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2019 International Conference on Machine Learning and Cybernetics (ICMLC)最新文献

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Energy Efficient Geocasting Based on Q-Learning for Wireless Sensor Networks 基于q -学习的无线传感器网络节能地理投影
Pub Date : 2019-07-01 DOI: 10.1109/ICMLC48188.2019.8949272
Neng-Chung Wang, Young-Long Chen, Yung-Fa Huang, Li-Cheng Huang, Tzu-Yi Wang, Hsu-Yao Chuang
In this paper, we propose two energy efficient geocasting protocols based on Q-learning for wireless sensor networks (WSNs), called FERMA-QL and FER-MA-QL-E. We utilize the theorem of Fermat point to find Fermat points in geocasting, the node which is the closest to the Fermat points is selected as the relay nodes. Then, we establish the shared path among gateways, relay nodes and base station by Q-learning for data transmission. In FERMA-QL, the reward is given by the reciprocal of the distance between the received node and the destination node In FERMA-QL-E, the reward is given by the remaining energy of the received node divided by the distance between itself and the destination node. Sensors utilize the shared path to forward their data to achieve goal of reduce energy consumption. Simulation result shows that the proposed FERMA-QL and FERMA-QL-E can efficiently extend the life-time of the WSN.
在本文中,我们提出了两种基于q -学习的无线传感器网络(WSNs)节能地理投射协议,称为FERMA-QL和FER-MA-QL-E。利用费马点定理寻找地质浇铸中的费马点,选取离费马点最近的节点作为中继节点。然后,通过q学习建立网关、中继节点和基站之间的共享路径,实现数据传输。在FERMA-QL中,奖励是接收节点与目的节点之间距离的倒数。在FERMA-QL- e中,奖励是接收节点的剩余能量除以自身与目的节点之间的距离。传感器利用共享路径转发数据,达到降低能耗的目的。仿真结果表明,所提出的FERMA-QL和FERMA-QL- e能够有效地延长无线传感器网络的寿命。
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引用次数: 1
Investigations on Classification Methods for Loan Application Based on Machine Learning 基于机器学习的贷款申请分类方法研究
Pub Date : 2019-07-01 DOI: 10.1109/ICMLC48188.2019.8949252
Mingli Wu, Yafei Huang, Jianyong Duan
As there is an increasing trend of people consuming by debit in China, financial organizations deal with a lot of loan applications. If customers cannot repay the loans on time, the organizations have to cover the loss. Therefore it is important to predict correctly whether a customer will repay the loan on time. Typical machine learning methods can be employed to exploit customers' financial information and give valuable judgements. We investigated the function of Deep Neural Network (DNN) in this work, as it achieves high successful rate in fields of image recognition, speech recognition and natural language processing. We compared it with traditional learning methods, such as Naïve Bayes, decision tree and K-Nearest Neighbor. Experiments showed that DNN achieves better performance than its traditional competitors. The accuracy and recall of DNN are 0.73 and 0.42 respectively. Its It-score is 25% higher than the best one of traditional methods.
由于中国的借方消费呈增长趋势,金融机构处理了大量的贷款申请。如果客户不能按时偿还贷款,这些机构必须承担损失。因此,正确预测客户是否会按时偿还贷款是很重要的。典型的机器学习方法可以用来利用客户的财务信息,并给出有价值的判断。由于深度神经网络(Deep Neural Network, DNN)在图像识别、语音识别和自然语言处理等领域取得了很高的成功率,因此本文对其功能进行了研究。我们将其与传统的学习方法,如Naïve贝叶斯、决策树和k近邻进行了比较。实验表明,深度神经网络比传统的竞争对手取得了更好的性能。DNN的准确率和召回率分别为0.73和0.42。它的it得分比最好的传统方法高出25%。
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引用次数: 4
Retrieving Articles and Image Labeling Based on Relevance of Keywords 基于关键词相关性的文章检索与图像标注
Pub Date : 2019-07-01 DOI: 10.1109/ICMLC48188.2019.8949205
Shu-Chen Cheng, Chun Lu
When users input keywords into the search engine, a massive search results will be retrieved. However, it becomes difficult for the users to learn as it is unreadable with the excessive amount of results. This study establishes an information retrieval system for computer science related articles. It firstly collects articles by running a web crawler, and uses TF-IDF (Term Frequency-Inverse Document Frequency) method to extract keywords to acquire the focus of the article. And with the use of association rules and cosine similarity, the articles are classified by their relevance. Finally, according to users' feedbacks, the system provides appropriate resources to improve the motivation and willingness to learn. In addition, the pictures in the articles are also a basis for analyzing the articles. This study uses image semantic analysis to label the pictures so as to improve the accuracy in analyzing the articles.
