Xin Liu, Xianzhong Zhou, Tianqi Ji, Han Bai, Huaxiong Li
{"title":"Combining eye movements for semantic image classification","authors":"Xin Liu, Xianzhong Zhou, Tianqi Ji, Han Bai, Huaxiong Li","doi":"10.1109/ICNSC.2017.8000186","DOIUrl":"https://doi.org/10.1109/ICNSC.2017.8000186","url":null,"abstract":"Nowadays, the “semantic gap” problems have greatly limited development of image classification. The key to this problem is to get semantic information of the images. A semantic image feature extraction method is proposed in this paper, in which eye movement information is integrated. Firstly, the underlying visual features of images are extracted. Secondly, weighed feature vectors of images are constructed based on eye movements and underlying visual features. To evaluate the effectiveness of the integrated feature vectors in classification, both support vector machine and k - nearest neighbor algorithm are adopted. Experimental results demonstrate the effectiveness and efficiency of the proposed methods.","PeriodicalId":145129,"journal":{"name":"2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114339616","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}
{"title":"Salient locations search based on human visual attention: An experimental analysis","authors":"Wenting Hu, Pei Yang, Xianzhong Zhou, Zhen Liu, Huaxiong Li, Xianjun Zhu","doi":"10.1109/icnsc.2017.8000167","DOIUrl":"https://doi.org/10.1109/icnsc.2017.8000167","url":null,"abstract":"","PeriodicalId":145129,"journal":{"name":"2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115037425","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}
{"title":"Performance study for a novel vertical axis wind turbine based on simulation analysis","authors":"Chao Ma, Lei Song, Ming-Zhu Zhang","doi":"10.1109/ICNSC.2017.8000151","DOIUrl":"https://doi.org/10.1109/ICNSC.2017.8000151","url":null,"abstract":"The drag-type vertical axis wind turbines (VAWTs) have advantages of simple structure, self-starting at low wind speed and low cost, but they show low wind energy conversion efficiencies. A novel vertical axis wind turbine is proposed aiming to improve the disadvantage of the traditional wind turbines based on bionic principle in this paper. The structure of the novel vertical axis wind rotor is designed by combining traditional Savonius wind rotor structure and fish's ridge structure. Aerodynamic performance of the novel wind rotor and a traditional Savonius wind rotor are numerically explored and predicted by numerical simulation method for their non-linear two-dimensional unsteady flows. Performance comparison of the two wind rotors is also carried out. The results show that the novel wind rotor has better performance for torque and power coefficient on lower tip speed ratio (TSR) conditions than traditional Savonius rotor. Based on the simulation analysis of the two different types of wind rotors, we present the approach of changing and reconstructing different curvatures to obtain higher efficiency.","PeriodicalId":145129,"journal":{"name":"2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115432438","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}
{"title":"Simulation-based verification of system requirements: An integrated solution","authors":"F. Aiello, A. Garro, Y. Lemmens, S. Dutré","doi":"10.1109/ICNSC.2017.8000180","DOIUrl":"https://doi.org/10.1109/ICNSC.2017.8000180","url":null,"abstract":"Modeling of system properties deals with formally expressing constraints and requirements that influence and determine the structure and behavior of a system. System Property Models enable the verification of system properties through real or simulated experiments so as to support their evaluation during system design and their monitoring during system operation. However, several challenges should be addressed to effectively handle systems properties with the support of an integrated tool-chain. In this context, the paper presents the concrete experimentation of a promising solution that enables the formal modeling of requirements in Modelica and their subsequent simulation-based verification. The solution is applied to evaluate different design variants of a trailing-edge high-lift system. In particular, two ways to feed the requirements model are explored: in an early phase, data series are used to evaluate the requirements themselves; then a co-simulation of the requirements model with the 3D-model of the system is used to evaluate and identify what design variants best meet the system requirements.","PeriodicalId":145129,"journal":{"name":"2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122551914","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}
