2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)最新文献
To solve the problem of privacy leakage of sensitive relationships caused by the spatial-temporal trajectory correlation of users in social networks, this paper proposes a privacy protection algorithm for sensitive relationships based on spatial-temporal trajectory features. In this paper, we propose a new measurement model for evaluating users' similarities, the basic idea of which is to calculate the similarity between users' sub-trajectories based on spatial and temporal dimensions. The proposed privacy protection algorithm adopts a heuristic to evaluate the inference contribution and information loss caused by data modification in order to protect sensitive relationship privacy meanwhile maintaining the trajectory data utility. We also provide the security analysis and theoretically prove the availability of the proposed algorithm. Based on the real social network data, the experimental results show that the proposed algorithm is efficient and could achieve high data utility.
{"title":"Spatio-Temporal Trajectory Features Based Sensitive Relationship Protection","authors":"Xiangyu Liu, Yifan Shen, Xiufeng Xia, Jiajia Li, Chuanyu Zong, Rui Zhu","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00049","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00049","url":null,"abstract":"To solve the problem of privacy leakage of sensitive relationships caused by the spatial-temporal trajectory correlation of users in social networks, this paper proposes a privacy protection algorithm for sensitive relationships based on spatial-temporal trajectory features. In this paper, we propose a new measurement model for evaluating users' similarities, the basic idea of which is to calculate the similarity between users' sub-trajectories based on spatial and temporal dimensions. The proposed privacy protection algorithm adopts a heuristic to evaluate the inference contribution and information loss caused by data modification in order to protect sensitive relationship privacy meanwhile maintaining the trajectory data utility. We also provide the security analysis and theoretically prove the availability of the proposed algorithm. Based on the real social network data, the experimental results show that the proposed algorithm is efficient and could achieve high data utility.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125076725","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}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00105
Yeisol Yoo, J. S. Yoo
Radio Frequency Identification (RFID) technology is used in many applications for monitoring object movement. The use of RFID in supply chain management systems enables to track the movement of products from suppliers to warehouses, store backrooms, and eventually points of sale. The vast amount of data resulting from the proliferation of RFID readers and tags poses challenges for data management and analytics. RFID data warehousing can enhance data quality and consistency, and give great potential benefits for Online Analytical Processing (OLAP) applications. Traditional data warehouses are built primarily on relational database management systems. However, the size of RFID data being collected and analyzed in the industry for business intelligence is growing rapidly, making traditional warehousing solutions prohibitively expensive. Hive is an open-source data warehousing solution built on top of Hadoop which is a popular Big Data computing framework. This paper presents alternative RFID data warehouse designs which can handle a large amount of RFID data and support a variety of OLAP queries. The proposed approaches are implemented on Hive and evaluated for query performance in cloud computing environment.
{"title":"RFID Data Warehousing and OLAP with Hive","authors":"Yeisol Yoo, J. S. Yoo","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00105","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00105","url":null,"abstract":"Radio Frequency Identification (RFID) technology is used in many applications for monitoring object movement. The use of RFID in supply chain management systems enables to track the movement of products from suppliers to warehouses, store backrooms, and eventually points of sale. The vast amount of data resulting from the proliferation of RFID readers and tags poses challenges for data management and analytics. RFID data warehousing can enhance data quality and consistency, and give great potential benefits for Online Analytical Processing (OLAP) applications. Traditional data warehouses are built primarily on relational database management systems. However, the size of RFID data being collected and analyzed in the industry for business intelligence is growing rapidly, making traditional warehousing solutions prohibitively expensive. Hive is an open-source data warehousing solution built on top of Hadoop which is a popular Big Data computing framework. This paper presents alternative RFID data warehouse designs which can handle a large amount of RFID data and support a variety of OLAP queries. The proposed approaches are implemented on Hive and evaluated for query performance in cloud computing environment.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116032974","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}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00131
Jianjian Yang, Xinzhou Cheng, Kun Chao, Yunyun Wang, Lexi Xu, Jie Gao
In the past thirty years, China experiences fast development in terms of economic and technology. This leads to the frequent exchange and communication among different cities. Specifically, meetings, sports, and industry exchanges at various levels are becoming more frequent and popular. Above events have significant impact on the city, hence, government/organizer should quantitatively evaluate the impact of events. Based on the various data of telecom operators, this paper proposes an insight scheme for large-scale events of the city. The proposed scheme can analyze the changes of the users scale and the business volume. In addition, this scheme also analyzes the aggregation areas of users before and after events and other characteristics. Especially, for the characteristics of external users from other cities, the proposed scheme can provide the data analysis results, in this way to support both the organizer and the government of the host city. Finally, the organizer and the government can provide good services.
