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

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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
Budi Prasetya, A. Kurniawan, Iskandar, Arfianto Fahmi
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.
为了提高64-QAM多载波通信系统的性能,我们提出了一种新的方法——闭环旋转调制。闭环过程需要反馈信道信息以复杂量的形式,其中包含了信道的增益和延迟信息。基于无失真传输的目的,在发射机侧得到了多载波系统闭环旋转调制方法中的方程。仿真结果表明,采用闭环旋转调制后,多载波解调器的输出信号与传输信号完全一致。在产生误差曲线的概率上,只要受AWGN信道干扰,采用闭环旋转调制就能与系统性能相吻合。为了使算法能够最优地工作,反馈的更新速度必须快于信道波动的变化,并且信道反馈能够完美地工作。仿真结果还表明,信道信息反馈虽然不完善,但仍能产生良好的性能,信道反馈越准确,误差概率越高。该方案的另一个优点是在多载波系统的传输过程中不使用保护间隔,从而使数据的效率最大化。
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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
I. K. Laga Dwi Pandika, Budhi Irawan, C. Setianingsih
Congestion in a region can cause a lack of efficiency of resources used and can have a wide impact on the smoothness of socio-economic activities in the region one of them in the area of Bandung and especially in the field of tourism congestion caused hampering of tourism activities for tourists. It takes an application that is able to get the optimal route to help the tourists to get to their tourist destination and avoid the congestion that occurs on the highway. In this final project, the author has designed Android application using shortest path algorithm. The algorithm used is Floyd-Warshall by considering the effectiveness and efficient level and Simple Additive Weighting (SAW) method in its weighting. From the test results that have been done this application works well by providing an appropriate route alternative with the average processing time of 0.0796250102 seconds shows Floyd-Warshall Algorithm and SAW method is working effectively and efficiently on the shortest route search.
一个地区的拥堵可能导致资源使用效率低下,并可能对该地区社会经济活动的顺利进行产生广泛影响,其中一个在万隆地区,特别是在旅游领域,拥堵造成了游客旅游活动的阻碍。它需要一个能够获得最佳路线的应用程序,以帮助游客到达他们的旅游目的地,避免高速公路上发生的拥堵。在这个最终的项目中,作者使用最短路径算法设计了Android应用程序。该算法采用Floyd-Warshall算法,考虑了算法的有效性和效率水平,加权采用简单加性加权法(Simple Additive Weighting, SAW)。从已经完成的测试结果来看,该应用程序提供了一个合适的路由替代方案,平均处理时间为0.0796250102秒,表明Floyd-Warshall算法和SAW方法在最短路由搜索上是有效和高效的。
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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
Taufiq Ari Wibowo, Muhammad Nasrun, C. Setianingsih
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.
在社会生活中,说谎是社会中常见而频繁的事情。沟通是在家庭、社区和工作世界中增加关系和建立关系的主要方式之一。在心理学领域,它可以通过身体部位来检测,比如;脸,眼睛,心跳等等。在这个Final Project中,编译器的工作重点是人眼。测谎仪以瞳孔直径变化和眨眼次数为目标,采用霍夫变换方法和决策树算法作为决策者。从研究结果来看,测谎仪系统获得了92%的准确率。采用霍夫圆变换法观察瞳孔直径的变化,采用眼宽比法增加眨眼次数,提高了精度。在进行的研究中,一个人的瞳孔眼睛会感受到最初被调查者瞳孔直径的扩大,眼睛的眨眼次数比被调查者在回答问题之前的眨眼次数增加了8倍以上。
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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
Umu Hanifah, Purba Daru Kusuma, C. Setianingsih
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.