{"title":"Topology upgrading method for energy balance in scale-free wireless sensor networks","authors":"Xiuwen Fu, Yongsheng Yang, Wenfeng Li, G. Fortino","doi":"10.1109/ICNSC.2017.8000090","DOIUrl":"https://doi.org/10.1109/ICNSC.2017.8000090","url":null,"abstract":"Scale-free can be seemed as one of the most impacting discoveries in complex networks theory and has already been successfully proved to be highly effective in constructing error-tolerant topology structures of wireless sensor networks (WSNs). As in scale-free WSNs, a few key nodes possess most connections, requiring them to take excessive message-relay tasks. Due to this reason, the energy of these nodes would be depleted much earlier than other sensor nodes, threatening the lifetime of the entire network. In this paper, we propose a topology upgrading method by referencing the concept of small-world. In our method, we present a novel node centrality metric-Directed Betweeness Centrality (DBC) to locate the key nodes and a network centrality metric- Directed Betweeness Network Entropy (DBNE) to measure the energy balance level of the network. Based on DBNE, we propose a shortcut deploying scheme to promote the energy distribution of the network more uniform. The simulations have shown that our scheme is able to improve the energy balance level of the network significantly.","PeriodicalId":145129,"journal":{"name":"2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123713082","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}
F. Cicirelli, A. Guerrieri, G. Spezzano, Andrea Vinci, O. Briante, A. Iera, G. Ruggeri
{"title":"An edge-based approach to develop large-scale smart environments by leveraging SIoT","authors":"F. Cicirelli, A. Guerrieri, G. Spezzano, Andrea Vinci, O. Briante, A. Iera, G. Ruggeri","doi":"10.1109/ICNSC.2017.8000182","DOIUrl":"https://doi.org/10.1109/ICNSC.2017.8000182","url":null,"abstract":"Large-scale Smart Environments (LSEs) are open and dynamic systems where issues related to scalability and interoperability require to be carefully addressed. Moreover, as such systems typically extend on a wide area and include a huge number of interacting devices, aspects concerning services and objects discovery and reputation assessment require being managed. Despite the increasing interest in this topic, there is a lack of approaches for developing LSEs. This paper proposes an agent-based approach for the development of LSEs which leverages Edge Computing and Social Internet of Things paradigms in order to address the above mentioned issues. The effectiveness of such an approach is assessed through a case study involving a Smart School District environment.","PeriodicalId":145129,"journal":{"name":"2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130310580","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}
{"title":"Cognitive channel selection for Wireless Sensor communications","authors":"M. Chincoli, P. D. Boef, A. Liotta","doi":"10.1109/ICNSC.2017.8000192","DOIUrl":"https://doi.org/10.1109/ICNSC.2017.8000192","url":null,"abstract":"Wireless sensor networks (WSNs) are dense networks affected by severe interference among many devices. They operate in the unlicensed 2.4 GHz band that is shared by different technologies, such as Bluetooth and WiFi, which add interference at higher transmission power. For this reason, interference is an important factor to avoid for reliable communications. Due to the unpredictable nature of the wireless medium, the 802.15.4e standard has introduced the possibility to schedule a channel in frequency using Time Division Multiple Access (TDMA), but the selection of the optimal channel is still an ongoing research. In this paper, a Multilayered Feedforward Neural Network (MFNN) is proposed as a possible solution to make predictions about which channel can offer low latency and high throughput at any given time slot. Controlled experiments were conducted in an anechoic chamber, considering the two scenarios of no interference and interference incurred by other sensors and WiFi. Results show that MFNN is a valid solution, obtaining performance comparable to the best case scenario.","PeriodicalId":145129,"journal":{"name":"2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128300070","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}
