, C. Setianingsih

引用次数: 7

Lie Detector With Analysis Pupil Dilation And Eye Blinks Analysis Using Hough Transform And Decision Tree 利用Hough变换和决策树分析瞳孔扩张和眨眼的测谎仪

2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC) Pub Date : 2018-12-01 DOI: 10.1109/ICCEREC.2018.8712103

Taufiq Ari Wibowo, Muhammad Nasrun, C. Setianingsih

{"title":"Lie Detector With Analysis Pupil Dilation And Eye Blinks Analysis Using Hough Transform And Decision Tree","authors":"Taufiq Ari Wibowo, Muhammad Nasrun, C. Setianingsih","doi":"10.1109/ICCEREC.2018.8712103","DOIUrl":"https://doi.org/10.1109/ICCEREC.2018.8712103","url":null,"abstract":"In a social life, lying is a common and frequent thing among the community. Communication is one of the main ways to multiply relationships and build relationships in family, community, and the world of work. In the world of psychology, it can be detected using body parts such as; face, eyes, heartbeat and more. In this Final Project the compiler focus to work on the human eye. The lie detector uses the object of pupil diameter change and the number of blinking eyes with the Hough Transform method and the Decision Tree algorithm as the decision maker. From the results of research conducted on the lie detector system obtained an accuracy of 92%. Accuracy is obtained from observations on the change in pupillary diameter using hough circular transform method and increased the number of blinking eye with eye aspect ratio method. In research conducted, a person who lies pupil eyes will experience enlargement of the pupil diameter of the initial respondent and increased the number of blinks of the eye to more than 8 times from the initial blink of respondents before the question.","PeriodicalId":250054,"journal":{"name":"2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123940711","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: 3

Detection of Pterygium Disease Using Forward Chaining and Viola Jones Algorithm 利用前向链和Viola Jones算法检测翼状胬肉

2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC) Pub Date : 2018-12-01 DOI: 10.1109/ICCEREC.2018.8712102

Umu Hanifah, Purba Daru Kusuma, C. Setianingsih

{"title":"Detection of Pterygium Disease Using Forward Chaining and Viola Jones Algorithm","authors":"Umu Hanifah, Purba Daru Kusuma, C. Setianingsih","doi":"10.1109/ICCEREC.2018.8712102","DOIUrl":"https://doi.org/10.1109/ICCEREC.2018.8712102","url":null,"abstract":"Eyesight is one of the most important senses for human life. Because only with our eyes, we can see and know the situations and conditions that occur around us. If there are problems or disorders that happen in our eyes, then we will feel uncomfortable and there are several diseases that can reduce the quality of vision and can cause blindness. In this project the author will be make an application to detect Pterygium eye disease based on the early symptoms that have been felt by the patient and find out how severely the patient affected by Pterygium disease with different levels. The stages used to determine the level of Pterygium disease is by filling all the symptoms by the patient in the application using Forward Chaining method and using an image segmentation process with Viola Jones Algorithm. The results of using the Viola Jones algorithm that have been processed using this application have an accuracy rate of 76% by testing 50 images and the results of the images detected are 38 images, in addition there are some images that are not detected and there are some images that are not detected.","PeriodicalId":250054,"journal":{"name":"2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC)","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115810532","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: 6

Automatic Modulation Detection Using Non-Linear Transformation Data Extraction And Neural Network Classification 基于非线性变换数据提取和神经网络分类的自动调制检测

2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC) Pub Date : 2018-12-01 DOI: 10.1109/ICCEREC.2018.8712101