{"title":"An Insight Scheme for Large-Scale Events Based on Telecom Operators Data","authors":"Jianjian Yang, Xinzhou Cheng, Kun Chao, Yunyun Wang, Lexi Xu, Jie Gao","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00131","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00131","url":null,"abstract":"In the past thirty years, China experiences fast development in terms of economic and technology. This leads to the frequent exchange and communication among different cities. Specifically, meetings, sports, and industry exchanges at various levels are becoming more frequent and popular. Above events have significant impact on the city, hence, government/organizer should quantitatively evaluate the impact of events. Based on the various data of telecom operators, this paper proposes an insight scheme for large-scale events of the city. The proposed scheme can analyze the changes of the users scale and the business volume. In addition, this scheme also analyzes the aggregation areas of users before and after events and other characteristics. Especially, for the characteristics of external users from other cities, the proposed scheme can provide the data analysis results, in this way to support both the organizer and the government of the host city. Finally, the organizer and the government can provide good services.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121195840","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}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00115
Xiangbin Shi, Jingyuan Tan, Deyuan Zhang
The indoor wheeled robot is widely used in research, industrial manufacturing, and service industries. For the positioning process of indoor wheeled mobile robots, the data from a single sensor is not reliable and accurate. The traditional solution to this problem is to use the extended Kalman filter (EKF) method, which suffers from linearization error and accumulation error. To tackle these problems, we propose Linear transformation error elimination extended Kalman filter(TEKF) to fuse multiple sensors. Firstly, the data of the sensors of the odometer, Inertial measurement unit(IMU) and lidar are collected and preprocessed, and a complementary filtering method is proposed to obtain the angular velocity. Secondly, the second-order Taylor series expansion is performed on the state and the observation equation, which overcomes the linearization error and improves the accuracy of data fusion. Finally, the backtracking processing method is adopted to eliminate the accumulated error and enhance the environmental adaptability. The experimental results of the real indoor wheeled robot shows that TEKF can effectively improve the accuracy of data fusion and ensure that the indoor wheeled robot can be more accurately positioned.
{"title":"Indoor Wheeled Robot Positioning Algorithm Based on Extended Kalman Filter","authors":"Xiangbin Shi, Jingyuan Tan, Deyuan Zhang","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00115","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00115","url":null,"abstract":"The indoor wheeled robot is widely used in research, industrial manufacturing, and service industries. For the positioning process of indoor wheeled mobile robots, the data from a single sensor is not reliable and accurate. The traditional solution to this problem is to use the extended Kalman filter (EKF) method, which suffers from linearization error and accumulation error. To tackle these problems, we propose Linear transformation error elimination extended Kalman filter(TEKF) to fuse multiple sensors. Firstly, the data of the sensors of the odometer, Inertial measurement unit(IMU) and lidar are collected and preprocessed, and a complementary filtering method is proposed to obtain the angular velocity. Secondly, the second-order Taylor series expansion is performed on the state and the observation equation, which overcomes the linearization error and improves the accuracy of data fusion. Finally, the backtracking processing method is adopted to eliminate the accumulated error and enhance the environmental adaptability. The experimental results of the real indoor wheeled robot shows that TEKF can effectively improve the accuracy of data fusion and ensure that the indoor wheeled robot can be more accurately positioned.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126902118","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}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00042
Lexi Xu, Xuefeng Chen, Liang Zhao, Xin Hu, Nan Jiang, Yuting Luan, Xinzhou Cheng, Jie Gao
Due to the diverse services and high rate requirements of telecom users, mobile cellular systems envisage the challenges of high resource usage, especially the base station (BS) in the hot-spot area. This paper investigates on telecom big data of LTE/5G systems, and then we design a telecom big data assisted comprehensive BS resource analysis (CBSRA) algorithm. CBSRA algorithm considers six categories of resource data/indicators. Then, CBSRA algorithm judges the usage level of each indicator. Finally, CBSRA algorithm takes the comprehensive analysis and outputs the results. We implement the CBSRA algorithm in a realistic cellular system in China, and the proposed algorithm can assist operator to effectively detect BS with high resource usage.
