2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)最新文献_第3页

Design of a Robust Controller Using Real Twisting Algorithm for a Fixed Wing Airplane 基于实扭转算法的固定翼飞机鲁棒控制器设计

2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI) Pub Date : 2019-02-01 DOI: 10.1109/KBEI.2019.8734903

M. Navabi, N. Davoodi

引用次数: 5

A Model for Utilizing the Potential of Gamification in Learning 一种利用游戏化学习潜力的模式

2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI) Pub Date : 2019-02-01 DOI: 10.1109/KBEI.2019.8735001

Sara Nazififard, S. Jafari, H. Z. Matin, H. Yazdani

{"title":"A Model for Utilizing the Potential of Gamification in Learning","authors":"Sara Nazififard, S. Jafari, H. Z. Matin, H. Yazdani","doi":"10.1109/KBEI.2019.8735001","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8735001","url":null,"abstract":"In learning contexts, gamification is a technique to motivate learners and enhance their participation in learning activities by applying game elements and components. But it still pays little attention to using gamification in Adult learning activities. Through a systematic literature review, this study investigates the literature on the motivational and behavioral theories underlying gamification in the context of learning to synthesize the essential factors to improve learning outcomes. This paper presents a conceptual model of gamification in a learning context. A theory-driven model was created in order to categorize into a multi-dimensional model. In addition, this model can be extended to any kind of games not only educational games because the whole gaming experience is based on the same theory as human learning. It originates from behavioral science and it has progressed well-stablished learning algorithm. By investigating and synthesizing the earlier studies and categorizing them in accordance with a contemporary approach, a conceptual model for gamification of adult learning has been proposed. Then in order to validate and test this theory-driven model should be implemented and tested in experimental studies involving organization employees.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126050762","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

Modified Distributed Bee Algorithm in Task Allocation of Swarm Robotic 群机器人任务分配中的改进分布式蜜蜂算法

2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI) Pub Date : 2019-02-01 DOI: 10.1109/KBEI.2019.8735026

Razieh Moradi, H. Nezamabadi-pour, Mohadeseh Soleimanpour

引用次数: 0

A Large-Margin Approach for Multi-Label Classification Based on Correlation Between Labels 基于标签相关性的多标签大间距分类方法

2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI) Pub Date : 2019-02-01 DOI: 10.1109/KBEI.2019.8735036

Arman Yanpi, M. Taheri

{"title":"A Large-Margin Approach for Multi-Label Classification Based on Correlation Between Labels","authors":"Arman Yanpi, M. Taheri","doi":"10.1109/KBEI.2019.8735036","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8735036","url":null,"abstract":"Multi label classification is a challenging task in machine learning concerned with assigning a sample to a subset of available label set. Meaning, a sample can belong to multiple labels. Furthermore, high dimensionality of data and complex correlation between labels makes it even more interesting. For this reason, it attracted many researchers in recent years. classifier-chains (CC), one of well-known methods for multi label classification which is based on binary relevance (BR) method, incorporates label correlation by assuming an order for labels and inserting previous label outputs in feature space and achieves higher performance while still retaining relatively low time complexity. But using predicted labels as features might not be very interpretable with regards to integrating label correlation into the model, especially considering there could be different types of features in a dataset. In this paper, we propose an approach for using correlation among labels based on structure of CC by defining a large-margin model between two predicted labels. Thus directly exploiting the correlation between them in a more interpretable way. The proposed approach is evaluated using 9 multi label datasets and 2 evaluation metrics. Empirical experiments show promising results and demonstrate the effectiveness of proposed method against classifier chains algorithm.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"59 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133218324","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

A Prototype Auction-based Mechanism for Computation Offloading in Fog-cloud Environments 雾云环境下基于拍卖的计算卸载原型机制

2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI) Pub Date : 2019-02-01 DOI: 10.1109/KBEI.2019.8734918