Hernawan Kurniansyah, H. Wijanto, F. Y. Suratman

{"title":"Automatic Modulation Detection Using Non-Linear Transformation Data Extraction And Neural Network Classification","authors":"Hernawan Kurniansyah, H. Wijanto, F. Y. Suratman","doi":"10.1109/ICCEREC.2018.8712101","DOIUrl":"https://doi.org/10.1109/ICCEREC.2018.8712101","url":null,"abstract":"Adaptive Modulation and Coding (AMC) is a system that performed adaptive modulation scheme in which sets of modulation used by the same system adapted to the conditions of the transmission channel. This research want to make an AMC system that can distinguish Amplitude Modulation (AM), Lower Sideband (LSB), Upper Sideband (USB), Binary Phase-shift Keying (BPSK), Quartenary Phase-shift Keying (QPSK), and 8-Phase-shift Keying (8PSK) modulation automatically. AMC has an important role in the military. Modern electronic warfare, called the Electronic Warfare (EW) consists of three main components, these are Electronic Support (ES), Electronic Attack (EA) and Electronic Protect (EP). In electronic support, the main purpose is to collect the information of the received radio signal, so the AMC system can be used for this. With the AMC system, the modulation type is known to do the demodulation process, so the overlapped information can be known. The feature extraction process is one of the most important processes in AMC System. In this research, feature extraction performed is a high-order statistical feature in the time domain. The statistical order used is order 4. Information signals are passed on the transmission channel in the presence of AWGN noise interference with variable signal quality of 0 dB to 40 dB. Artificial neural network algorithm is used to classify modulation with a learning rate of 0.5 and the maximum number of epochs is 1000. By using the 4th order statistical feature, the AMC system on this research can distinguish AM, LSB, USB, BPSK, QPSK, and 8PSK modulation. This research focus on modulation that is used in HF military radio. The accuracy rate of this system in performing modulation classification without using non-linear transformations is 65.5% on 10 dB signal quality. Then, the accuracy of AMC by using non-linear transformations on the received signal reaches 88.8% on the 10 dB signal quality.","PeriodicalId":250054,"journal":{"name":"2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128240539","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: 10

CAPIC: Cache based on Popularity and Class in Named Data Network 命名数据网络中基于流行度和类别的缓存

2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC) Pub Date : 2018-12-01 DOI: 10.1109/ICCEREC.2018.8712105

L. V. Yovita, N. Syambas, Ian Yosef Matheus Edward

{"title":"CAPIC: Cache based on Popularity and Class in Named Data Network","authors":"L. V. Yovita, N. Syambas, Ian Yosef Matheus Edward","doi":"10.1109/ICCEREC.2018.8712105","DOIUrl":"https://doi.org/10.1109/ICCEREC.2018.8712105","url":null,"abstract":"In the IP network, if there are many consumers who want the same data, the request and response process for data will be repeated and will increase the overall network load. Modifications have been made to IP networks, namely by Content Distribution Network which places a duplicate server in a place closer to the consumer. CDN managed to reduce network load but cannot accommodate changes in dynamic consumer requests. A new network paradigm was proposed. The network paradigm that was originally host-centric turned into content-centric. This scheme is known as the Named Data Network (NDN). NDN causes data communication to be carried out efficiently and minimizes network load. Content store as an important component of NDN routers is a limited resource. For this reason, certain mechanisms are needed to optimize content store usage. As far as the author's knowledge there are no papers that discuss caching mechanisms that pay attention to popularity and at the same time also differentiate service classes. In fact, there is a variation of traffic related to the traffic requirement. That's why it is necessary to differentiate service class treatment in NDN content store and also consider the content popularity. This paper proposed a caching algorithm namely CAPIC (CAche based on PopularIty and Class). From the simulation, concludes that CAPIC gives the greater hit rate compared to another scheme that only considers popularity and the better path stretch and appropriates with the cache proportion based on class.","PeriodicalId":250054,"journal":{"name":"2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130983744","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: 8

Remote Access Weather Monitoring System Based on Soft Real-Time System (SRTS) 基于软实时系统(SRTS)的远程接入天气监测系统

2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC) Pub Date : 2018-12-01 DOI: 10.1109/ICCEREC.2018.8711997