{"title":"Telecom Big Data Assisted BS Resource Analysis for LTE/5G Systems","authors":"Lexi Xu, Xuefeng Chen, Liang Zhao, Xin Hu, Nan Jiang, Yuting Luan, Xinzhou Cheng, Jie Gao","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00042","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00042","url":null,"abstract":"Due to the diverse services and high rate requirements of telecom users, mobile cellular systems envisage the challenges of high resource usage, especially the base station (BS) in the hot-spot area. This paper investigates on telecom big data of LTE/5G systems, and then we design a telecom big data assisted comprehensive BS resource analysis (CBSRA) algorithm. CBSRA algorithm considers six categories of resource data/indicators. Then, CBSRA algorithm judges the usage level of each indicator. Finally, CBSRA algorithm takes the comprehensive analysis and outputs the results. We implement the CBSRA algorithm in a realistic cellular system in China, and the proposed algorithm can assist operator to effectively detect BS with high resource usage.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127194511","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}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00113
Yunqing Guan, Qingsheng Li, Y. Tian
This paper designs and develops an Environmental Data News Generation (EDNG) system of Internet of things data acquisition and generation that can automatically collect data such as environmental temperature, humidity and light intensity in a region and automate broadcast by data news for healthcare. The system is based on digital data collection, Internet of things, embedded development and other technologies. Through designing hardware and software such as the design of networking data acquisition devices, the establishment of cloud forwarding servers, the development of terminal WeChat mini-programs and data news acquisition systems, the problem of automatic data collection, fusion generation and accurate and efficient reporting of regional environmental data news is solved. At the same time, through the research of regional environmental data news gathering and generation technology, the functions of automation of environmental data collection and real evolution of news broadcast were realized. The accuracy of data acquisition and the speed of news reporting are improved, and an effective strategy is provided for the automatic generation of other data news.
{"title":"IoT-Based Environmental Data News Generation System for Healthcare","authors":"Yunqing Guan, Qingsheng Li, Y. Tian","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00113","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00113","url":null,"abstract":"This paper designs and develops an Environmental Data News Generation (EDNG) system of Internet of things data acquisition and generation that can automatically collect data such as environmental temperature, humidity and light intensity in a region and automate broadcast by data news for healthcare. The system is based on digital data collection, Internet of things, embedded development and other technologies. Through designing hardware and software such as the design of networking data acquisition devices, the establishment of cloud forwarding servers, the development of terminal WeChat mini-programs and data news acquisition systems, the problem of automatic data collection, fusion generation and accurate and efficient reporting of regional environmental data news is solved. At the same time, through the research of regional environmental data news gathering and generation technology, the functions of automation of environmental data collection and real evolution of news broadcast were realized. The accuracy of data acquisition and the speed of news reporting are improved, and an effective strategy is provided for the automatic generation of other data news.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125804333","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}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00065
Jingdong Liu, Won-Ho Choi, Fei Hao
With the continuous development of China's social economy, people's living standards continue to improve, the people's investment in leisure and entertainment continues to increase, among which film has become one of the people's first choice for leisure and entertainment. In recent years, the domestic film market has been expanding, at the same time, western films represented by Hollywood have also produced a fierce impact on domestic films. How to improve the local film quality, improve the local film box office level has become a hot issue. In this paper, 152 domestic films in 2018 are selected as research objects, and Ordinary Least Square and TQAR models are adopted to analyze the factors affecting the box office of films, so as to provide effective references for effectively reducing the cost of film investment and improving the market value of domestic films.