视力是人类生命中最重要的感官之一。因为只有用我们的眼睛,我们才能看到和知道发生在我们周围的情况和条件。如果我们的眼睛出现问题或紊乱,那么我们会感到不舒服,有几种疾病会降低视力质量,并可能导致失明。在这个项目中,笔者将根据患者的早期症状,对翼状胬肉眼病进行检测,了解患者翼状胬肉病的严重程度和不同程度。用于确定翼状胬肉疾病级别的阶段是通过使用前向链接方法填充患者在应用程序中的所有症状,并使用维奥拉琼斯算法的图像分割过程。使用本应用程序处理过的Viola Jones算法的结果,通过测试50张图像,检测到的图像结果为38张图像,准确率为76%,此外还有一些未检测到的图像和未检测到的图像。
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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
Hernawan Kurniansyah, H. Wijanto, F. Y. Suratman
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.
自适应调制和编码(AMC)是一种执行自适应调制方案的系统,其中同一系统使用的调制集适应传输信道的条件。本课题的研究目标是研制一种能够自动区分调幅(AM)、下边带(LSB)、上边带(USB)、二相移键控(BPSK)、四相移键控(QPSK)和八相移键控(8PSK)调制的自动控制系统。AMC在军队中扮演着重要的角色。现代电子战,称为电子战(EW),由三个主要部分组成,即电子支援(ES)、电子攻击(EA)和电子防护(EP)。在电子支援中,主要目的是收集接收到的无线电信号的信息,因此AMC系统可以用于此。在AMC系统中,已知调制类型来进行解调过程,因此可以知道重叠信息。特征提取是AMC系统中最重要的过程之一。在本研究中,所进行的特征提取是一个时域的高阶统计特征。使用的统计顺序是顺序4。信息信号在有AWGN噪声干扰的情况下通过传输信道,信号质量在0 ~ 40 dB之间变化。采用人工神经网络算法对调制进行分类,学习率为0.5,最大epoch数为1000。利用4阶统计特征,本研究的AMC系统可以区分AM、LSB、USB、BPSK、QPSK和8PSK调制。本文对军用高频无线电中的调制技术进行了研究。在10db信号质量下,该系统在不使用非线性变换的情况下进行调制分类的准确率为65.5%。在10db信号质量下,对接收信号进行非线性变换的AMC精度达到88.8%。
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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
L. V. Yovita, N. Syambas, Ian Yosef Matheus Edward
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.
在IP网络中,如果有许多消费者需要相同的数据,则数据的请求和响应过程将重复,并将增加整体网络负载。对IP网络进行了修改,即内容分发网络将复制服务器放置在更靠近消费者的地方。CDN设法减少了网络负载,但不能适应动态消费者请求的变化。提出了一种新的网络范式。最初以主机为中心的网络模式变成了以内容为中心。这种方案被称为命名数据网络(NDN)。NDN使数据通信高效进行,使网络负荷最小化。内容存储作为NDN路由器的重要组成部分,是一种有限的资源。出于这个原因,需要某些机制来优化内容存储的使用。就笔者所知,还没有一篇论文讨论了既关注流行度又区分服务类别的缓存机制。实际上,存在与交通需求相关的交通变化。这就是为什么在NDN内容商店中需要区分服务等级待遇,并考虑内容的受欢迎程度。本文提出了一种缓存算法CAPIC (CAche based on PopularIty and Class)。仿真结果表明,与仅考虑流行度和路径延伸的方案相比,CAPIC方案具有更高的命中率,并且适合基于类别的缓存比例。
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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
Megatari Wahyu Ningrum Handani, Giva Andriana Mutiara, D. R. Suchendra
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.