当用户在搜索引擎中输入关键字时,会检索到大量的搜索结果。然而,由于结果过多,用户很难学习,因为它难以阅读。本研究建立一个计算机科学相关文章的资讯检索系统。首先通过运行网络爬虫收集文章,然后使用TF-IDF (Term Frequency- inverse Document Frequency)方法提取关键词,获取文章的重点。利用关联规则和余弦相似度,根据文章的相关性进行分类。最后,根据用户的反馈,系统提供适当的资源,以提高学习的动机和意愿。此外,文章中的图片也是分析文章的依据。本研究采用图像语义分析对图片进行标注,以提高文章分析的准确性。
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引用次数: 0
Real-Time Car Detection and Driving Safety Alarm System With Google Tensorflow Object Detection API 实时汽车检测和驾驶安全报警系统与谷歌Tensorflow对象检测API
Pub Date : 2019-07-01 DOI: 10.1109/ICMLC48188.2019.8949265
C. Hsieh, Dung-Ching Lin, Chengjia Wang, Zong-Ting Chen, Jiun-Jian Liaw
Car accident is a serious social problem which often results in both life loss and financial loss. Most of car accidents are caused by a lack of safe distance between cars. To relieve this problem, in this paper we propose a real-time car detection and safety alarm system. The proposed system consists of two modules: real-time car detection module and safety alarm module. The proposed system is supposed to apply in a normal highway driving scenario. In the car detection module, the Google Tensorflow Object Detection (GTOD) API is employed. The function of GTOD API is to detect frontal cars in real-time and then mark them with rectangular boxes. As for the safety alarm module, it consists of three phases: to calculate the box width of detected cars; to calculate the safety factor; to determine the driving state. To justify the proposed system, a real highway experiment is conducted. The results show that the proposed system is able to appropriately indicate driving states: safe, dangerous and warning. By the given experimental results, it implies that the proposed system is feasible and applicable in the real-world applications.
交通事故是一个严重的社会问题,经常造成生命损失和经济损失。大多数车祸是由于车与车之间缺乏安全距离造成的。为了解决这一问题,本文提出了一种实时车辆检测与安全报警系统。本系统由两个模块组成:实时车辆检测模块和安全报警模块。该系统预计将适用于正常的高速公路驾驶场景。在汽车检测模块中,使用了Google Tensorflow Object detection (GTOD) API。GTOD API的功能是实时检测前方车辆,并用矩形框对其进行标记。安全报警模块分为三个阶段:计算被检测车辆的箱体宽度;计算安全系数;以确定驾驶状态。为了验证所提出的系统,进行了真实的高速公路实验。结果表明,所提出的系统能够适当地指示驾驶状态:安全、危险和警告。实验结果表明,该系统在实际应用中是可行的。
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引用次数: 6
Would you Turn-On GPS for LBA? Fuzzy AHP Approach 你会为LBA开启GPS吗?模糊层次分析法
Pub Date : 2019-07-01 DOI: 10.1109/ICMLC48188.2019.8949270
Hengdong Yang, Shiang-Lin Lin, Jui-Yen Chang
Location-based advertising (LBA) is a mobile phone service to apply customers' geographic location to provide suitable advertisement. It was proved in literature to be effective to motivate purchasing intention. However, perceived benefits would be accompanied by perceived risks of privacy concerns to users. The precondition of receiving the LBA is to turn on the location functions in the mobile device. This study applies the Fuzzy Analytic Hierarchy Process (FAHP) method to analyze the factors evaluated by consumers while considering to turn on the GPS functions for receiving LBA. The analytic results reported that “functional value”, “privacy considerations” and “inertia and usage of other 3C habits” are the top three important decision dimensions. In terms of decision factors, the most top three important evaluation factors are “habit of using 3C device”, “getting money-saving opportunities” and “whereabouts”. The findings are useful not only for LBA providers to design and manage their advertising practices but also for consumers to understand the critical factors while considering to turn on the GPS functions for receiving LBA.