Megatari Wahyu Ningrum Handani, Giva Andriana Mutiara, D. R. Suchendra

{"title":"Remote Access Weather Monitoring System Based on Soft Real-Time System (SRTS)","authors":"Megatari Wahyu Ningrum Handani, Giva Andriana Mutiara, D. R. Suchendra","doi":"10.1109/ICCEREC.2018.8711997","DOIUrl":"https://doi.org/10.1109/ICCEREC.2018.8711997","url":null,"abstract":"Nowadays, along with the uncertainty changing of temperature and weather conditions, the need of a real time informative applications of weather conditions is really high. This research makes an application that can provide information about weather conditions at a particular location in real time. Although some research had been developed, however the application is still cannot provide direct weather information from the desired location accurately and real-time. The system is designed using DHT11 sensors, rain sensors, LDR sensors, BMP 280 sensors and IP Cameras. The real-time‘s concept used is Soft Real-Time System (SRTS). Based on the testing process that performed at different times, we have a temperature variation of 220 °C - 380 °C, humidity 10%-70% RH is generated and the response time of the system is in range 151ms - 157ms. This data then compared with the data from several weathers forecast application in some media. Data is sent and stored to the data base and then displayed in web application also mobile application. Based on that information, the user can get information directly in real time conditions due to weather conditions at the destination location by click the camera button.","PeriodicalId":250054,"journal":{"name":"2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133637642","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: 2

Mild Cognitive Impairment Classification using Hjorth Descriptor Based on EEG Signal 基于脑电信号的Hjorth描述符轻度认知障碍分类

2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC) Pub Date : 2018-12-01 DOI: 10.1109/ICCEREC.2018.8712095

S. Hadiyoso, L. R. M. Tati

引用次数: 5

16-Bit Low Power Feedforward Architecture Sigma-Delta ADC with Integrator Time Multiplexing for Microprocessors 16位低功耗前馈架构Sigma-Delta ADC与微处理器积分器时间复用

2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC) Pub Date : 2018-12-01 DOI: 10.1109/ICCEREC.2018.8712099

Robert T. Nericua, George Vinfred S. Maraat, Re-Ann Cristine O. Calimpusan, O. J. Gerasta, J. Hora

引用次数: 0

Hate Speech Detection Using Latent Semantic Analysis (LSA) Method Based On Image 基于图像的潜在语义分析(LSA)方法的仇恨语音检测

2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC) Pub Date : 2018-12-01 DOI: 10.1109/ICCEREC.2018.8712111

Ilham Maulana Ahmad Niam, Budhi Irawan, C. Setianingsih, Bagas Prakoso Putra

{"title":"Hate Speech Detection Using Latent Semantic Analysis (LSA) Method Based On Image","authors":"Ilham Maulana Ahmad Niam, Budhi Irawan, C. Setianingsih, Bagas Prakoso Putra","doi":"10.1109/ICCEREC.2018.8712111","DOIUrl":"https://doi.org/10.1109/ICCEREC.2018.8712111","url":null,"abstract":"Hate speech are a words, actions which is prohibited because it leads to acts that trigger anarchism and violence attidudes toward other individuals or groups. Ethics in the internet are needed considering that internet is a matter that important use for today's society. However, more side are miss using the internet to spread such kind a hate speech, such as ethnicity, religion and race. The development of a system for detecting hate speech through images is quite rare for now a days. Therefore, this study study is classified to detect whether there is an element of hatred in the image that will be selected. In this final project, the author hopes to make how to classify the element of hate speech in an image performed by the machine learning, which later that machine learning can recognize any kind of hate speech on the image through the existing text. With using Latent Semantic Analysis (LSA) method, we get the result of this research is precision 67%, recall 76.84%, and accuracy 57.9%. After creation of this research, it is hoped the computer can know and classify the existence of hate speech in the image.","PeriodicalId":250054,"journal":{"name":"2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127088897","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: 13