2020 IEEE Symposium Series on Computational Intelligence (SSCI)最新文献

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SIMP3: Social Interaction-Based Multi-Pedestrian Path Prediction By Self-Driving Cars SIMP3:自动驾驶汽车基于社会互动的多行人路径预测
2020 IEEE Symposium Series on Computational Intelligence (SSCI) Pub Date : 2020-12-01 DOI: 10.1109/SSCI47803.2020.9308130
Nora Muscholl, Atanas Poibrenski, M. Klusch, Patrick Gebhard
{"title":"SIMP3: Social Interaction-Based Multi-Pedestrian Path Prediction By Self-Driving Cars","authors":"Nora Muscholl, Atanas Poibrenski, M. Klusch, Patrick Gebhard","doi":"10.1109/SSCI47803.2020.9308130","DOIUrl":"https://doi.org/10.1109/SSCI47803.2020.9308130","url":null,"abstract":"An accurate and fast prediction of future positions of pedestrians by a self-driving car in critical traffic scenarios remains a challenge. The intention of a pedestrian to cross the street can be influenced by social interactions with another one across the street, which may be manifested through various types of social signals such as hand waving. Current socially-aware multi-pedestrian path predictors mainly rely on geometric heuristics such as the distance between pedestrians in the field of view of the car, but do not consider their social interaction across the street. This paper presents a novel social interaction-based multi-pedestrian path predictor (SIMP3) which leverages a combination of dynamic Bayesian networks for intention detection and recurrent network for prediction of future pedestrian locations. The system has been evaluated on the benchmark OpenDS-CTS2 of critical traffic scenarios with socially interacting pedestrians across the street simulated in OpenDS. Our experiments revealed that in most scenarios SIMP3 can significantly outperform the selected competitors.","PeriodicalId":413489,"journal":{"name":"2020 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115020970","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: 4
Design of Work Ticket System and Scheduling Algorithm based on Blockchain 基于区块链的工单系统及调度算法设计
2020 IEEE Symposium Series on Computational Intelligence (SSCI) Pub Date : 2020-12-01 DOI: 10.1109/SSCI47803.2020.9308362
Hongkai Wang, Yiyang Yao, Qitong Hou, Xiaoyi Wang, Lei Zeng, Weiwei Qiu, Dong He, Qiang Wang
{"title":"Design of Work Ticket System and Scheduling Algorithm based on Blockchain","authors":"Hongkai Wang, Yiyang Yao, Qitong Hou, Xiaoyi Wang, Lei Zeng, Weiwei Qiu, Dong He, Qiang Wang","doi":"10.1109/SSCI47803.2020.9308362","DOIUrl":"https://doi.org/10.1109/SSCI47803.2020.9308362","url":null,"abstract":"This paper proposes and designs a work ticket system based on blockchain technology to realize employee identity authentication, credible management of work ticket status circulation, and authority control. Allow users to fully control the private key and store it locally, effectively avoiding large-scale information leakage. After the work ticket data is encrypted with a hash algorithm, the private key is used to sign it for storage on the blockchain, which ensures that the work ticket data cannot be tampered with or forged, and the person responsible can be accurately located based on the signature information. In the circulation of work tickets from the distribution to the receiving state, in order to distribute the work tickets to the corresponding receivers more reasonably, this paper combines the Analytic Hierarchy Process in operations research to design the work ticket scheduling algorithm and the contrast matrix is used to define the weights of various characteristics of the receivers, and after the consistency check, the receiver with the highest score is calculated, making the system more intelligent and efficient.","PeriodicalId":413489,"journal":{"name":"2020 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129558240","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: 1
Motion Identification of fingerspelling by Wrist EMG Analysis 基于腕部肌电图分析的手指拼写动作识别
2020 IEEE Symposium Series on Computational Intelligence (SSCI) Pub Date : 2020-12-01 DOI: 10.1109/SSCI47803.2020.9308269
Tsubasa Fukui, Momoyo Ito, S. Ito, M. Fukumi
