2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)最新文献_第2页

An optical flow feature and McFIS based approach for 3-dimensional human action recognition 基于光流特征和McFIS的三维人体动作识别方法

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827689

K. Subramanian, R. Venkatesh Babu, S. Suresh

{"title":"An optical flow feature and McFIS based approach for 3-dimensional human action recognition","authors":"K. Subramanian, R. Venkatesh Babu, S. Suresh","doi":"10.1109/ISSNIP.2014.6827689","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827689","url":null,"abstract":"We propose to develop a 3-D optical flow features based human action recognition system. Optical flow based features are employed here since they can capture the apparent movement in object, by design. Moreover, they can represent information hierarchically from local pixel level to global object level. In this work, 3-D optical flow based features are extracted by combining the 2-D optical flow based features with the depth flow features o btained from d epth camera. In order to develop an action recognition system, we employ a Meta-Cognitive Neuro-Fuzzy Inference System (McFIS). The aim of McFIS is to find the decision boundary separating different classes based on their respective optical flow based features. McFIS consists of a neuro-fuzzy inference system (cognitive component) and a self-regulatory learning mechanism (meta-cognitive component). During the supervised learning, self-regulatory learning mechanism monitors the knowledge of the current sample with respect to the existing knowledge in the network and controls the learning by deciding on sample deletion, sample learning or sample reserve strategies. The performance of the proposed action recognition system was evaluated on a proprietary data set consisting of eight subjects. The performance evaluation with standard support vector machine classifier and extreme learning machine indicates improved performance of McFIS is recognizing actions based of 3-D optical flow based features.","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":"115814291","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

Single port, large area touch and force sensing: Towards low cost sensitive printed surfaces 单端口，大面积触摸和力传感:面向低成本敏感印刷表面

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827695

S. Blayac, Arnaud Schreiner, Maxime Nouaille, Beatrice Dubois, F. Depoutot

引用次数: 5

Transmission Power Control based on temperature and relative humidity 基于温度和相对湿度的传输功率控制

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827674

César Ortega-Corral, Luis E. Palafox, J. A. García-Macías, J. Sánchez-García, Leocundo Aguilar, J. Nieto-Hipólito

{"title":"Transmission Power Control based on temperature and relative humidity","authors":"César Ortega-Corral, Luis E. Palafox, J. A. García-Macías, J. Sánchez-García, Leocundo Aguilar, J. Nieto-Hipólito","doi":"10.1109/ISSNIP.2014.6827674","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827674","url":null,"abstract":"In this paper we present a novel Wireless Sensor Network (WSN) Transmission Power Control (TPC) scheme based on prevailing weather conditions: temperature and relative humidity (TRH). After the analysis of several days worth of experimental data containing received signal strength indicator (RSSI) values, a strong correspondence became evident between signal loss and wireless channel weather conditions. This led us to characterize a TRH normalized gradient that describes a relative amount of power loss that is incurred when using the wireless channel. After review, we deployed this gradient with certain modifications as a gain coefficient in a novel way of compensating wireless transmission power. Meaning that a TRH TPC scheme is proposed, for more dependable wireless communications, which determines power gain using RSSI feedback. Performance metrics of a prototype TRH TPC algorithm, with differing parametric values, are presented and compared to another node with no TPC, transmitting at the same time with a fixed power level. Finally, after weighing in the full range of results, we establish a set of conditions where this TRH compensator is effective in improving the RSSI and the overall packet received rate (PRR), while operating in harsh daylight and humid conditions.","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":"114688741","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: 5

Performance analysis of a distributed 6LoWPAN network for the Smart Grid applications 面向智能电网应用的分布式6LoWPAN网络性能分析

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827646

Dong Chen, Jason Brown, J. Khan

引用次数: 14

Optical electronic nose based on porphyrin and phthalocyanine thin films for rice flavour classification 基于卟啉和酞菁薄膜的光学电子鼻用于大米风味分类