基于位置的广告(location based advertising, LBA)是一种利用手机用户的地理位置提供合适广告的服务。文献证明,这对激发购买意愿是有效的。然而,感知到的好处将伴随着用户隐私担忧的感知风险。接收LBA的前提是打开移动设备的定位功能。本研究采用模糊层次分析法(FAHP)对消费者在考虑开启GPS接收LBA功能时所评价的因素进行分析。分析结果显示,“功能价值”、“隐私考虑”和“惯性和其他3C习惯的使用”是最重要的三个决策维度。在决策因素方面,排名前三位的重要评价因素分别是“使用3C设备的习惯”、“获得省钱机会”和“去向”。研究结果不仅有助于LBA提供商设计和管理他们的广告实践,也有助于消费者在考虑打开GPS功能以接收LBA时了解关键因素。
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引用次数: 1
Research on Comprehensive Quality Evaluation Method Based on Cooperative Performance 基于合作绩效的综合质量评价方法研究
Pub Date : 2019-07-01 DOI: 10.1109/ICMLC48188.2019.8949166
Cheng-Bin Wang, Fachao Li
Comprehensive quality evaluation is the measure of the members' comprehensive ability and the premise and foundation of improving the team's operation efficiency. How to accurately obtain the comprehensive quality of members has been a widely concerned issue in the academic and application fields. Taking cooperative performance as the main observation index, this paper proposes a comprehensive quality evaluation model based on cooperative performance, and analyzes the characteristics and shortcomings of this model. In order to solve the problem that the solution cannot be guaranteed, the method of multi objective programming is applied to give the solution strategy based on the deviation variable. Finally, the feasibility and effectiveness of the model are analyzed with a case study. Theoretical analysis and example calculation show that the model has good interpretability and operability, which not only improves the existing evaluation methods to a certain extent, but also has wide application value in the fields of resource allocation, artificial intelligence and recommendation system.
综合素质评价是衡量团队成员综合能力的尺度,是提高团队运作效率的前提和基础。如何准确地获取会员的综合素质,一直是学术界和应用领域广泛关注的问题。本文以合作绩效为主要观察指标,提出了一种基于合作绩效的综合质量评价模型,并分析了该模型的特点和不足。为了解决不能保证解的问题,应用多目标规划方法给出了基于偏差变量的求解策略。最后,通过实例分析了该模型的可行性和有效性。理论分析和算例计算表明,该模型具有良好的可解释性和可操作性,不仅在一定程度上改进了现有的评价方法,而且在资源分配、人工智能和推荐系统等领域具有广泛的应用价值。
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引用次数: 0
On Optimal Energy Consumption Control Method for Tail Fin Bionic Robotic Fish 尾鳍仿生机器鱼最优能量消耗控制方法研究
Pub Date : 2019-07-01 DOI: 10.1109/ICMLC48188.2019.8949254
Guihai Li, Gang Liu, Yu-Xuan Li, Song-Lin Chen
The endurance ability is an important factor to be considered in the practical application of bionic robotic fish. By designing an optimal energy consumption control method, the energy consumption of robotic fish can be effectively reduced. In this paper, the structural characteristics of the tail fin bionic robotic fish are abstracted through the motion analysis of the tail fin fish. On this basis, a simplified dynamic and kinematic model of the robotic fish and a calculation method of energy consumption are established. Then, by changing the oscillation amplitude and frequency of the tail, the change law of the swimming speed is obtained. It is also found that the energy consumption is positively correlated with the swimming speed in general. In order to get the lowest energy consumption swimming mode of robotic fish at different swimming speeds, a series of optimal energy consumption points are obtained at the interval of 0.05m/s. The control method of optimal energy consumption of robotic fish is designed by analyzing its distribution law.
在仿生机器鱼的实际应用中,耐力是一个需要考虑的重要因素。通过设计最优的能耗控制方法,可以有效降低机器鱼的能耗。本文通过对尾鳍鱼的运动分析,抽象出了尾鳍仿生机器鱼的结构特点。在此基础上,建立了机器鱼的简化动力学和运动学模型以及能量消耗的计算方法。然后,通过改变尾鳍的振荡幅度和频率,得到游动速度的变化规律。总体上,能量消耗与游泳速度呈正相关。为了得到机器鱼在不同游泳速度下的最低能耗游泳模式,以0.05m/s为间隔获得一系列最优能耗点。通过分析机器鱼的能量分配规律,设计了机器鱼的最优能量消耗控制方法。
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引用次数: 1
Nanocarbon Electrode for Wearable Device With Flexible Material 采用柔性材料的可穿戴设备用纳米碳电极
Pub Date : 2019-07-01 DOI: 10.1109/ICMLC48188.2019.8949223
Mai Kondo, T. Fujita, K. Kanda, K. Maenaka
In this study, we aimed to develop a smart-cloth for workout. A flexible elastic electrode by using silicone rubber with special carbon black material, KETJENBLACK, was fabricated and tested. The flexible conductive electrode having an expansion ability of 100% or more was successfully fabricated. The compound of special carbon black, KETJENBLACK, can offer flexible electrodes and be suitable for wearable devices.