{"title":"Motion Identification of fingerspelling by Wrist EMG Analysis","authors":"Tsubasa Fukui, Momoyo Ito, S. Ito, M. Fukumi","doi":"10.1109/SSCI47803.2020.9308269","DOIUrl":"https://doi.org/10.1109/SSCI47803.2020.9308269","url":null,"abstract":"Recent years, interfaces using biometric information are progressing. Electromyogram(EMG) has been used in a variety of situations. Many studies have measured EMG in the shoulders and arms, where there is a lot of muscle mass. In addition, wet type sensors have been often used. However, those are inconvenient to use in everyday life and high cost. In this research, we measure wrist EMG for convenience and cost. Currently, researches have been done on the wrist EMG motion identification and personal identification. These studies have conducted simple movements and a large number of electrodes for discrimination. Furthermore, authentication by password sequence with gestures has not been done. In this paper, we propose to realize motion identification and personal authentication with complex movements using a small number of electrodes. The measured data was preprocessed such as removing noise and smoothing. We compared the accuracies obtained using Support Vector Machine(SVM) and Long Short-term memory(LSTM) for motion identification and authentication. The accuracies obtained using SVM and LSTM were 60.4% and 62.4%, respectively. In this case, the number of data was small. It is therefore necessary for increasing the number of data to perform deep learning.","PeriodicalId":413489,"journal":{"name":"2020 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"2003 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128681397","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: 1
Multichannel Symbolic Aggregate Approximation Intelligent Icons: Application for Activity Recognition 多通道符号聚合近似智能图标:活动识别的应用
2020 IEEE Symposium Series on Computational Intelligence (SSCI) Pub Date : 2020-12-01 DOI: 10.1109/SSCI47803.2020.9308497
Lamprini Pappa, P. Karvelis, G. Georgoulas, C. Stylios
{"title":"Multichannel Symbolic Aggregate Approximation Intelligent Icons: Application for Activity Recognition","authors":"Lamprini Pappa, P. Karvelis, G. Georgoulas, C. Stylios","doi":"10.1109/SSCI47803.2020.9308497","DOIUrl":"https://doi.org/10.1109/SSCI47803.2020.9308497","url":null,"abstract":"In this work, we introduce the Multichannel Intelligent Icons, a novel method for producing and presenting essential patterns of multidimensional bio-signals. The proposed approach is an extension of Symbolic Aggregate Approximation (SAX) along with an innovative variation of Intelligent Icons. The innovation on the approach stands on the grounds of creating a spatial correlation of the inherited information in all dimensions and so it provides extra features for distinguishing the human activities. The proposed model is testing on Human Activity recorded data and for the classification purposes a Nearest Neighbour classifier is applied. The achieved results are compared with the case of applying single-channel intelligent icons approach and it is inferred a noteworthy increase in terms of accuracy and sensitivity with the proposed approach.","PeriodicalId":413489,"journal":{"name":"2020 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128735010","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
A Genetic Programming Hyper-Heuristic Approach to Design High-Level Heuristics for Dynamic Workflow Scheduling in Cloud 云环境下动态工作流调度的遗传规划超启发式高级启发式设计
2020 IEEE Symposium Series on Computational Intelligence (SSCI) Pub Date : 2020-12-01 DOI: 10.1109/SSCI47803.2020.9308261
Kirita-Rose Escott, Hui Ma, Gang Chen
{"title":"A Genetic Programming Hyper-Heuristic Approach to Design High-Level Heuristics for Dynamic Workflow Scheduling in Cloud","authors":"Kirita-Rose Escott, Hui Ma, Gang Chen","doi":"10.1109/SSCI47803.2020.9308261","DOIUrl":"https://doi.org/10.1109/SSCI47803.2020.9308261","url":null,"abstract":"Workflow scheduling in the cloud is the process of allocating tasks to scarce cloud resources, with an optimal goal. This is often achieved by adopting an effective scheduling heuristic. Workflow scheduling in cloud is challenging due to the dynamic nature of the cloud, often existing works focus on static workflows, ignoring this challenge. Existing heuristics, such as MINMIN, focus mainly on one specific aspect of the scheduling problem. High-level heuristics are heuristics constructed from existing man-made heuristics. In this paper, we introduce a new and more realistic workflow scheduling problem that considers different kinds of workflows, cloud resources and high-level heuristics. We propose a High-Level Heuristic Dynamic Workflow Scheduling Genetic Programming (HLH-DSGP) algorithm to automatically design high-level heuristics for workflow scheduling to minimise the response time of dynamically arriving task in a workflow. Our proposed HLH-DSGP can work consistently well regardless of the size and pattern of workflows, or number of available cloud resources. It is evaluated using a popular benchmark dataset using the popular WorkflowSim simulator. Our experiments show that with high-level scheduling heuristics, designed by HLH-DSGP, we can jointly use several well-known heuristics to achieve a desirable balance among multiple aspects of the scheduling problem collectively, hence improving the scheduling performance.","PeriodicalId":413489,"journal":{"name":"2020 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129448823","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: 1