如今,随着温度和天气条件的不确定性变化,对天气条件的实时信息应用的需求非常高。这项研究制作了一个应用程序,可以实时提供特定地点的天气状况信息。虽然已经进行了一些研究,但是应用程序仍然不能准确实时地提供所需位置的直接天气信息。该系统采用了DHT11传感器、雨水传感器、LDR传感器、BMP 280传感器和IP摄像机。使用的实时概念是软实时系统(SRTS)。根据在不同时间进行的测试过程,我们的温度变化范围为220°C - 380°C,湿度为10%-70% RH,系统的响应时间范围为151ms - 157ms。然后将该数据与一些媒体上应用的几个天气预报数据进行比较。数据被发送并存储到数据库中,然后在web应用程序和移动应用程序中显示。根据这些信息,用户可以通过点击相机按钮直接获得目的地天气状况的实时信息。
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引用次数: 2
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
Robert T. Nericua, George Vinfred S. Maraat, Re-Ann Cristine O. Calimpusan, O. J. Gerasta, J. Hora
This study presents a design of low power 3rd order 16-bit Sigma Delta Analog to Digital Converter in Feedforward Architecture with Integrator Time Multiplexing Technique implemented in TSMC 65nm CMOS technology. The designed is composed of a 3rd-order modulator in feedforward architecture to improve loop stability and with integrator time multiplexing technique for reduction of power consumption. The Analog to Digital Converter (ADC) is designed to consume a total power of 0.342mW and with a modulator sampling rate of 25600Hz. This ADC uses a 2V supply for analog circuit blocks and a 1V supply for digital circuit block. The ADC has a dimension of 333.35um x 241.64um.
本研究提出一种采用积分器时间复用技术的低功耗三阶16位Sigma Delta前馈模数转换器的设计方案。该系统采用前馈三阶调制器结构,提高了系统的稳定性,同时采用积分器时间复用技术,降低了系统功耗。模数转换器(ADC)的设计功耗为0.342mW,调制器采样率为25600Hz。该ADC采用2V模拟电路模块和1V数字电路模块。ADC的尺寸为333.35um x 241.64um。
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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
Ilham Maulana Ahmad Niam, Budhi Irawan, C. Setianingsih, Bagas Prakoso Putra
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.
仇恨言论是一种被禁止的言论和行为,因为它会导致引发无政府主义和对其他个人或团体的暴力态度的行为。考虑到互联网对当今社会的重要用途,互联网中的道德规范是需要的。然而,更多的方面是怀念利用互联网传播这种仇恨言论,如民族,宗教和种族。最近,通过图片检测仇恨言论的系统的开发非常罕见。因此,本研究对研究进行分类,检测图像中是否存在将被选择的仇恨元素。在这个最终的项目中,作者希望通过机器学习来完成如何对图像中的仇恨言论元素进行分类,之后机器学习可以通过现有的文本来识别图像上的任何一种仇恨言论。利用潜在语义分析(LSA)方法,得到了准确率67%、查全率76.84%、准确率57.9%的研究结果。本研究创建后,希望计算机能够知道并分类图像中仇恨言论的存在。
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引用次数: 13
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
S. Hadiyoso, L. R. M. Tati
Electroencephalogram (EEG) has an important role for detection, classification, diagnosis and treatment of brain disorders. One indication of a brain disorder that can be diagnosed through EEG examination is Mild Cognitive Impairment (MCI). MCI can be a symptom of Alzheimer's disease (AD) at a higher level. In this paper, we apply time domain based EEG signal processing to classify these signals in MCI patients with normal controlled subjects. Hjorth Descriptor is used to obtained the signal features, namely complexity, mobility and activity. 10 EEG data consisting of 5 MCI patients and 5 normal subjects were analyzed. From the results of testing, the Hjorth parameters in normal subjects tend to have a greater value than the MCI subject.
脑电图(EEG)对脑部疾病的检测、分类、诊断和治疗具有重要作用。通过脑电图检查可以诊断出脑部疾病的一个迹象是轻度认知障碍(MCI)。MCI可能是阿尔茨海默病(AD)的一种更高水平的症状。本文采用基于时域的脑电信号处理方法对MCI患者的脑电信号进行分类。Hjorth Descriptor用于获取信号的特征,即复杂度、移动性和活动性。对5例轻度认知损伤患者和5例正常人的10例脑电图数据进行分析。从测试结果来看,正常受试者的Hjorth参数值往往大于MCI受试者。
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引用次数: 5
期刊
2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC)
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