{"title":"Towards Internet of Underground Things in smart lighting: A statistical model of wireless underground channel","authors":"Abdul Salam, M. Vuran, S. Irmak","doi":"10.1109/ICNSC.2017.8000155","DOIUrl":"https://doi.org/10.1109/ICNSC.2017.8000155","url":null,"abstract":"The Internet of Underground Things (IOUT) has many applications in the area of smart lighting. IOUT enables communications in smart lighting through underground (UG) and aboveground (AG) communication channels. In IOUT communications, an in-depth analysis of the wireless underground channel is important to design smart lighting solutions. In this paper, based on the empirical and the statistical analysis, a statistical channel model for the UG channel has been developed. The parameters for the statistical tapped-delay-line model are extracted from the measured power delay profiles (PDP). The PDP of the UG channel is represented by the exponential decay of the lateral, direct, and reflected waves. The developed statistical model can be used to generate the channel impulse response, and precisely predicts the UG channel RMS delay spread, coherence bandwidth, and propagation loss characteristics in different conditions. The statistical model also shows good agreement with the empirical data, and is useful for tailored IOUT solutions in the area of smart lighting.","PeriodicalId":145129,"journal":{"name":"2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC)","volume":"167 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121558328","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}
Yan Liang, Yizheng Tao, Ning Feng, Zhenjing Wan, Feng Xu, Xue Jiang, Shan Gao
{"title":"Aggregating sentence-level features for Chinese near-duplicate document detection","authors":"Yan Liang, Yizheng Tao, Ning Feng, Zhenjing Wan, Feng Xu, Xue Jiang, Shan Gao","doi":"10.1109/ICNSC.2017.8000087","DOIUrl":"https://doi.org/10.1109/ICNSC.2017.8000087","url":null,"abstract":"Detecting near-duplicate documents efficiently is an indispensable capability for many applications, such as searching engines, information retrieval systems, and recommendation systems. In this paper, we propose a novel content presentation method for near-duplicate document detection from a large collection of Chinese documents. The proposed method, called multi-aggregation fingerprint (MAF), consists of sentence-level feature extraction and multi-feature aggregation. Compared with terms, sentences are more representative and contain more abundant and integrated information. Thus, we extract the crucial information of sentences to form the sentence features. To improve the accuracy and efficiency of near-duplicate document detection, we exploit both holistic characteristics of sentence features in the dataset and the statistic information of sentence features belonging to a document. Accordingly, we split the sentence feature space based on the distribution of features in the dataset. Each sentence feature is assigned to the nearest partition of the feature space, and multiple sentence features are aggregated into a compact and global fingerprint. Experimental results show the proposed MAF method can produce competitive results on the Chinese document dataset.","PeriodicalId":145129,"journal":{"name":"2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116017469","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}
{"title":"Storage coordination and peak-shaving operation in urban areas with high renewable penetration","authors":"Nina Voulis, M. Warnier, F. Brazier","doi":"10.1109/icnsc.2017.8000148","DOIUrl":"https://doi.org/10.1109/icnsc.2017.8000148","url":null,"abstract":"As renewable power generation gains importance, balancing of power demand and supply becomes more and more challenging. This paper addresses this challenge by exploring the potential of individually-owned storage units in decentralised power systems with a high share of renewables. The focus is on the influence of coordination and peak-shaving operation of these individual units in realistic urban areas. Currently extensive amount of research exits on specific applications related to storage coordination. However, in these studies often simplified consumer models are used. This study considers a representative mixed residential and commercial neighbourhood in Amsterdam. The influence of storage coordination and peak-shaving operation on the neighbourhood's energy autonomy and on the peakiness of the power exchanged with the main grid are addressed. Results show that, compared to individual storage operation, coordinated storage operation increases renewable energy utilisation by 39%, decreases the excess energy transferred to the grid by almost threefold and increases the neighbourhood self-sufficiency by 21%. Peak-shaving operation reduces the highest power peak of the year by 55%. These results are statistically significant (p-value < 10−4). Thus, in realistic urban areas storage coordination improves local energy autonomy, while peak-shaving operation reduces peaks in power flows exchanged with the main grid.","PeriodicalId":145129,"journal":{"name":"2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126245988","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}