Adaptive Continuous Feature Binarization for Tsetlin Machines Applied to Forecasting Dengue Incidences in the Philippines Tsetlin机器自适应连续特征二值化在菲律宾登革热发病率预测中的应用
2020 IEEE Symposium Series on Computational Intelligence (SSCI) Pub Date : 2020-12-01 DOI: 10.1109/SSCI47803.2020.9308291
Kuruge Darshana Abeyrathna, Ole-Christoffer Granmo, Xuan Zhang, Morten Goodwin
{"title":"Adaptive Continuous Feature Binarization for Tsetlin Machines Applied to Forecasting Dengue Incidences in the Philippines","authors":"Kuruge Darshana Abeyrathna, Ole-Christoffer Granmo, Xuan Zhang, Morten Goodwin","doi":"10.1109/SSCI47803.2020.9308291","DOIUrl":"https://doi.org/10.1109/SSCI47803.2020.9308291","url":null,"abstract":"The Tsetlin Machine (TM) is a recent interpretable machine learning algorithm that requires relatively modest computational power, yet attains competitive accuracy in several benchmarks. TMs are inherently binary; however, many machine learning problems are continuous. While binarization of continuous data through brute-force thresholding has yielded promising accuracy, such an approach is computationally expensive and hinders extrapolation. In this paper, we address these limitations by standardizing features to support scale shifts in the transition from training data to real-world operation, typical for e.g. forecasting. For scalability, we employ sampling to reduce the number of binarization thresholds, relying on stratification to minimize loss of accuracy. We evaluate the approach empirically using two artificial datasets before we apply the resulting TM to forecast dengue outbreaks in the Philippines using the spatiotemporal properties of the data. Our results show that the loss of accuracy due to threshold sampling is insignificant. Furthermore, the dengue outbreak forecasts made by the TM are more accurate than those obtained by Support Vector Machines (SVMs), Decision Trees (DTs), and several multi-layered Artificial Neural Networks (ANNs), both in terms of forecasting precision and Fl-score.","PeriodicalId":413489,"journal":{"name":"2020 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129682295","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
Financial time-series analysis of Brazilian stock market using machine learning 利用机器学习对巴西股市进行金融时间序列分析
2020 IEEE Symposium Series on Computational Intelligence (SSCI) Pub Date : 2020-12-01 DOI: 10.1109/SSCI47803.2020.9308470
F. G. D. C. Ferreira, A. Gandomi, R. N. Cardoso
{"title":"Financial time-series analysis of Brazilian stock market using machine learning","authors":"F. G. D. C. Ferreira, A. Gandomi, R. N. Cardoso","doi":"10.1109/SSCI47803.2020.9308470","DOIUrl":"https://doi.org/10.1109/SSCI47803.2020.9308470","url":null,"abstract":"The recent profound changes in technological development have allowed the application of complex computational techniques for modeling and predicting price movements in the Stock Market. In this context, this paper compares the performance of different Machine Learning classifiers in predicting the trend of future financial asset price movements, in addition to performing the stock market trading simulation to assess financial gains provided by the trading strategy that considers the predictions as buying and selling signals. The paper considers five single classifiers, three ensemble classifiers that use Decision Tree as weak classifiers and four ensemble classifiers that combine the eight other classifiers, in addition to two benchmark classifiers. The simulation uses the best classifier and compares its efficiency with the buy and hold strategy. Results show that the precision of the Convolutional Neural Network surpasses that of the other classifiers and the simulation indicates that the use of classification as a trading strategy can reduce the potential for greater gains, but also avoids large losses, reducing the risk of investment.","PeriodicalId":413489,"journal":{"name":"2020 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123148124","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: 1
Discovering Communities with SGNS Modelling-based Network connections and Text communications Clustering 基于SGNS建模的网络连接和文本通信聚类发现社区
2020 IEEE Symposium Series on Computational Intelligence (SSCI) Pub Date : 2020-12-01 DOI: 10.1109/SSCI47803.2020.9308190
W. Mohotti, R. Nayak
