2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)最新文献_第9页

Formulation of a simple model to estimate road surface roughness condition from Android smartphone sensors 基于Android智能手机传感器估算路面粗糙度的简单模型

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827694

Viengnam Douangphachanh, H. Oneyama

引用次数: 14

Parkinson Disease Classification based on binary coded genetic algorithm and Extreme learning machine 基于二进制编码遗传算法和极限学习机的帕金森病分类

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827649

V. Sachnev, Hyoung-Joong Kim

引用次数: 7

Automatic recognition of oyster racks in the aerial image 航拍图像中牡蛎架的自动识别

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827688

Wu-Ja Lin, Yi-Xiang Huang

引用次数: 2

Mobile target tracking and data fusion using dual-interacting multiple model system 基于双交互多模型系统的移动目标跟踪与数据融合

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827699

C. Wann, Jia-Yu Shiu

引用次数: 0

Efficient binary consensus in randomized and noisy environments 随机和噪声环境下的有效二元一致

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827594

A. Gogolev, L. Marcenaro

引用次数: 1

Image deblurring for navigation systems of vision impaired people using sensor fusion data 基于传感器融合数据的视障人士导航系统图像去模糊

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827599

N. Rajakaruna, C. Rathnayake, Kit Yan Chan, I. Murray

{"title":"Image deblurring for navigation systems of vision impaired people using sensor fusion data","authors":"N. Rajakaruna, C. Rathnayake, Kit Yan Chan, I. Murray","doi":"10.1109/ISSNIP.2014.6827599","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827599","url":null,"abstract":"Image deblurring is a key component in vision based indoor/outdoor navigation systems; as blurring is one of the main causes of poor image quality. When images with poor quality are used for analysis, navigation errors are likely to be generated. For navigation systems, camera movement mainly causes blurring, as the camera is continuously moving by the body movement. This paper proposes a deblurring methodology that takes advantage of the fact that most smartphones are equipped with 3-axis accelerometers and gyroscopes. It uses data of the accelerometer and gyroscope to derive a motion vector calculated from the motion of the smartphone during the image-capturing period. A heuristic method, namely particle swarm optimization, is developed to determine the optimal motion vector, in order to deblur the captured image by reversing the effect of motion. Experimental results indicated that deblurring can be successfully performed using the optimal motion vector and that the deblurred images can be used as a readily approach to object and path identification in vision based navigation systems, especially for blind and vision impaired indoor/outdoor navigation. Also, the performance of proposed method is compared with the commonly used deblurring methods. Better results in term of image quality can be achieved. This experiment aims to identify issues in image quality including low light conditions, low quality images due to movement of the capture device and static and moving obstacles in front of the user in both indoor and outdoor environments. From this information, image-processing techniques to will be identified to assist in object and path edge detection necessary to create a guidance system for those with low vision.","PeriodicalId":269784,"journal":{"name":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123407072","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: 10

Improving the accuracy of simulation models for localization schemes 提高定位方案仿真模型的精度

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827654

Walid M. Ibrahim, N. Abuali, A. Taha, H. Hassanein

{"title":"Improving the accuracy of simulation models for localization schemes","authors":"Walid M. Ibrahim, N. Abuali, A. Taha, H. Hassanein","doi":"10.1109/ISSNIP.2014.6827654","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827654","url":null,"abstract":"Localization plays a substantial role in the future Internet, especially within the context of the Internet of Things (IoT). Increased dependence on devices and sensed data presses for more efficient and accurate localization schemes. In the IoT environment the area covered is large making it impossible to localize all devices and Sensor Nodes (SNs) using single-hop localization techniques. A solution to this problem is to use a multi-hop localization technique to estimate devices' positions. Simulating localization techniques for wireless sensor networks is required in order to reduce cost and study the difference between localization techniques easily especially if the simulated environment is large. Thus a realistic model is required to simulate the localization process as accurately as possible. Many multi-hop localization techniques use Received Signal Strength Indicator (RSSI) to estimate the distance between SNs. Our interest in this work is to enhance the validation of these schemes prior to deployment. Specifically, we propose the use of a more realistic model for generating RSSI values. The model is based on practical measurements and is validated through extensive simulation.","PeriodicalId":269784,"journal":{"name":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121486225","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

Using trajectory features for upper limb action recognition 基于轨迹特征的上肢动作识别

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827613

Xiaoting Wang, S. Suvorova, T. Vaithianathan, C. Leckie

引用次数: 6

Surface plasmon resonance based detection of human serum albumin as a marker for hepatocytes activity 基于表面等离子体共振的人血清白蛋白检测作为肝细胞活性的标志物

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827601

A. Henseleit, J. Stuermer, C. Pohl, Natalie Haustein, F. Sonntag, T. Bley, E. Boschke

{"title":"Surface plasmon resonance based detection of human serum albumin as a marker for hepatocytes activity","authors":"A. Henseleit, J. Stuermer, C. Pohl, Natalie Haustein, F. Sonntag, T. Bley, E. Boschke","doi":"10.1109/ISSNIP.2014.6827601","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827601","url":null,"abstract":"Techniques for monitoring cell cultures and fermentation processes not only enable prompt feedback to variations in critical parameters (e.g., media composition and metabolites) but further improve our understanding of the processes themselves. In this context, surface plasmon resonance (SPR) spectroscopy is one of the methods of choice. This technique exploits angle shifting to follow molecular interactions in real-time. Therefore, it allows samples to be characterized without additional molecular labels and time-consuming sample preparation. The immobilization of receptors onto the chip surface is one of the most challenging requirements in SPR. Especially for measurements in crude samples, it is crucial to achieve a sufficient immobilization level and block the remaining sensitive area to prevent nonspecific binding. In this article, we present a SPR-based detection system for human serum albumin (HSA). As HSA is exclusively synthesized in the liver, it can be used to characterize the specific activity of in vitro cultivated human hepatocytes. These can be cultivated in so-called multi-organ-chips, which have been developed by groups at the TU Berlin and Fraunhofer IWS for predictive preclinical substance evaluation.","PeriodicalId":269784,"journal":{"name":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131719240","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

Using ORMOCER®s as casting material for a 3D shape sensor based on Fiber Bragg gratings 使用ORMOCER®s作为基于光纤光栅的3D形状传感器的铸造材料

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827628

C. Ledermann, H. Pauer, H. Woern, M. Seyfried, G. Domann, H. Wolter

引用次数: 7