{"title":"Research on the Influencing Factors of Film Box Office Based on Ordinary Least Square and Threshold Quantile Autoregressive Model","authors":"Jingdong Liu, Won-Ho Choi, Fei Hao","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00065","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00065","url":null,"abstract":"With the continuous development of China's social economy, people's living standards continue to improve, the people's investment in leisure and entertainment continues to increase, among which film has become one of the people's first choice for leisure and entertainment. In recent years, the domestic film market has been expanding, at the same time, western films represented by Hollywood have also produced a fierce impact on domestic films. How to improve the local film quality, improve the local film box office level has become a hot issue. In this paper, 152 domestic films in 2018 are selected as research objects, and Ordinary Least Square and TQAR models are adopted to analyze the factors affecting the box office of films, so as to provide effective references for effectively reducing the cost of film investment and improving the market value of domestic films.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124344251","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}
Human multi-target tracking in video is an important issue in the field of computer vision. It is necessary to detect the target on each frame, and to connect the targets of all frames into a target sequence. For target matching among different frames, we propose a tracking algorithm for constructing object pose sequence(COPS) based on Openpose. The position status and the ORB feature of the target pose are dynamically weighted and fused into new features. Target pose is searched in the corresponding target pose sequence by comparing the new features between the target pose in the sequence and every pose in current frame. When the target pose is matched, the influence of the position feature on the pose similarity could be enhanced when the target motion is continuously detected. When the target scale changes too much, the method can expand the contribution of the ORB feature to the pose similarity comparison. The experiments of human multitarget tracking algorithm are carried out on the PoseTrack and MOT datasets, and the results show that the proposed tracking algorithm overcomes the problem of target matching between frames.
{"title":"Pose-Based Multi-Target Tracking","authors":"Xiangbin Shi, Xiaoyu Yang, Deyuan Zhang, Jing Bi, Zhaokui Li, Fang Liu","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00087","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00087","url":null,"abstract":"Human multi-target tracking in video is an important issue in the field of computer vision. It is necessary to detect the target on each frame, and to connect the targets of all frames into a target sequence. For target matching among different frames, we propose a tracking algorithm for constructing object pose sequence(COPS) based on Openpose. The position status and the ORB feature of the target pose are dynamically weighted and fused into new features. Target pose is searched in the corresponding target pose sequence by comparing the new features between the target pose in the sequence and every pose in current frame. When the target pose is matched, the influence of the position feature on the pose similarity could be enhanced when the target motion is continuously detected. When the target scale changes too much, the method can expand the contribution of the ORB feature to the pose similarity comparison. The experiments of human multitarget tracking algorithm are carried out on the PoseTrack and MOT datasets, and the results show that the proposed tracking algorithm overcomes the problem of target matching between frames.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124405327","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}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00096
Hongjian Li, Luoying Hao, Qieshi Zhang, Xiping Hu, Jun Cheng
In this paper, we proposed a practical and efficient algorithm based on conventional semi-direct monocular visual odometry (SVO) algorithm, which mainly aims at the future application of the Simultaneous Localization and Mapping (SLAM) for embedded or mobile platforms such as robots and wearable devices. By applying the velocity momentum during the initial pose estimation, we present a novel algorithm for obtaining the initial pose, which is closer to the true value and more effective to solving the limitation of non-convergence in most existing approaches. A sparse image alignment module is also proposed to rectify the pose offset occurred at the corner, by elaborately resetting the relative pose at the location with large photometric error. The proposed lifted semi-direct monocular visual odometry has been extensively evaluated on benchmark dataset. The experimental result demonstrates that our method can explicitly generate the accurate initial poses without reducing the speed.