{"title":"Discovering Communities with SGNS Modelling-based Network connections and Text communications Clustering","authors":"W. Mohotti, R. Nayak","doi":"10.1109/SSCI47803.2020.9308190","DOIUrl":"https://doi.org/10.1109/SSCI47803.2020.9308190","url":null,"abstract":"By the community discovery, the microblogging services facilitate diverse applications such as viral marketing, disaster management, customized programs, and many more. However, the sparseness and heterogeneity of user networks and text content make it difficult to group users with a similar interest. In this paper, we present a novel method to discover user communities with common interests. The proposed method utilizes both text content and interaction network information where network information is modeled using the concept of Skip-Gram with Negative Sampling for Non-negative Matrix Factorization. Empirical analysis using several real-world Twitter datasets shows that the proposed method is able to produce accurate user communities as compared to the state-of-the-art community discovery and clustering methods.","PeriodicalId":413489,"journal":{"name":"2020 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123601293","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
Elliptic Envelope Based Detection of Stealthy False Data Injection Attacks in Smart Grid Control Systems 基于椭圆包络的智能电网控制系统隐形假数据注入攻击检测
2020 IEEE Symposium Series on Computational Intelligence (SSCI) Pub Date : 2020-12-01 DOI: 10.1109/SSCI47803.2020.9308523
M. Ashrafuzzaman, Saikat Das, Ph.D., Ananth A. Jillepalli, Y. Chakhchoukh, Frederick T. Sheldon
{"title":"Elliptic Envelope Based Detection of Stealthy False Data Injection Attacks in Smart Grid Control Systems","authors":"M. Ashrafuzzaman, Saikat Das, Ph.D., Ananth A. Jillepalli, Y. Chakhchoukh, Frederick T. Sheldon","doi":"10.1109/SSCI47803.2020.9308523","DOIUrl":"https://doi.org/10.1109/SSCI47803.2020.9308523","url":null,"abstract":"State estimation is an important process in power transmission systems. Stealthy false data injection attacks (SF-DIA) against state estimation may cause electricity theft, minor disturbances or even outages. Accurate and precise detection of these attacks are very important to prevent or minimize damages. In this paper, we propose an unsupervised learning based scheme to detect SFDIA on the state estimation. The scheme uses random forest classifier for dimensionality reduction and elliptic envelope for detecting these attacks as anomalies. We compare the performance of the elliptic envelope method with four other unsupervised methods. All five models are trained and then tested with a dataset from a simulated IEEE 14-bus system. The results demonstrate that the elliptic envelope based approach provides the best detection rate and least false alarm rate among these five unsupervised methods.","PeriodicalId":413489,"journal":{"name":"2020 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114340049","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
Towards a More Practically Sound Formulation of Dynamic Problems and Performance Evaluation of Dynamic Search Methods 更实用的动态问题表述及动态搜索方法的性能评价
2020 IEEE Symposium Series on Computational Intelligence (SSCI) Pub Date : 2020-12-01 DOI: 10.1109/SSCI47803.2020.9308464
A. Ahrari, S. Elsayed, R. Sarker, D. Essam, C. Coello
{"title":"Towards a More Practically Sound Formulation of Dynamic Problems and Performance Evaluation of Dynamic Search Methods","authors":"A. Ahrari, S. Elsayed, R. Sarker, D. Essam, C. Coello","doi":"10.1109/SSCI47803.2020.9308464","DOIUrl":"https://doi.org/10.1109/SSCI47803.2020.9308464","url":null,"abstract":"The commonly used methodology for the simulation of dynamic problems formulates them as intervals of static problems, in which the change occurs between two successive intervals. This study proposes a more practically sound formulation of steadily changing dynamic problems, a class of dynamic problems in which the problem landscape continuously, but smoothly, changes over time. The new formulation provides more flexibility for a dynamic optimizer to choose the trade-off between the change frequency and the change severity while the change rate is prescribed by the actual problem. Besides, this study introduces a novel performance indicator for dynamic optimization methods. Unlike conventional ones, this indicator considers the real-time change in the actual problem during a time step and the period in which the best solution should be implemented. The practical importance of this formulation and the proposed performance indicator are studied on a few carefully designed controlled experiments. Subsequently, more comprehensive numerical simulations are performed to investigate the dependency of the optimal change frequency on the employed prediction method and test problem.","PeriodicalId":413489,"journal":{"name":"2020 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114364637","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
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