在这项研究中,我们的目标是开发一种用于锻炼的智能布。采用硅橡胶和特殊炭黑材料KETJENBLACK制备了一种柔性弹性电极,并对其进行了测试。成功制备了膨胀率达到100%以上的柔性导电电极。特殊炭黑化合物KETJENBLACK可以提供柔性电极,适用于可穿戴设备。
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引用次数: 2
Detection of Optimal Puncture Position in OVUM Images for Artificial Insemination 人工授精OVUM图像中最佳穿刺位置的检测
Pub Date : 2019-07-01 DOI: 10.1109/ICMLC48188.2019.8949312
Yuya Kinishi, T. Maekawa, S. Mizuta, T. Ishikawa, Y. Hata
This paper aims to determine the optimal puncture position of ovum by evaluating rupture membrane of cytoplasm. We employed 139 ovum images on the Piezo-ICSI (Intracytoplasmic sperm injection). In it, grayscale images before puncture and their actual puncture position were obtained from the movie file (Rupture:31, No Rupture:108), and Local Binary Pattern (LBP) feature is calculated at analysis area around the puncture position. LBP feature dimensions are reduced, and data are classified by hierarchical clustering method using feature of three dimensions. As a result, the data classified into two clusters (Clusters A and B). Cluster A has 7 Ruptures and 50 No Ruptures, Cluster B has 24 Ruptures and 58 No Ruptures. Then, the sensitivity is 0.77. Therefore, it is possible to evaluate rupture membrane of cytoplasm from shape feature of membrane. The optimal puncture position could be determined by the features.
本文旨在通过评价细胞质破裂膜来确定卵子的最佳穿刺位置。我们使用了139个卵子的卵胞浆内单精子注射(Piezo-ICSI)图像。其中,从电影文件(破裂:31,未破裂:108)中获取穿刺前的灰度图像及其实际穿刺位置,并在穿刺位置周围的分析区域计算局部二值模式(Local Binary Pattern, LBP)特征。将LBP特征降维,利用三维特征对数据进行分层聚类分类。因此,将数据分为两组(a和B), a组有7个Ruptures和50个No Ruptures, B组有24个Ruptures和58个No Ruptures。则灵敏度为0.77。因此,从膜的形状特征来评价细胞质破裂膜是可能的。根据特征确定最佳穿刺位置。
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引用次数: 1
Automatic Detection of Mispronounced Lyrics in Singing 唱词发音错误的自动检测
Pub Date : 2019-07-01 DOI: 10.1109/ICMLC48188.2019.8949315
Wei-Ho Tsai, Van-Thuan Tran, Shiang-Shiun Kung
In this study, we propose an automatic system for detecting mispronounced lyrics in singing, thereby providing information for singing performance assessment. The system is built upon the basis of speech utterance verification and further improved by considering the difference between singing and speech. We recognize that the vowels are often lengthened during singing and thus include a duration modeling concept in the acoustic modeling to absorb the variation of the length of a vowel in singing. Our experiments show that the proposed methods can achieve 11.3% equal error rate in detecting the mispronounced lyrics in singing.
在这项研究中,我们提出了一个自动检测唱歌中发音错误歌词的系统,从而为唱歌表现评估提供信息。该系统建立在语音验证的基础上,并考虑到唱歌和说话的区别,进一步完善。我们认识到在歌唱过程中元音经常被拉长,因此在声学建模中包含了一个持续时间建模的概念,以吸收歌唱中元音长度的变化。实验结果表明,该方法在检测唱词中的误读时,平均错误率可达11.3%。
{"title":"Automatic Detection of Mispronounced Lyrics in Singing","authors":"Wei-Ho Tsai, Van-Thuan Tran, Shiang-Shiun Kung","doi":"10.1109/ICMLC48188.2019.8949315","DOIUrl":"https://doi.org/10.1109/ICMLC48188.2019.8949315","url":null,"abstract":"In this study, we propose an automatic system for detecting mispronounced lyrics in singing, thereby providing information for singing performance assessment. The system is built upon the basis of speech utterance verification and further improved by considering the difference between singing and speech. We recognize that the vowels are often lengthened during singing and thus include a duration modeling concept in the acoustic modeling to absorb the variation of the length of a vowel in singing. Our experiments show that the proposed methods can achieve 11.3% equal error rate in detecting the mispronounced lyrics in singing.","PeriodicalId":221349,"journal":{"name":"2019 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125870879","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
期刊
2019 International Conference on Machine Learning and Cybernetics (ICMLC)
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