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827644

Rotthaporn Palasuek, S. Kladsomboon, T. Thepudom, T. Kerdcharoen

{"title":"Optical electronic nose based on porphyrin and phthalocyanine thin films for rice flavour classification","authors":"Rotthaporn Palasuek, S. Kladsomboon, T. Thepudom, T. Kerdcharoen","doi":"10.1109/ISSNIP.2014.6827644","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827644","url":null,"abstract":"In this paper, we have developed an optoelectronic nose for rice classification based on measurement of changes in the optical absorption of organic thin films upon interactions with volatile analytes. The organic thin films based on metalloporphyrin (ZnTPP) and metallophthalocyanine (ZnOBPc) for gas sensing application were fabricated by spin coating technique. The optical properties of these thin films were tested with UV-VIS spectrophotometry. The surface topology of the films was observed by atomic force microscopy (AFM) technique which reveals that the film's topology is homogeneous with nano-scale thickness. The sensing behavior of the films toward various volatile compounds representing the simulated aroma rice, such as 5% v/v hexanal, 5% v/v octanal and deionized water, was investigated under N2 atmosphere at room temperature. The results have shown that ZnTPP and ZnOBPc thin film gas sensors can discriminate such volatile compounds. The optoelectronic nose was then applied to examine the odors of Jasmine rice, normal white rice and various of their mixtures. It was shown that ZnOBPc thin film can clearly classify the type of rice better than ZnTPP thin film. These results were confirmed by computational quantum mechanics based on density functional theory, which reveals that ZnOBPc molecule binds to the simulated rice aroma molecules better than ZnTPP molecule.","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":"127206428","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

On-cloth wearable E-nose for monitoring and discrimination of body odor signature 用于监测和识别体臭特征的穿戴式电子鼻

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827634

T. Seesaard, Sasiprapa Seaon, P. Lorwongtragool, T. Kerdcharoen

引用次数: 5

Human cognition inspired particle swarm optimization algorithm 人类认知启发的粒子群优化算法

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827610

M. Tanweer, S. Sundaram

引用次数: 28

Performance evaluation of MQTT and CoAP via a common middleware 通过公共中间件对MQTT和CoAP进行性能评估

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827678

Dinesh Thangavel, Xiaoping Ma, A. Valera, H. Tan, C. Tan

{"title":"Performance evaluation of MQTT and CoAP via a common middleware","authors":"Dinesh Thangavel, Xiaoping Ma, A. Valera, H. Tan, C. Tan","doi":"10.1109/ISSNIP.2014.6827678","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827678","url":null,"abstract":"Wireless sensor networks (WSNs) typically consist of sensor nodes and gateways that operate on devices with limited resources. As a result, WSNs require bandwidth-efficient and energy-efficient application protocols for data transmission. Message Queue Telemetry Transport (MQTT) and Constrained Application Protocol (CoAP) are two such protocols proposed for resource-constrained devices. In this paper, we design and implement a common middleware that supports MQTT and CoAP and provides a common programming interface. We design the middleware to be extensible to support future protocols. Using the common middleware, we conducted experiments to study the performance of MQTT and CoAP in terms of end-to-end delay and bandwidth consumption. Experimental results reveal that MQTT messages have lower delay than CoAP messages at lower packet loss rates and higher delay than CoAP messages at higher loss rates. Moreover, when the message size is small and the loss rate is equal to or less than 25%, CoAP generates lower additional traffic than MQTT to ensure message reliability.","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":"130970808","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: 403

On the utility of overhearing in DTN 论窃听在数字电视中的应用

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827701

Xiangfa Guo, M. Chan

引用次数: 0

Database independent human emotion recognition with Meta-Cognitive Neuro-Fuzzy Inference System 基于元认知神经模糊推理系统的数据库独立人类情感识别

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827690

K. Subramanian, R. Venkatesh Babu, Savitha Ramasamy

{"title":"Database independent human emotion recognition with Meta-Cognitive Neuro-Fuzzy Inference System","authors":"K. Subramanian, R. Venkatesh Babu, Savitha Ramasamy","doi":"10.1109/ISSNIP.2014.6827690","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827690","url":null,"abstract":"Facial emotions are the most expressive way to display emotions. Many algorithms have been proposed which employ a particular set of people (usually a database) to both train and test their model. This paper focuses on the challenging task of database independent emotion recognition, which is a generalized case of subject-independent emotion recognition. The emotion recognition system employed in this work is a Meta-Cognitive Neuro-Fuzzy Inference System (McFIS). McFIS has two components, a neuro-fuzzy inference system, which is the cognitive component and a self-regulatory learning mechanism, which is the meta-cognitive component. The meta-cognitive component, monitors the knowledge in the neuro-fuzzy inference system and decides on what-to-learn, when-to-learn and how-to-learn the training samples, efficiently. For each sample, the McFIS decides whether to delete the sample without being learnt, use it to add/ prune or update the network parameter or reserve it for future use. This helps the network avoid over-training and as a result improve its generalization performance over untrained databases. In this study, we extract pixel based emotion features from well-known (Japanese Female Facial Expression) JAFFE and (Taiwanese Female Expression Image) TFEID database. Two sets of experiment are conducted. First, we study the individual performance of both databases on McFIS based on 5-fold cross validation study. Next, in order to study the generalization performance, McFIS trained on JAFFE database is tested on TFEID and vice-versa. The performance The performance comparison in both experiments against SVM classifier gives promising results.","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":"123134233","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