R. Besharati, Mohammad Hossein Rezvani

{"title":"A Prototype Auction-based Mechanism for Computation Offloading in Fog-cloud Environments","authors":"R. Besharati, Mohammad Hossein Rezvani","doi":"10.1109/KBEI.2019.8734918","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8734918","url":null,"abstract":"One of the significant issues in fog computing environments is computation offloading. In order to do this process, the communications between the fog and cloud nodes should be investigated. In the literature, a great body of research exists in which the researchers proposed numerous optimization methods regard the subject of offloading in fog networks. These proposals have been implemented taking into account service level agreements (SLAs). In this paper, we propose an optimization method for modeling the interactions of offloading process using rich theory of microeconomics. We model the offloading interactions based on auction mechanism. Then, we modelled and formulated the communications between fog nodes and the cloud entity. Our model takes into account the specifications and limitations of the underlying physical infrastructure such as paths and capacity of each path. These paths are used during computation offloading operations. In our proposed auction economy, the bandwidth of physical links plays the role of the commodity. Finally, the auction is run between the cloud and fog nodes as provider and consumer respectively.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133682538","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: 14

Novel Broadband 3U CubeSat Reflectarray Antenna 新型宽带3U立方体卫星反射天线

2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI) Pub Date : 2019-02-01 DOI: 10.1109/KBEI.2019.8735040

B. Mohammadi, J. Nourinia, C. Ghobadi, F. Alizadeh, Seyed Vahid Masuminia

引用次数: 1

State Feedback Control Design of Cars Wings in Order to Improve Road-Holding on Corners of Roads 为改善弯道握持力的汽车机翼状态反馈控制设计

2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI) Pub Date : 2019-02-01 DOI: 10.1109/KBEI.2019.8735068

Mahdi Salehi, F. Farivar

{"title":"State Feedback Control Design of Cars Wings in Order to Improve Road-Holding on Corners of Roads","authors":"Mahdi Salehi, F. Farivar","doi":"10.1109/KBEI.2019.8735068","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8735068","url":null,"abstract":"Car wing has many capabilities to work on and benefit from. There are different types of wings and spoilers in sport cars that are being used to help having better acceleration, braking, etc. Generally after aerodynamic analysis of wings or rear spoilers, and simulation the second step is to find the best control system to achieve maximum advantages from wings and spoilers. In other words, the wing working time is during car’s cornering and turning on different angels, braking or accelerating that is the time for a control system to operate. In this paper the goal is to implement state feedback tracking control system and optimization of the system by LQR method around equilibrium and operating points of the system specially during cornering of the vehicle. So to obtain the goal, the first step is to review previous works and benefit from. Then the second section is considered for mathematical calculation and the system dynamics plus design of mechanical components and assembled system by CATIA software. After that the control model is extracted for the control system. Furthermore the control system, which is tracking control system, is designed, implemented and the results are shown by figures and plots. The final step is to optimize the control system by LQR optimal control method and the results are compared to other methods. In this article the control system is simulated by MATLAB software.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"296 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123460742","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

Automatic vessel wall segmentation of IVOCT images using region detection EREL algorithm 基于区域检测EREL算法的IVOCT图像血管壁自动分割

2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI) Pub Date : 2019-02-01 DOI: 10.1109/KBEI.2019.8734974

Niyoosha Dallalazar, A. Ayatollahi, M. Habibi, A. Kermani

引用次数: 0

Adaptive fuzzy nonlinear sliding-mode controller for a car-like robot 类车机器人的自适应模糊非线性滑模控制器

2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI) Pub Date : 2019-02-01 DOI: 10.1109/KBEI.2019.8734995

Masoud Shirzadeh, M. Shojaeefard, A. Amirkhani, H. Behroozi

引用次数: 10

Companies Products Demands Forecasting using Learning Fuzzy Cellular Automata Model. Case Study: Barij Essence Pharmaceutical Company 基于学习模糊元胞自动机模型的企业产品需求预测。案例研究:百日香精制药公司

2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI) Pub Date : 2019-02-01 DOI: 10.1109/KBEI.2019.8735063

M. Golchin

引用次数: 0