{"title":"A Lifted Semi-Direct Monocular Visual Odometry","authors":"Hongjian Li, Luoying Hao, Qieshi Zhang, Xiping Hu, Jun Cheng","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00096","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00096","url":null,"abstract":"In this paper, we proposed a practical and efficient algorithm based on conventional semi-direct monocular visual odometry (SVO) algorithm, which mainly aims at the future application of the Simultaneous Localization and Mapping (SLAM) for embedded or mobile platforms such as robots and wearable devices. By applying the velocity momentum during the initial pose estimation, we present a novel algorithm for obtaining the initial pose, which is closer to the true value and more effective to solving the limitation of non-convergence in most existing approaches. A sparse image alignment module is also proposed to rectify the pose offset occurred at the corner, by elaborately resetting the relative pose at the location with large photometric error. The proposed lifted semi-direct monocular visual odometry has been extensively evaluated on benchmark dataset. The experimental result demonstrates that our method can explicitly generate the accurate initial poses without reducing the speed.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128782705","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}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00046
Natasha Niaz, R. Ahmad, Waqas Ahmed, Shahryar Saleem, Liang Zhao
Phantom cellular networks are the key enabling technology that can increase the capacity of cellular networks by adding a new data plane to an existing macro cell control plane. In this paper, performance of Energy Harvesting (EH) enabled phantom cells operating under a macro cell is analyzed in terms of sum capacity and energy efficiency (EE). The Phantom Base Stations (PBSs) provide capacity gains by offloading users from Macro Base Station (MBS). However, due to the reuse of the same resource blocks by all PBSs, co-channel interference exists between PBSs, which limits the capacity gains. Furthermore, an excessive amount of energy is consumed by the PBSs to overcome this co-channel interference. To minimize the above mentioned capacity limiting problem of co-channel interference and energy consumption, semi-static ON/OFF switching schemes are evaluated. Interference Aware (IA) and Traffic Aware (TA) ON/OFF switching schemes are compared with Random ON/OFF and macro cell only schemes. Simulation results show that when the numbers of offloaded users are high, the TA scheme performs better in terms of capacity, with energy savings up to 90%. For both the IA and TA switching schemes, the gains are dependent on user distribution within the network.
{"title":"Semi-Static ON/OFF Switching Schemes for Energy Efficient Phantom Cellular Networks","authors":"Natasha Niaz, R. Ahmad, Waqas Ahmed, Shahryar Saleem, Liang Zhao","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00046","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00046","url":null,"abstract":"Phantom cellular networks are the key enabling technology that can increase the capacity of cellular networks by adding a new data plane to an existing macro cell control plane. In this paper, performance of Energy Harvesting (EH) enabled phantom cells operating under a macro cell is analyzed in terms of sum capacity and energy efficiency (EE). The Phantom Base Stations (PBSs) provide capacity gains by offloading users from Macro Base Station (MBS). However, due to the reuse of the same resource blocks by all PBSs, co-channel interference exists between PBSs, which limits the capacity gains. Furthermore, an excessive amount of energy is consumed by the PBSs to overcome this co-channel interference. To minimize the above mentioned capacity limiting problem of co-channel interference and energy consumption, semi-static ON/OFF switching schemes are evaluated. Interference Aware (IA) and Traffic Aware (TA) ON/OFF switching schemes are compared with Random ON/OFF and macro cell only schemes. Simulation results show that when the numbers of offloaded users are high, the TA scheme performs better in terms of capacity, with energy savings up to 90%. For both the IA and TA switching schemes, the gains are dependent on user distribution within the network.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"242 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132548023","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}
2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)
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